Cavitation | 캐비테이션

캐비테이션이란 무엇입니까?

The spillways of the Glen Canyon dam in 1983 (Lee and Hoopes, 1996).

캐비테이션은 유체 흐름의 매우 낮은 압력 또는 포화 압력을 높이는 온도 상승으로 인해 유체 내에서 증기 또는 기포가 빠르게 발생하는 것입니다. 기포의 갑작스런 출현 (및 후속 붕괴)은 비압축성 유체 내에서 압력의 급격한 변화를 일으켜 심각한 기계적 손상을 일으킬 수 있습니다. 캐비테이션에 의해 유도 된 힘은 1983 년 Glen Canyon 댐의 배수로에서 경험 한 손상에서 볼 수 있듯이 며칠 내에 수 피트의 암석을 침식 할 가능성이 있습니다 (Lee and Hoopes, 1996).

또한 고압 다이 캐스팅에서 캐비테이션이 발생할 수 있습니다. 다이의 수축 및 곡선을 통한 용융 합금의 빠른 이동은 급속한 압력 강하를 초래하고 후속 캐비테이션으로 이어질 수 있습니다. 생성된 증기 기포는 최종 주조에서 다공성을 유발하거나 더 나쁜 경우 다이에 손상을 일으켜 주조품을 훼손시키고 다이 수명을 감소시킬 수 있습니다.

캐비테이션은 터빈과 파이프에 손상을 줄 수 있고, 댐의 배수로에서 콘크리트를 침식하는 등의 원인이 될 수 있습니다. 아래 이미지는 댐의 배수로 바닥 근처의 콘크리트 침식을 보여줍니다. 댐에 사용되는 콘크리트는 일반적으로 강도가 높지만 캐비테이션은 여전히 그것을 부식시킬 수 있습니다.

Eroded concrete due to cavitation on the spillway of a dam

캐비테이션은 때때로 오염 물질과 유기 분자를 분해하고, 소수성 화학 물질을 결합하고, 캐비테이션 기포의 파열로 인해 생성 된 충격파를 통해 신장 결석을 파괴하고, 혼합을위한 난류를 증가시켜 수질 정화와 같은 특정 산업 응용 분야에서 의도적으로 유도됩니다.

따라서 캐비테이션이 발생할 가능성이있는 위치와 그 강도를 이해하는 것이 중요합니다. 캐비테이션을 실험을 수행하거나 실험 결과의 현상을 시각화하는 것이 어렵고, 잠재적으로 손상 될 수 있으므로 수치해석 시뮬레이션으로 검토하는 것이 매우 필요하고, 유용합니다.

Real-World Applications | 실제 응용 분야

  • 물 및 환경 구조 내에서 손상을 주는 캐비테이션 시뮬레이션
  • 다이 손상 및 주조 다공성을 유발할 수 있는 고압 다이 캐스팅 중 캐비테이션 시뮬레이션
  • MEMS 장치 내의 열 거품 형성 시뮬레이션
  • 열 전달 표면의 비등 거동 예측
  • 캐비테이션 역학으로 인한 혼합 예측

Modeling Cavitation in FLOW-3D

FLOW-3D의 캐비테이션 모델은 thermal bubble jets 와 MEMS devices를 시뮬레이션하는데 성공적으로 사용되었습니다. FLOW-3D는 “active”또는 “passive” 모델 옵션을 제공합니다. Active 모델은 기포 영역을 열고 수동 모델은 흐름을 통해 캐비테이션 기포의 존재를 추적하고 전파하지만, 기포 영역의 형성을 시작하지는 않습니다.

Active모델은 더 큰 캐비테이션 영역이 예상되고 유동장에 영향을 미치는 경우에 가장 적합하며, Passive모델은 작은 기포의 간단한 모양이 예상되는 시뮬레이션에 가장 적합합니다. 활성 모델과 에너지 전송 계산을 통해 위상 변화도 옵션입니다. 기포는 계면에서의 증발 또는 응축으로 인해 추가로 팽창하거나 수축 할 수 있습니다.

Sample Results

아래 시뮬레이션은 수축 노즐을 보여줍니다. 애니메이션은 매우 일시적인 진동 동작을 보여주는 캐비테이션 버블의 진화를 보여줍니다. 캐비테이션 부피 분율은 초기 연속 액체에서 캐비테이션의 시작을 시각화하기 위해 플롯됩니다.

아래 애니메이션은 진입 속도가 8m/s이고 수렴 기울기가 18 °이고 발산 기울기가 8 ° 인 벤츄리 내의 캐비테이션을 보여줍니다. 다시 말하지만, 캐비테이션의 과도 동작은 잘 모델링되어 있으며, 모델은 22ms의 실험 결과와 비교하여 17.4ms의 캐비테이션주기 기간을 예측합니다 (Stutz and Reboud 1997).

Cavitation in a venturi

물 탱크를 통해 이동하는 고속 발사체를 시뮬레이션하여 발사체 후류에서 생성 된 저압 영역의 공동 기둥을 보여줍니다. 발사체의 초기 속도는 600m / s입니다. 아래는 탱크의 움직임과 후행하는 캐비테이션 유체의 애니메이션입니다. 발사체가 감속함에 따라 캐비테이션 기둥의 반경이 좁아집니다.

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High-speed bullet

References

Lee, W., Hoopes, J.A., 1996, Prediction of Cavitation Damage for Spillways, Journal of Hydraulic Engineering, 122(9): 481-488.

Plesset, M.S., Prosperetti, A., 1977, Bubble Dynamics and Cavitation, Annual Revue of Fluid Mech, 9: 145-185.

Rouse, H., 1946. Elementary Mechanics of Fluids, New York: Dover Publications, Inc.

Stutz, B., Reboud, J.L., 1997, Experiments on unsteady cavitation, Experiments in Fluids, 22: 191-198.

FLOW-3D CAST Bibliography

FLOW-3D CAST bibliography

아래는 FSI의 금속 주조 참고 문헌에 수록된 기술 논문 모음입니다. 이 모든 논문에는 FLOW-3D CAST 해석 결과가 수록되어 있습니다. FLOW-3D CAST를 사용하여 금속 주조 산업의 응용 프로그램을 성공적으로 시뮬레이션하는 방법에 대해 자세히 알아보십시오.

Below is a collection of technical papers in our Metal Casting Bibliography. All of these papers feature FLOW-3D CAST results. Learn more about how FLOW-3D CAST can be used to successfully simulate applications for the Metal Casting Industry.

33-20     Eric Riedel, Martin Liepe Stefan Scharf, Simulation of ultrasonic induced cavitation and acoustic streaming in liquid and solidifying aluminum, Metals, 10.4; 476, 2020. doi.org/10.3390/met10040476

20-20   Wu Yue, Li Zhuo and Lu Rong, Simulation and visual tester verification of solid propellant slurry vacuum plate casting, Propellants, Explosives, Pyrotechnics, 2020. doi.org/10.1002/prep.201900411

17-20   C.A. Jones, M.R. Jolly, A.E.W. Jarfors and M. Irwin, An experimental characterization of thermophysical properties of a porous ceramic shell used in the investment casting process, Supplimental Proceedings, pp. 1095-1105, TMS 2020 149th Annual Meeting and Exhibition, San Diego, CA, February 23-27, 2020. doi.org/10.1007/978-3-030-36296-6_102

12-20   Franz Josef Feikus, Paul Bernsteiner, Ricardo Fernández Gutiérrez and Michal Luszczak , Further development of electric motor housings, MTZ Worldwide, 81, pp. 38-43, 2020. doi.org/10.1007/s38313-019-0176-z

09-20   Mingfan Qi, Yonglin Kang, Yuzhao Xu, Zhumabieke Wulabieke and Jingyuan Li, A novel rheological high pressure die-casting process for preparing large thin-walled Al–Si–Fe–Mg–Sr alloy with high heat conductivity, high plasticity and medium strength, Materials Science and Engineering: A, 776, art. no. 139040, 2020. doi.org/10.1016/j.msea.2020.139040

07-20   Stefan Heugenhauser, Erhard Kaschnitz and Peter Schumacher, Development of an aluminum compound casting process – Experiments and numerical simulations, Journal of Materials Processing Technology, 279, art. no. 116578, 2020. doi.org/10.1016/j.jmatprotec.2019.116578

05-20   Michail Papanikolaou, Emanuele Pagone, Mark Jolly and Konstantinos Salonitis, Numerical simulation and evaluation of Campbell running and gating systems, Metals, 10.1, art. no. 68, 2020. doi.org/10.3390/met10010068

102-19   Ferencz Peti and Gabriela Strnad, The effect of squeeze pin dimension and operational parameters on material homogeneity of aluminium high pressure die cast parts, Acta Marisiensis. Seria Technologica, 16.2, 2019. doi.org/0.2478/amset-2019-0010

94-19   E. Riedel, I. Horn, N. Stein, H. Stein, R. Bahr, and S. Scharf, Ultrasonic treatment: a clean technology that supports sustainability incasting processes, Procedia, 26th CIRP Life Cycle Engineering (LCE) Conference, Indianapolis, Indiana, USA, May 7-9, 2019. 

93-19   Adrian V. Catalina, Liping Xue, Charles A. Monroe, Robin D. Foley, and John A. Griffin, Modeling and Simulation of Microstructure and Mechanical Properties of AlSi- and AlCu-based Alloys, Transactions, 123rd Metalcasting Congress, Atlanta, GA, USA, April 27-30, 2019. 

84-19   Arun Prabhakar, Michail Papanikolaou, Konstantinos Salonitis, and Mark Jolly, Sand casting of sheet lead: numerical simulation of metal flow and solidification, The International Journal of Advanced Manufacturing Technology, pp. 1-13, 2019. doi.org/10.1007/s00170-019-04522-3

72-19   Santosh Reddy Sama, Eric Macdonald, Robert Voigt, and Guha Manogharan, Measurement of metal velocity in sand casting during mold filling, Metals, 9:1079, 2019. doi.org/10.3390/met9101079

71-19   Sebastian Findeisen, Robin Van Der Auwera, Michael Heuser, and Franz-Josef Wöstmann, Gießtechnische Fertigung von E-Motorengehäusen mit interner Kühling (Casting production of electric motor housings with internal cooling), Geisserei, 106, pp. 72-78, 2019 (in German).

58-19     Von Malte Leonhard, Matthias Todte, and Jörg Schäffer, Realistic simulation of the combustion of exothermic feeders, Casting, No. 2, pp. 28-32, 2019. In English and German.

52-19     S. Lakkum and P. Kowitwarangkul, Numerical investigations on the effect of gas flow rate in the gas stirred ladle with dual plugs, International Conference on Materials Research and Innovation (ICMARI), Bangkok, Thailand, December 17-21, 2018. IOP Conference Series: Materials Science and Engineering, Vol. 526, 2019. doi.org/10.1088/1757-899X/526/1/012028

47-19     Bing Zhou, Shuai Lu, Kaile Xu, Chun Xu, and Zhanyong Wang, Microstructure and simulation of semisolid aluminum alloy castings in the process of stirring integrated transfer-heat (SIT) with water cooling, International Journal of Metalcasting, Online edition, pp. 1-13, 2019. doi.org/10.1007/s40962-019-00357-6

31-19     Zihao Yuan, Zhipeng Guo, and S.M. Xiong, Skin layer of A380 aluminium alloy die castings and its blistering during solution treatment, Journal of Materials Science & Technology, Vol. 35, No. 9, pp. 1906-1916, 2019. doi.org/10.1016/j.jmst.2019.05.011

25-19     Stefano Mascetti, Raul Pirovano, and Giulio Timelli, Interazione metallo liquido/stampo: Il fenomeno della metallizzazione, La Metallurgia Italiana, No. 4, pp. 44-50, 2019. In Italian.

20-19     Fu-Yuan Hsu, Campbellology for runner system design, Shape Casting: The Minerals, Metals & Materials Series, pp. 187-199, 2019. doi.org/10.1007/978-3-030-06034-3_19

19-19     Chengcheng Lyu, Michail Papanikolaou, and Mark Jolly, Numerical process modelling and simulation of Campbell running systems designs, Shape Casting: The Minerals, Metals & Materials Series, pp. 53-64, 2019. doi.org/10.1007/978-3-030-06034-3_5

18-19     Adrian V. Catalina, Liping Xue, and Charles Monroe, A solidification model with application to AlSi-based alloys, Shape Casting: The Minerals, Metals & Materials Series, pp. 201-213, 2019. doi.org/10.1007/978-3-030-06034-3_20

17-19     Fu-Yuan Hsu and Yu-Hung Chen, The validation of feeder modeling for ductile iron castings, Shape Casting: The Minerals, Metals & Materials Series, pp. 227-238, 2019. doi.org/10.1007/978-3-030-06034-3_22

04-19   Santosh Reddy Sama, Tony Badamo, Paul Lynch and Guha Manogharan, Novel sprue designs in metal casting via 3D sand-printing, Additive Manufacturing, Vol. 25, pp. 563-578, 2019. doi.org/10.1016/j.addma.2018.12.009

02-19   Jingying Sun, Qichi Le, Li Fu, Jing Bai, Johannes Tretter, Klaus Herbold and Hongwei Huo, Gas entrainment behavior of aluminum alloy engine crankcases during the low-pressure-die-casting-process, Journal of Materials Processing Technology, Vol. 266, pp. 274-282, 2019. doi.org/10.1016/j.jmatprotec.2018.11.016

92-18   Fast, Flexible… More Versatile, Foundry Management Technology, March, 2018. 

82-18   Xu Zhao, Ping Wang, Tao Li, Bo-yu Zhang, Peng Wang, Guan-zhou Wang and Shi-qi Lu, Gating system optimization of high pressure die casting thin-wall AlSi10MnMg longitudinal loadbearing beam based on numerical simulation, China Foundry, Vol. 15, no. 6, pp. 436-442, 2018. doi: 10.1007/s41230-018-8052-z

80-18   Michail Papanikolaou, Emanuele Pagone, Konstantinos Salonitis, Mark Jolly and Charalampos Makatsoris, A computational framework towards energy efficient casting processes, Sustainable Design and Manufacturing 2018: Proceedings of the 5th International Conference on Sustainable Design and Manufacturing (KES-SDM-18), Gold Coast, Australia, June 24-26 2018, SIST 130, pp. 263-276, 2019. doi.org/10.1007/978-3-030-04290-5_27

64-18   Vasilios Fourlakidis, Ilia Belov and Attila Diószegi, Strength prediction for pearlitic lamellar graphite iron: Model validation, Metals, Vol. 8, No. 9, 2018. doi.org/10.3390/met8090684

51-18   Xue-feng Zhu, Bao-yi Yu, Li Zheng, Bo-ning Yu, Qiang Li, Shu-ning Lü and Hao Zhang, Influence of pouring methods on filling process, microstructure and mechanical properties of AZ91 Mg alloy pipe by horizontal centrifugal casting, China Foundry, vol. 15, no. 3, pp.196-202, 2018. doi.org/10.1007/s41230-018-7256-6

47-18   Santosh Reddy Sama, Jiayi Wang and Guha Manogharan, Non-conventional mold design for metal casting using 3D sand-printing, Journal of Manufacturing Processes, vol. 34-B, pp. 765-775, 2018. doi.org/10.1016/j.jmapro.2018.03.049

42-18   M. Koru and O. Serçe, The Effects of Thermal and Dynamical Parameters and Vacuum Application on Porosity in High-Pressure Die Casting of A383 Al-Alloy, International Journal of Metalcasting, pp. 1-17, 2018. doi.org/10.1007/s40962-018-0214-7

41-18   Abhilash Viswanath, S. Savithri, U.T.S. Pillai, Similitude analysis on flow characteristics of water, A356 and AM50 alloys during LPC process, Journal of Materials Processing Technology, vol. 257, pp. 270-277, 2018. doi.org/10.1016/j.jmatprotec.2018.02.031

29-18   Seyboldt, Christoph and Liewald, Mathias, Investigation on thixojoining to produce hybrid components with intermetallic phase, AIP Conference Proceedings, vol. 1960, no. 1, 2018. doi.org/10.1063/1.5034992

28-18   Laura Schomer, Mathias Liewald and Kim Rouven Riedmüller, Simulation of the infiltration process of a ceramic open-pore body with a metal alloy in semi-solid state to design the manufacturing of interpenetrating phase composites, AIP Conference Proceedings, vol. 1960, no. 1, 2018. doi.org/10.1063/1.5034991

41-17   Y. N. Wu et al., Numerical Simulation on Filling Optimization of Copper Rotor for High Efficient Electric Motors in Die Casting Process, Materials Science Forum, Vol. 898, pp. 1163-1170, 2017.

12-17   A.M.  Zarubin and O.A. Zarubina, Controlling the flow rate of melt in gravity die casting of aluminum alloys, Liteynoe Proizvodstvo (Casting Manufacturing), pp 16-20, 6, 2017. In Russian.

10-17   A.Y. Korotchenko, Y.V. Golenkov, M.V. Tverskoy and D.E. Khilkov, Simulation of the Flow of Metal Mixtures in the Mold, Liteynoe Proizvodstvo (Casting Manufacturing), pp 18-22, 5, 2017. In Russian.

08-17   Morteza Morakabian Esfahani, Esmaeil Hajjari, Ali Farzadi and Seyed Reza Alavi Zaree, Prediction of the contact time through modeling of heat transfer and fluid flow in compound casting process of Al/Mg light metals, Journal of Materials Research, © Materials Research Society 2017

04-17   Huihui Liu, Xiongwei He and Peng Guo, Numerical simulation on semi-solid die-casting of magnesium matrix composite based on orthogonal experiment, AIP Conference Proceedings 1829, 020037 (2017); doi.org/10.1063/1.4979769.

100-16  Robert Watson, New numerical techniques to quantify and predict the effect of entrainment defects, applied to high pressure die casting, PhD Thesis: University of Birmingham, 2016.

88-16   M.C. Carter, T. Kauffung, L. Weyenberg and C. Peters, Low Pressure Die Casting Simulation Discovery through Short Shot, Cast Expo & Metal Casting Congress, April 16-19, 2016, Minneapolis, MN, Copyright 2016 American Foundry Society.

61-16   M. Koru and O. Serçe, Experimental and numerical determination of casting mold interfacial heat transfer coefficient in the high pressure die casting of a 360 aluminum alloy, ACTA PHYSICA POLONICA A, Vol. 129 (2016)

59-16   R. Pirovano and S. Mascetti, Tracking of collapsed bubbles during a filling simulation, La Metallurgia Italiana – n. 6 2016

43-16   Kevin Lee, Understanding shell cracking during de-wax process in investment casting, Ph.D Thesis: University of Birmingham, School of Engineering, Department of Chemical Engineering, 2016.

35-16   Konstantinos Salonitis, Mark Jolly, Binxu Zeng, and Hamid Mehrabi, Improvements in energy consumption and environmental impact by novel single shot melting process for casting, Journal of Cleaner Production, doi.org/10.1016/j.jclepro.2016.06.165, Open Access funded by Engineering and Physical Sciences Research Council, June 29, 2016

20-16   Fu-Yuan Hsu, Bifilm Defect Formation in Hydraulic Jump of Liquid Aluminum, Metallurgical and Materials Transactions B, 2016, Band: 47, Heft 3, 1634-1648.

15-16   Mingfan Qia, Yonglin Kanga, Bing Zhoua, Wanneng Liaoa, Guoming Zhua, Yangde Lib,and Weirong Li, A forced convection stirring process for Rheo-HPDC aluminum and magnesium alloys, Journal of Materials Processing Technology 234 (2016) 353–367

112-15   José Miguel Gonçalves Ledo Belo da Costa, Optimization of filling systems for low pressure by FLOW-3D, Dissertação de mestrado integrado em Engenharia Mecânica, 2015.

89-15   B.W. Zhu, L.X. Li, X. Liu, L.Q. Zhang and R. Xu, Effect of Viscosity Measurement Method to Simulate High Pressure Die Casting of Thin-Wall AlSi10MnMg Alloy Castings, Journal of Materials Engineering and Performance, Published online, November 2015, doi.org/10.1007/s11665-015-1783-8, © ASM International.

88-15   Peng Zhang, Zhenming Li, Baoliang Liu, Wenjiang Ding and Liming Peng, Improved tensile properties of a new aluminum alloy for high pressure die casting, Materials Science & Engineering A651(2016)376–390, Available online, November 2015.

83-15   Zu-Qi Hu, Xin-Jian Zhang and Shu-Sen Wu, Microstructure, Mechanical Properties and Die-Filling Behavior of High-Performance Die-Cast Al–Mg–Si–Mn Alloy, Acta Metall. Sin. (Engl. Lett.), doi.org/10.1007/s40195-015-0332-7, © The Chinese Society for Metals and Springer-Verlag Berlin Heidelberg 2015.

82-15   J. Müller, L. Xue, M.C. Carter, C. Thoma, M. Fehlbier and M. Todte, A Die Spray Cooling Model for Thermal Die Cycling Simulations, 2015 Die Casting Congress & Exposition, Indianapolis, IN, October 2015

81-15   M. T. Murray, L.F. Hansen, L. Chilcott, E. Li and A.M. Murray, Case Studies in the Use of Simulation- Improved Yield and Reduced Time to Market, 2015 Die Casting Congress & Exposition, Indianapolis, IN, October 2015

80-15   R. Bhola, S. Chandra and D. Souders, Predicting Castability of Thin-Walled Parts for the HPDC Process Using Simulations, 2015 Die Casting Congress & Exposition, Indianapolis, IN, October 2015

76-15   Prosenjit Das, Sudip K. Samanta, Shashank Tiwari and Pradip Dutta, Die Filling Behaviour of Semi Solid A356 Al Alloy Slurry During Rheo Pressure Die Casting, Transactions of the Indian Institute of Metals, pp 1-6, October 2015

74-15   Murat KORU and Orhan SERÇE, Yüksek Basınçlı Döküm Prosesinde Enjeksiyon Parametrelerine Bağlı Olarak Döküm Simülasyon, Cumhuriyet University Faculty of Science, Science Journal (CSJ), Vol. 36, No: 5 (2015) ISSN: 1300-1949, May 2015

69-15   A. Viswanath, S. Sivaraman, U. T. S. Pillai, Computer Simulation of Low Pressure Casting Process Using FLOW-3D, Materials Science Forum, Vols. 830-831, pp. 45-48, September 2015

68-15   J. Aneesh Kumar, K. Krishnakumar and S. Savithri, Computer Simulation of Centrifugal Casting Process Using FLOW-3D, Materials Science Forum, Vols. 830-831, pp. 53-56, September 2015

59-15   F. Hosseini Yekta and S. A. Sadough Vanini, Simulation of the flow of semi-solid steel alloy using an enhanced model, Metals and Materials International, August 2015.

44-15   Ulrich E. Klotz, Tiziana Heiss and Dario Tiberto, Platinum investment casting material properties, casting simulation and optimum process parameters, Jewelry Technology Forum 2015

41-15   M. Barkhudarov and R. Pirovano, Minimizing Air Entrainment in High Pressure Die Casting Shot Sleeves, GIFA 2015, Düsseldorf, Germany

40-15   M. Todte, A. Fent, and H. Lang, Simulation in support of the development of innovative processes in the casting industry, GIFA 2015, Düsseldorf, Germany

19-15   Bruce Morey, Virtual casting improves powertrain design, Automotive Engineering, SAE International, March 2015.

15-15   K.S. Oh, J.D. Lee, S.J. Kim and J.Y. Choi, Development of a large ingot continuous caster, Metall. Res. Technol. 112, 203 (2015) © EDP Sciences, 2015, doi.org/10.1051/metal/2015006, www.metallurgical-research.org

14-15   Tiziana Heiss, Ulrich E. Klotz and Dario Tiberto, Platinum Investment Casting, Part I: Simulation and Experimental Study of the Casting Process, Johnson Matthey Technol. Rev., 2015, 59, (2), 95, doi.org/10.1595/205651315×687399

138-14 Christopher Thoma, Wolfram Volk, Ruben Heid, Klaus Dilger, Gregor Banner and Harald Eibisch, Simulation-based prediction of the fracture elongation as a failure criterion for thin-walled high-pressure die casting components, International Journal of Metalcasting, Vol. 8, No. 4, pp. 47-54, 2014. doi.org/10.1007/BF03355594

107-14  Mehran Seyed Ahmadi, Dissolution of Si in Molten Al with Gas Injection, ProQuest Dissertations And Theses; Thesis (Ph.D.), University of Toronto (Canada), 2014; Publication Number: AAT 3637106; ISBN: 9781321195231; Source: Dissertation Abstracts International, Volume: 76-02(E), Section: B.; 191 p.

99-14   R. Bhola and S. Chandra, Predicting Castability for Thin-Walled HPDC Parts, Foundry Management Technology, December 2014

92-14   Warren Bishenden and Changhua Huang, Venting design and process optimization of die casting process for structural components; Part II: Venting design and process optimization, Die Casting Engineer, November 2014

90-14   Ken’ichi Kanazawa, Ken’ichi Yano, Jun’ichi Ogura, and Yasunori Nemoto, Optimum Runner Design for Die-Casting using CFD Simulations and Verification with Water-Model Experiments, Proceedings of the ASME 2014 International Mechanical Engineering Congress and Exposition, IMECE2014, November 14-20, 2014, Montreal, Quebec, Canada, IMECE2014-37419

89-14   P. Kapranos, C. Carney, A. Pola, and M. Jolly, Advanced Casting Methodologies: Investment Casting, Centrifugal Casting, Squeeze Casting, Metal Spinning, and Batch Casting, In Comprehensive Materials Processing; McGeough, J., Ed.; 2014, Elsevier Ltd., 2014; Vol. 5, pp 39–67.

77-14   Andrei Y. Korotchenko, Development of Scientific and Technological Approaches to Casting Net-Shaped Castings in Sand Molds Free of Shrinkage Defects and Hot Tears, Post-doctoral thesis: Russian State Technological University, 2014. In Russian.

69-14   L. Xue, M.C. Carter, A.V. Catalina, Z. Lin, C. Li, and C. Qiu, Predicting, Preventing Core Gas Defects in Steel Castings, Modern Casting, September 2014

68-14   L. Xue, M.C. Carter, A.V. Catalina, Z. Lin, C. Li, and C. Qiu, Numerical Simulation of Core Gas Defects in Steel Castings, Copyright 2014 American Foundry Society, 118th Metalcasting Congress, April 8 – 11, 2014, Schaumburg, IL

51-14   Jesus M. Blanco, Primitivo Carranza, Rafael Pintos, Pedro Arriaga, and Lakhdar Remaki, Identification of Defects Originated during the Filling of Cast Pieces through Particles Modelling, 11th World Congress on Computational Mechanics (WCCM XI), 5th European Conference on Computational Mechanics (ECCM V), 6th European Conference on Computational Fluid Dynamics (ECFD VI), E. Oñate, J. Oliver and A. Huerta (Eds)

47-14   B. Vijaya Ramnatha, C.Elanchezhiana, Vishal Chandrasekhar, A. Arun Kumarb, S. Mohamed Asif, G. Riyaz Mohamed, D. Vinodh Raj , C .Suresh Kumar, Analysis and Optimization of Gating System for Commutator End Bracket, Procedia Materials Science 6 ( 2014 ) 1312 – 1328, 3rd International Conference on Materials Processing and Characterisation (ICMPC 2014)

42-14  Bing Zhou, Yong-lin Kang, Guo-ming Zhu, Jun-zhen Gao, Ming-fan Qi, and Huan-huan Zhang, Forced convection rheoforming process for preparation of 7075 aluminum alloy semisolid slurry and its numerical simulation, Trans. Nonferrous Met. Soc. China 24(2014) 1109−1116

37-14    A. Karwinski, W. Lesniewski, P. Wieliczko, and M. Malysza, Casting of Titanium Alloys in Centrifugal Induction Furnaces, Archives of Metallurgy and Materials, Volume 59, Issue 1, doi.org/10.2478/amm-2014-0068, 2014.

26-14    Bing Zhou, Yonglin Kang, Mingfan Qi, Huanhuan Zhang and Guoming ZhuR-HPDC Process with Forced Convection Mixing Device for Automotive Part of A380 Aluminum Alloy, Materials 2014, 7, 3084-3105; doi.org/10.3390/ma7043084

20-14  Johannes Hartmann, Tobias Fiegl, Carolin Körner, Aluminum integral foams with tailored density profile by adapted blowing agents, Applied Physics A, doi.org/10.1007/s00339-014-8377-4, March 2014.

19-14    A.Y. Korotchenko, N.A. Nikiforova, E.D. Demjanov, N.C. Larichev, The Influence of the Filling Conditions on the Service Properties of the Part Side Frame, Russian Foundryman, 1 (January), pp 40-43, 2014. In Russian.

11-14 B. Fuchs and C. Körner, Mesh resolution consideration for the viability prediction of lost salt cores in the high pressure die casting process, Progress in Computational Fluid Dynamics, Vol. 14, No. 1, 2014, Copyright © 2014 Inderscience Enterprises Ltd.

08-14 FY Hsu, SW Wang, and HJ Lin, The External and Internal Shrinkages in Aluminum Gravity Castings, Shape Casting: 5th International Symposium 2014. Available online at Google Books

103-13  B. Fuchs, H. Eibisch and C. Körner, Core Viability Simulation for Salt Core Technology in High-Pressure Die Casting, International Journal of Metalcasting, July 2013, Volume 7, Issue 3, pp 39–45

94-13    Randall S. Fielding, J. Crapps, C. Unal, and J.R.Kennedy, Metallic Fuel Casting Development and Parameter Optimization Simulations, International Conference on Fast reators and Related Fuel Cycles (FR13), 4-7 March 2013, Paris France

90-13  A. Karwińskia, M. Małyszaa, A. Tchórza, A. Gila, B. Lipowska, Integration of Computer Tomography and Simulation Analysis in Evaluation of Quality of Ceramic-Carbon Bonded Foam Filter, Archives of Foundry Engineering, doi.org/10.2478/afe-2013-0084, Published quarterly as the organ of the Foundry Commission of the Polish Academy of Sciences, ISSN, (2299-2944), Volume 13, Issue 4/2013

88-13  Litie and Metallurgia (Casting and Metallurgy), 3 (72), 2013, N.V.Sletova, I.N.Volnov, S.P.Zadrutsky, V.A.Chaikin, Modeling of the Process of Removing Non-metallic Inclusions in Aluminum Alloys Using the FLOW-3D program, pp 138-140. In Russian.

85-13    Michał Szucki,Tomasz Goraj, Janusz Lelito, Józef S. Suchy, Numerical Analysis of Solid Particles Flow in Liquid Metal, XXXVII International Scientific Conference Foundryman’ Day 2013, Krakow, 28-29 November 2013

84-13  Körner, C., Schwankl, M., Himmler, D., Aluminum-Aluminum compound castings by electroless deposited zinc layers, Journal of Materials Processing Technology (2014), doi.org/10.1016/j.jmatprotec.2013.12.01483-13.

77-13  Antonio Armillotta & Raffaello Baraggi & Simone Fasoli, SLM tooling for die casting with conformal cooling channels, The International Journal of Advanced Manufacturing Technology, doi.org/10.1007/s00170-013-5523-7, December 2013.

64-13   Johannes Hartmann, Christina Blümel, Stefan Ernst, Tobias Fiegl, Karl-Ernst Wirth, Carolin Körner, Aluminum integral foam castings with microcellular cores by nano-functionalization, J Mater Sci, doi.org/10.1007/s10853-013-7668-z, September 2013.

46-13  Nicholas P. Orenstein, 3D Flow and Temperature Analysis of Filling a Plutonium Mold, LA-UR-13-25537, Approved for public release; distribution is unlimited. Los Alamos Annual Student Symposium 2013, 2013-07-24 (Rev.1)

42-13   Yang Yue, William D. Griffiths, and Nick R. Green, Modelling of the Effects of Entrainment Defects on Mechanical Properties in a Cast Al-Si-Mg Alloy, Materials Science Forum, 765, 225, 2013.

39-13  J. Crapps, D.S. DeCroix, J.D Galloway, D.A. Korzekwa, R. Aikin, R. Fielding, R. Kennedy, C. Unal, Separate effects identification via casting process modeling for experimental measurement of U-Pu-Zr alloys, Journal of Nuclear Materials, 15 July 2013.

35-13   A. Pari, Real Life Problem Solving through Simulations in the Die Casting Industry – Case Studies, © Die Casting Engineer, July 2013.

34-13  Martin Lagler, Use of Simulation to Predict the Viability of Salt Cores in the HPDC Process – Shot Curve as a Decisive Criterion, © Die Casting Engineer, July 2013.

24-13    I.N.Volnov, Optimizatsia Liteynoi Tekhnologii, (Casting Technology Optimization), Liteyshik Rossii (Russian Foundryman), 3, 2013, 27-29. In Russian

23-13  M.R. Barkhudarov, I.N. Volnov, Minimizatsia Zakhvata Vozdukha v Kamere Pressovania pri Litie pod Davleniem, (Minimization of Air Entrainment in the Shot Sleeve During High Pressure Die Casting), Liteyshik Rossii (Russian Foundryman), 3, 2013, 30-34. In Russian

09-13  M.C. Carter and L. Xue, Simulating the Parameters that Affect Core Gas Defects in Metal Castings, Copyright 2012 American Foundry Society, Presented at the 2013 CastExpo, St. Louis, Missouri, April 2013

08-13  C. Reilly, N.R. Green, M.R. Jolly, J.-C. Gebelin, The Modelling Of Oxide Film Entrainment In Casting Systems Using Computational Modelling, Applied Mathematical Modelling, http://dx.doi.org/10.1016/j.apm.2013.03.061, April 2013.

03-13  Alexandre Reikher and Krishna M. Pillai, A fast simulation of transient metal flow and solidification in a narrow channel. Part II. Model validation and parametric study, Int. J. Heat Mass Transfer (2013), http://dx.doi.org/10.1016/j.ijheatmasstransfer.2012.12.061.

02-13  Alexandre Reikher and Krishna M. Pillai, A fast simulation of transient metal flow and solidification in a narrow channel. Part I: Model development using lubrication approximation, Int. J. Heat Mass Transfer (2013), http://dx.doi.org/10.1016/j.ijheatmasstransfer.2012.12.060.

116-12  Jufu Jianga, Ying Wang, Gang Chena, Jun Liua, Yuanfa Li and Shoujing Luo, “Comparison of mechanical properties and microstructure of AZ91D alloy motorcycle wheels formed by die casting and double control forming, Materials & Design, Volume 40, September 2012, Pages 541-549.

107-12  F.K. Arslan, A.H. Hatman, S.Ö. Ertürk, E. Güner, B. Güner, An Evaluation for Fundamentals of Die Casting Materials Selection and Design, IMMC’16 International Metallurgy & Materials Congress, Istanbul, Turkey, 2012.

103-12 WU Shu-sen, ZHONG Gu, AN Ping, WAN Li, H. NAKAE, Microstructural characteristics of Al−20Si−2Cu−0.4Mg−1Ni alloy formed by rheo-squeeze casting after ultrasonic vibration treatment, Transactions of Nonferrous Metals Society of China, 22 (2012) 2863-2870, November 2012. Full paper available online.

109-12 Alexandre Reikher, Numerical Analysis of Die-Casting Process in Thin Cavities Using Lubrication Approximation, Ph.D. Thesis: The University of Wisconsin Milwaukee, Engineering Department (2012) Theses and Dissertations. Paper 65.

97-12 Hong Zhou and Li Heng Luo, Filling Pattern of Step Gating System in Lost Foam Casting Process and its Application, Advanced Materials Research, Volumes 602-604, Progress in Materials and Processes, 1916-1921, December 2012.

93-12  Liangchi Zhang, Chunliang Zhang, Jeng-Haur Horng and Zichen Chen, Functions of Step Gating System in the Lost Foam Casting Process, Advanced Materials Research, 591-593, 940, DOI: 10.4028/www.scientific.net/AMR.591-593.940, November 2012.

91-12  Hong Yan, Jian Bin Zhu, Ping Shan, Numerical Simulation on Rheo-Diecasting of Magnesium Matrix Composites, 10.4028/www.scientific.net/SSP.192-193.287, Solid State Phenomena, 192-193, 287.

89-12  Alexandre Reikher and Krishna M. Pillai, A Fast Numerical Simulation for Modeling Simultaneous Metal Flow and Solidification in Thin Cavities Using the Lubrication Approximation, Numerical Heat Transfer, Part A: Applications: An International Journal of Computation and Methodology, 63:2, 75-100, November 2012.

82-12  Jufu Jiang, Gang Chen, Ying Wang, Zhiming Du, Weiwei Shan, and Yuanfa Li, Microstructure and mechanical properties of thin-wall and high-rib parts of AM60B Mg alloy formed by double control forming and die casting under the optimal conditions, Journal of Alloys and Compounds, http://dx.doi.org/10.1016/j.jallcom.2012.10.086, October 2012.

78-12   A. Pari, Real Life Problem Solving through Simulations in the Die Casting Industry – Case Studies, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012, Indianapolis, IN.

77-12  Y. Wang, K. Kabiri-Bamoradian and R.A. Miller, Rheological behavior models of metal matrix alloys in semi-solid casting process, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012, Indianapolis, IN.

76-12  A. Reikher and H. Gerber, Analysis of Solidification Parameters During the Die Cast Process, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012, Indianapolis, IN.

75-12 R.A. Miller, Y. Wang and K. Kabiri-Bamoradian, Estimating Cavity Fill Time, 2012 Die Casting Congress & Exposition, © NADCA, October 8-10, 2012Indianapolis, IN.

65-12  X.H. Yang, T.J. Lu, T. Kim, Influence of non-conducting pore inclusions on phase change behavior of porous media with constant heat flux boundaryInternational Journal of Thermal Sciences, Available online 10 October 2012. Available online at SciVerse.

55-12  Hejun Li, Pengyun Wang, Lehua Qi, Hansong Zuo, Songyi Zhong, Xianghui Hou, 3D numerical simulation of successive deposition of uniform molten Al droplets on a moving substrate and experimental validation, Computational Materials Science, Volume 65, December 2012, Pages 291–301.

52-12 Hongbing Ji, Yixin Chen and Shengzhou Chen, Numerical Simulation of Inner-Outer Couple Cooling Slab Continuous Casting in the Filling Process, Advanced Materials Research (Volumes 557-559), Advanced Materials and Processes II, pp. 2257-2260, July 2012.

47-12    Petri Väyrynen, Lauri Holappa, and Seppo Louhenkilpi, Simulation of Melting of Alloying Materials in Steel Ladle, SCANMET IV – 4th International Conference on Process Development in Iron and Steelmaking, Lulea, Sweden, June 10-13, 2012.

46-12  Bin Zhang and Dave Salee, Metal Flow and Heat Transfer in Billet DC Casting Using Wagstaff® Optifill™ Metal Distribution Systems, 5th International Metal Quality Workshop, United Arab Emirates Dubai, March 18-22, 2012.

45-12 D.R. Gunasegaram, M. Givord, R.G. O’Donnell and B.R. Finnin, Improvements engineered in UTS and elongation of aluminum alloy high pressure die castings through the alteration of runner geometry and plunger velocity, Materials Science & Engineering.

44-12    Antoni Drys and Stefano Mascetti, Aluminum Casting Simulations, Desktop Engineering, September 2012

42-12   Huizhen Duan, Jiangnan Shen and Yanping Li, Comparative analysis of HPDC process of an auto part with ProCAST and FLOW-3D, Applied Mechanics and Materials Vols. 184-185 (2012) pp 90-94, Online available since 2012/Jun/14 at www.scientific.net, © (2012) Trans Tech Publications, Switzerland, doi:10.4028/www.scientific.net/AMM.184-185.90.

41-12    Deniece R. Korzekwa, Cameron M. Knapp, David A. Korzekwa, and John W. Gibbs, Co-Design – Fabrication of Unalloyed Plutonium, LA-UR-12-23441, MDI Summer Research Group Workshop Advanced Manufacturing, 2012-07-25/2012-07-26 (Los Alamos, New Mexico, United States)

29-12  Dario Tiberto and Ulrich E. Klotz, Computer simulation applied to jewellery casting: challenges, results and future possibilities, IOP Conf. Ser.: Mater. Sci. Eng.33 012008. Full paper available at IOP.

28-12  Y Yue and N R Green, Modelling of different entrainment mechanisms and their influences on the mechanical reliability of Al-Si castings, 2012 IOP Conf. Ser.: Mater. Sci. Eng. 33,012072.Full paper available at IOP.

27-12  E Kaschnitz, Numerical simulation of centrifugal casting of pipes, 2012 IOP Conf. Ser.: Mater. Sci. Eng. 33 012031, Issue 1. Full paper available at IOP.

15-12  C. Reilly, N.R Green, M.R. Jolly, The Present State Of Modeling Entrainment Defects In The Shape Casting Process, Applied Mathematical Modelling, Available online 27 April 2012, ISSN 0307-904X, 10.1016/j.apm.2012.04.032.

12-12   Andrei Starobin, Tony Hirt, Hubert Lang, and Matthias Todte, Core drying simulation and validation, International Foundry Research, GIESSEREIFORSCHUNG 64 (2012) No. 1, ISSN 0046-5933, pp 2-5

10-12  H. Vladimir Martínez and Marco F. Valencia (2012). Semisolid Processing of Al/β-SiC Composites by Mechanical Stirring Casting and High Pressure Die Casting, Recent Researches in Metallurgical Engineering – From Extraction to Forming, Dr Mohammad Nusheh (Ed.), ISBN: 978-953-51-0356-1, InTech

07-12     Amir H. G. Isfahani and James M. Brethour, Simulating Thermal Stresses and Cooling Deformations, Die Casting Engineer, March 2012

06-12   Shuisheng Xie, Youfeng He and Xujun Mi, Study on Semi-solid Magnesium Alloys Slurry Preparation and Continuous Roll-casting Process, Magnesium Alloys – Design, Processing and Properties, ISBN: 978-953-307-520-4, InTech.

04-12 J. Spangenberg, N. Roussel, J.H. Hattel, H. Stang, J. Skocek, M.R. Geiker, Flow induced particle migration in fresh concrete: Theoretical frame, numerical simulations and experimental results on model fluids, Cement and Concrete Research, http://dx.doi.org/10.1016/j.cemconres.2012.01.007, February 2012.

01-12   Lee, B., Baek, U., and Han, J., Optimization of Gating System Design for Die Casting of Thin Magnesium Alloy-Based Multi-Cavity LCD Housings, Journal of Materials Engineering and Performance, Springer New York, Issn: 1059-9495, 10.1007/s11665-011-0111-1, Volume 1 / 1992 – Volume 21 / 2012. Available online at Springer Link.

104-11  Fu-Yuan Hsu and Huey Jiuan Lin, Foam Filters Used in Gravity Casting, Metall and Materi Trans B (2011) 42: 1110. doi:10.1007/s11663-011-9548-8.

99-11    Eduardo Trejo, Centrifugal Casting of an Aluminium Alloy, thesis: Doctor of Philosophy, Metallurgy and Materials School of Engineering University of Birmingham, October 2011. Full paper available upon request.

93-11  Olga Kononova, Andrejs Krasnikovs ,Videvuds Lapsa,Jurijs Kalinka and Angelina Galushchak, Internal Structure Formation in High Strength Fiber Concrete during Casting, World Academy of Science, Engineering and Technology 59 2011

76-11  J. Hartmann, A. Trepper, and C. Körner, Aluminum Integral Foams with Near-Microcellular Structure, Advanced Engineering Materials 2011, Volume 13 (2011) No. 11, © Wiley-VCH

71-11  Fu-Yuan Hsu and Yao-Ming Yang Confluence Weld in an Aluminum Gravity Casting, Journal of Materials Processing Technology, Available online 23 November 2011, ISSN 0924-0136, 10.1016/j.jmatprotec.2011.11.006.

65-11     V.A. Chaikin, A.V. Chaikin, I.N.Volnov, A Study of the Process of Late Modification Using Simulation, in Zagotovitelnye Proizvodstva v Mashinostroenii, 10, 2011, 8-12. In Russian.

54-11  Ngadia Taha Niane and Jean-Pierre Michalet, Validation of Foundry Process for Aluminum Parts with FLOW-3D Software, Proceedings of the 2011 International Symposium on Liquid Metal Processing and Casting, 2011.

51-11    A. Reikher and H. Gerber, Calculation of the Die Cast parameters of the Thin Wall Aluminum Cast Part, 2011 Die Casting Congress & Tabletop, Columbus, OH, September 19-21, 2011

50-11   Y. Wang, K. Kabiri-Bamoradian, and R.A. Miller, Runner design optimization based on CFD simulation for a die with multiple cavities, 2011 Die Casting Congress & Tabletop, Columbus, OH, September 19-21, 2011

48-11 A. Karwiński, W. Leśniewski, S. Pysz, P. Wieliczko, The technology of precision casting of titanium alloys by centrifugal process, Archives of Foundry Engineering, ISSN: 1897-3310), Volume 11, Issue 3/2011, 73-80, 2011.

46-11  Daniel Einsiedler, Entwicklung einer Simulationsmethodik zur Simulation von Strömungs- und Trocknungsvorgängen bei Kernfertigungsprozessen mittels CFD (Development of a simulation methodology for simulating flow and drying operations in core production processes using CFD), MSc thesis at Technical University of Aalen in Germany (Hochschule Aalen), 2011.

44-11  Bin Zhang and Craig Shaber, Aluminum Ingot Thermal Stress Development Modeling of the Wagstaff® EpsilonTM Rolling Ingot DC Casting System during the Start-up Phase, Materials Science Forum Vol. 693 (2011) pp 196-207, © 2011 Trans Tech Publications, July, 2011.

43-11 Vu Nguyen, Patrick Rohan, John Grandfield, Alex Levin, Kevin Naidoo, Kurt Oswald, Guillaume Girard, Ben Harker, and Joe Rea, Implementation of CASTfill low-dross pouring system for ingot casting, Materials Science Forum Vol. 693 (2011) pp 227-234, © 2011 Trans Tech Publications, July, 2011.

40-11  A. Starobin, D. Goettsch, M. Walker, D. Burch, Gas Pressure in Aluminum Block Water Jacket Cores, © 2011 American Foundry Society, International Journal of Metalcasting/Summer 2011

37-11 Ferencz Peti, Lucian Grama, Analyze of the Possible Causes of Porosity Type Defects in Aluminum High Pressure Diecast Parts, Scientific Bulletin of the Petru Maior University of Targu Mures, Vol. 8 (XXV) no. 1, 2011, ISSN 1841-9267

31-11  Johannes Hartmann, André Trepper, Carolin Körner, Aluminum Integral Foams with Near-Microcellular Structure, Advanced Engineering Materials, 13: n/a. doi: 10.1002/adem.201100035, June 2011.

27-11  A. Pari, Optimization of HPDC Process using Flow Simulation Case Studies, Die Casting Engineer, July 2011

26-11    A. Reikher, H. Gerber, Calculation of the Die Cast Parameters of the Thin Wall Aluminum Die Casting Part, Die Casting Engineer, July 2011

21-11 Thang Nguyen, Vu Nguyen, Morris Murray, Gary Savage, John Carrig, Modelling Die Filling in Ultra-Thin Aluminium Castings, Materials Science Forum (Volume 690), Light Metals Technology V, pp 107-111, 10.4028/www.scientific.net/MSF.690.107, June 2011.

19-11 Jon Spangenberg, Cem Celal Tutum, Jesper Henri Hattel, Nicolas Roussel, Metter Rica Geiker, Optimization of Casting Process Parameters for Homogeneous Aggregate Distribution in Self-Compacting Concrete: A Feasibility Study, © IEEE Congress on Evolutionary Computation, 2011, New Orleans, USA

16-11  A. Starobin, C.W. Hirt, H. Lang, and M. Todte, Core Drying Simulation and Validations, AFS Proceedings 2011, © American Foundry Society, Presented at the 115th Metalcasting Congress, Schaumburg, Illinois, April 2011.

15-11  J. J. Hernández-Ortega, R. Zamora, J. López, and F. Faura, Numerical Analysis of Air Pressure Effects on the Flow Pattern during the Filling of a Vertical Die Cavity, AIP Conf. Proc., Volume 1353, pp. 1238-1243, The 14th International Esaform Conference on Material Forming: Esaform 2011; doi:10.1063/1.3589686, May 2011. Available online.

10-11 Abbas A. Khalaf and Sumanth Shankar, Favorable Environment for Nondentric Morphology in Controlled Diffusion Solidification, DOI: 10.1007/s11661-011-0641-z, © The Minerals, Metals & Materials Society and ASM International 2011, Metallurgical and Materials Transactions A, March 11, 2011.

08-11 Hai Peng Li, Chun Yong Liang, Li Hui Wang, Hong Shui Wang, Numerical Simulation of Casting Process for Gray Iron Butterfly Valve, Advanced Materials Research, 189-193, 260, February 2011.

04-11  C.W. Hirt, Predicting Core Shooting, Drying and Defect Development, Foundry Management & Technology, January 2011.

76-10  Zhizhong Sun, Henry Hu, Alfred Yu, Numerical Simulation and Experimental Study of Squeeze Casting Magnesium Alloy AM50, Magnesium Technology 2010, 2010 TMS Annual Meeting & ExhibitionFebruary 14-18, 2010, Seattle, WA.

68-10  A. Reikher, H. Gerber, K.M. Pillai, T.-C. Jen, Natural Convection—An Overlooked Phenomenon of the Solidification Process, Die Casting Engineer, January 2010

54-10    Andrea Bernardoni, Andrea Borsi, Stefano Mascetti, Alessandro Incognito and Matteo Corrado, Fonderia Leonardo aveva ragione! L’enorme cavallo dedicato a Francesco Sforza era materialmente realizzabile, A&C – Analisis e Calcolo, Giugno 2010. In  Italian.

48-10  J. J. Hernández-Ortega, R. Zamora, J. Palacios, J. López and F. Faura, An Experimental and Numerical Study of Flow Patterns and Air Entrapment Phenomena During the Filling of a Vertical Die Cavity, J. Manuf. Sci. Eng., October 2010, Volume 132, Issue 5, 05101, doi:10.1115/1.4002535.

47-10  A.V. Chaikin, I.N. Volnov, and V.A. Chaikin, Development of Dispersible Mixed Inoculant Compositions Using the FLOW-3D Program, Liteinoe Proizvodstvo, October, 2010, in Russian.

42-10  H. Lakshmi, M.C. Vinay Kumar, Raghunath, P. Kumar, V. Ramanarayanan, K.S.S. Murthy, P. Dutta, Induction reheating of A356.2 aluminum alloy and thixocasting as automobile component, Transactions of Nonferrous Metals Society of China 20(20101) s961-s967.

41-10  Pamela J. Waterman, Understanding Core-Gas Defects, Desktop Engineering, October 2010. Available online at Desktop Engineering. Also published in the Foundry Trade Journal, November 2010.

39-10  Liu Zheng, Jia Yingying, Mao Pingli, Li Yang, Wang Feng, Wang Hong, Zhou Le, Visualization of Die Casting Magnesium Alloy Steering Bracket, Special Casting & Nonferrous Alloys, ISSN: 1001-2249, CN: 42-1148/TG, 2010-04. In Chinese.

37-10  Morris Murray, Lars Feldager Hansen, and Carl Reinhardt, I Have Defects – Now What, Die Casting Engineer, September 2010

36-10  Stefano Mascetti, Using Flow Analysis Software to Optimize Piston Velocity for an HPDC Process, Die Casting Engineer, September 2010. Also available in Italian: Ottimizzare la velocita del pistone in pressofusione.  A & C, Analisi e Calcolo, Anno XII, n. 42, Gennaio 2011, ISSN 1128-3874.

32-10  Guan Hai Yan, Sheng Dun Zhao, Zheng Hui Sha, Parameters Optimization of Semisolid Diecasting Process for Air-Conditioner’s Triple Valve in HPb59-1 Alloy, Advanced Materials Research (Volumes 129 – 131), Vol. Material and Manufacturing Technology, pp. 936-941, DOI: 10.4028/www.scientific.net/AMR.129-131.936, August 2010.

29-10 Zheng Peng, Xu Jun, Zhang Zhifeng, Bai Yuelong, and Shi Likai, Numerical Simulation of Filling of Rheo-diecasting A357 Aluminum Alloy, Special Casting & Nonferrous Alloys, DOI: CNKI:SUN:TZZZ.0.2010-01-024, 2010.

27-10 For an Aerospace Diecasting, Littler Uses Simulation to Reveal Defects, and Win a New Order, Foundry Management & Technology, July 2010

23-10 Michael R. Barkhudarov, Minimizing Air Entrainment, The Canadian Die Caster, June 2010

15-10 David H. Kirkwood, Michel Suery, Plato Kapranos, Helen V. Atkinson, and Kenneth P. Young, Semi-solid Processing of Alloys, 2010, XII, 172 p. 103 illus., 19 in color., Hardcover ISBN: 978-3-642-00705-7.

09-10  Shannon Wetzel, Fullfilling Da Vinci’s Dream, Modern Casting, April 2010.

08-10 B.I. Semenov, K.M. Kushtarov, Semi-solid Manufacturing of Castings, New Industrial Technologies, Publication of Moscow State Technical University n.a. N.E. Bauman, 2009 (in Russian)

07-10 Carl Reilly, Development Of Quantitative Casting Quality Assessment Criteria Using Process Modelling, thesis: The University of Birmingham, March 2010 (Available upon request)

06-10 A. Pari, Optimization of HPDC Process using Flow Simulation – Case Studies, CastExpo ’10, NADCA, Orlando, Florida, March 2010

05-10 M.C. Carter, S. Palit, and M. Littler, Characterizing Flow Losses Occurring in Air Vents and Ejector Pins in High Pressure Die Castings, CastExpo ’10, NADCA, Orlando, Florida, March 2010

04-10 Pamela Waterman, Simulating Porosity Factors, Foundry Management Technology, March 2010, Article available at Foundry Management Technology

03-10 C. Reilly, M.R. Jolly, N.R. Green, JC Gebelin, Assessment of Casting Filling by Modeling Surface Entrainment Events Using CFD, 2010 TMS Annual Meeting & Exhibition (Jim Evans Honorary Symposium), Seattle, Washington, USA, February 14-18, 2010

02-10 P. Väyrynen, S. Wang, J. Laine and S.Louhenkilpi, Control of Fluid Flow, Heat Transfer and Inclusions in Continuous Casting – CFD and Neural Network Studies, 2010 TMS Annual Meeting & Exhibition (Jim Evans Honorary Symposium), Seattle, Washington, USA, February 14-18, 2010

60-09   Somlak Wannarumon, and Marco Actis Grande, Comparisons of Computer Fluid Dynamic Software Programs applied to Jewelry Investment Casting Process, World Academy of Science, Engineering and Technology 55 2009.

59-09   Marco Actis Grande and Somlak Wannarumon, Numerical Simulation of Investment Casting of Gold Jewelry: Experiments and Validations, World Academy of Science, Engineering and Technology, Vol:3 2009-07-24

56-09  Jozef Kasala, Ondrej Híreš, Rudolf Pernis, Start-up Phase Modeling of Semi Continuous Casting Process of Brass Billets, Metal 2009, 19.-21.5.2009

51-09  In-Ting Hong, Huan-Chien Tung, Chun-Hao Chiu and Hung-Shang Huang, Effect of Casting Parameters on Microstructure and Casting Quality of Si-Al Alloy for Vacuum Sputtering, China Steel Technical Report, No. 22, pp. 33-40, 2009.

42-09  P. Väyrynen, S. Wang, S. Louhenkilpi and L. Holappa, Modeling and Removal of Inclusions in Continuous Casting, Materials Science & Technology 2009 Conference & Exhibition, Pittsburgh, Pennsylvania, USA, October 25-29, 2009

41-09 O.Smirnov, P.Väyrynen, A.Kravchenko and S.Louhenkilpi, Modern Methods of Modeling Fluid Flow and Inclusions Motion in Tundish Bath – General View, Proceedings of Steelsim 2009 – 3rd International Conference on Simulation and Modelling of Metallurgical Processes in Steelmaking, Leoben, Austria, September 8-10, 2009

21-09 A. Pari, Case Studies – Optimization of HPDC Process Using Flow Simulation, Die Casting Engineer, July 2009

20-09 M. Sirvio, M. Wos, Casting directly from a computer model by using advanced simulation software, FLOW-3D Cast, Archives of Foundry Engineering Volume 9, Issue 1/2009, 79-82

19-09 Andrei Starobin, C.W. Hirt, D. Goettsch, A Model for Binder Gas Generation and Transport in Sand Cores and Molds, Modeling of Casting, Welding, and Solidification Processes XII, TMS (The Minerals, Metals & Minerals Society), June 2009

11-09 Michael Barkhudarov, Minimizing Air Entrainment in a Shot Sleeve during Slow-Shot Stage, Die Casting Engineer (The North American Die Casting Association ISSN 0012-253X), May 2009

10-09 A. Reikher, H. Gerber, Application of One-Dimensional Numerical Simulation to Optimize Process Parameters of a Thin-Wall Casting in High Pressure Die Casting, Die Casting Engineer (The North American Die Casting Association ISSN 0012-253X), May 2009

7-09 Andrei Starobin, Simulation of Core Gas Evolution and Flow, presented at the North American Die Casting Association – 113th Metalcasting Congress, April 7-10, 2009, Las Vegas, Nevada, USA

6-09 A.Pari, Optimization of HPDC PROCESS: Case Studies, North American Die Casting Association – 113th Metalcasting Congress, April 7-10, 2009, Las Vegas, Nevada, USA

2-09 C. Reilly, N.R. Green and M.R. Jolly, Oxide Entrainment Structures in Horizontal Running Systems, TMS 2009, San Francisco, California, February 2009

30-08 I.N.Volnov, Computer Modeling of Casting of Pipe Fittings, © 2008, Pipe Fittings, 5 (38), 2008. Russian version

28-08 A.V.Chaikin, I.N.Volnov, V.A.Chaikin, Y.A.Ukhanov, N.R.Petrov, Analysis of the Efficiency of Alloy Modifiers Using Statistics and Modeling, © 2008, Liteyshik Rossii (Russian Foundryman), October, 2008

27-08 P. Scarber, Jr., H. Littleton, Simulating Macro-Porosity in Aluminum Lost Foam Castings, American Foundry Society, © 2008, AFS Lost Foam Conference, Asheville, North Carolina, October, 2008

25-08 FMT Staff, Forecasting Core Gas Pressures with Computer Simulation, Foundry Management and Technology, October 28, 2008 © 2008 Penton Media, Inc. Online article

24-08 Core and Mold Gas Evolution, Foundry Management and Technology, January 24, 2008 (excerpted from the FM&T May 2007 issue) © 2008 Penton Media, Inc.

22-08 Mark Littler, Simulation Eliminates Die Casting Scrap, Modern Casting/September 2008

21-08 X. Chen, D. Penumadu, Permeability Measurement and Numerical Modeling for Refractory Porous Materials, AFS Transactions © 2008 American Foundry Society, CastExpo ’08, Atlanta, Georgia, May 2008

20-08 Rolf Krack, Using Solidification Simulations for Optimising Die Cooling Systems, FTJ July/August 2008

19-08 Mark Littler, Simulation Software Eliminates Die Casting Scrap, ECS Casting Innovations, July/August 2008

13-08 T. Yoshimura, K. Yano, T. Fukui, S. Yamamoto, S. Nishido, M. Watanabe and Y. Nemoto, Optimum Design of Die Casting Plunger Tip Considering Air Entrainment, Proceedings of 10th Asian Foundry Congress (AFC10), Nagoya, Japan, May 2008

08-08 Stephen Instone, Andreas Buchholz and Gerd-Ulrich Gruen, Inclusion Transport Phenomena in Casting Furnaces, Light Metals 2008, TMS (The Minerals, Metals & Materials Society), 2008

07-08 P. Scarber, Jr., H. Littleton, Simulating Macro-Porosity in Aluminum Lost Foam Casting, AFS Transactions 2008 © American Foundry Society, CastExpo ’08, Atlanta, Georgia, May 2008

06-08 A. Reikher, H. Gerber and A. Starobin, Multi-Stage Plunger Deceleration System, CastExpo ’08, NADCA, Atlanta, Georgia, May 2008

05-08 Amol Palekar, Andrei Starobin, Alexander Reikher, Die-casting end-of-fill and drop forge viscometer flow transients examined with a coupled-motion numerical model, 68th World Foundry Congress, Chennai, India, February 2008

03-08 Petri J. Väyrynen, Sami K. Vapalahti and Seppo J. Louhenkilpi, On Validation of Mathematical Fluid Flow Models for Simulation of Tundish Water Models and Industrial Examples, AISTech 2008, May 2008

53-07   A. Kermanpur, Sh. Mahmoudi and A. Hajipour, Three-dimensional Numerical Simulation of Metal Flow and Solidification in the Multi-cavity Casting Moulds of Automotive Components, International Journal of Iron & Steel Society of Iran, Article 2, Volume 4, Issue 1, Summer and Autumn 2007, pages 8-15.

36-07 Duque Mesa A. F., Herrera J., Cruz L.J., Fernández G.P. y Martínez H.V., Caracterización Defectológica de Piezas Fundida por Lost Foam Casting Mediante Simulación Numérica, 8° Congreso Iberoamericano de Ingenieria Mecanica, Cusco, Peru, 23 al 25 de Octubre de 2007 (in Spanish)

27-07 A.Y. Korotchenko, A.M. Zarubin, I.A.Korotchenko, Modeling of High Pressure Die Casting Filling, Russian Foundryman, December 2007, pp 15-19. (in Russian)

26-07 I.N. Volnov, Modeling of Casting Processes with Variable Geometry, Russian Foundryman, November 2007, pp 27-30. (in Russian)

16-07 P. Väyrynen, S. Vapalahti, S. Louhenkilpi, L. Chatburn, M. Clark, T. Wagner, Tundish Flow Model Tuning and Validation – Steady State and Transient Casting Situations, STEELSIM 2007, Graz/Seggau, Austria, September 12-14 2007

11-07 Marco Actis Grande, Computer Simulation of the Investment Casting Process – Widening of the Filling Step, Santa Fe Symposium on Jewelry Manufacturing Technology, May 2007

09-07 Alexandre Reikher and Michael Barkhudarov, Casting: An Analytical Approach, Springer, 1st edition, August 2007, Hardcover ISBN: 978-1-84628-849-4. U.S. Order FormEurope Order Form.

07-07 I.N. Volnov, Casting Modeling Systems – Current State, Problems and Perspectives, (in Russian), Liteyshik Rossii (Russian Foundryman), June 2007

05-07 A.N. Turchin, D.G. Eskin, and L. Katgerman, Solidification under Forced-Flow Conditions in a Shallow Cavity, DOI: 10.1007/s1161-007-9183-9, © The Minerals, Metals & Materials Society and ASM International 2007

04-07 A.N. Turchin, M. Zuijderwijk, J. Pool, D.G. Eskin, and L. Katgerman, Feathery grain growth during solidification under forced flow conditions, © Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved. DOI: 10.1016/j.actamat.2007.02.030, April 2007

03-07 S. Kuyucak, Sponsored Research – Clean Steel Casting Production—Evaluation of Laboratory Castings, Transactions of the American Foundry Society, Volume 115, 111th Metalcasting Congress, May 2007

02-07 Fu-Yuan Hsu, Mark R. Jolly and John Campbell, The Design of L-Shaped Runners for Gravity Casting, Shape Casting: 2nd International Symposium, Edited by Paul N. Crepeau, Murat Tiryakioðlu and John Campbell, TMS (The Minerals, Metals & Materials Society), Orlando, FL, Feb 2007

30-06 X.J. Liu, S.H. Bhavnani, R.A. Overfelt, Simulation of EPS foam decomposition in the lost foam casting process, Journal of Materials Processing Technology 182 (2007) 333–342, © 2006 Elsevier B.V. All rights reserved.

25-06 Michael Barkhudarov and Gengsheng Wei, Modeling Casting on the Move, Modern Casting, August 2006; Modeling of Casting Processes with Variable Geometry, Russian Foundryman, December 2007, pp 10-15. (in Russian)

24-06 P. Scarber, Jr. and C.E. Bates, Simulation of Core Gas Production During Mold Fill, © 2006 American Foundry Society

7-06 M.Y.Smirnov, Y.V.Golenkov, Manufacturing of Cast Iron Bath Tubs Castings using Vacuum-Process in Russia, Russia’s Foundryman, July 2006. In Russian.

6-06 M. Barkhudarov, and G. Wei, Modeling of the Coupled Motion of Rigid Bodies in Liquid Metal, Modeling of Casting, Welding and Advanced Solidification Processes – XI, May 28 – June 2, 2006, Opio, France, eds. Ch.-A. Gandin and M. Bellet, pp 71-78, 2006.

2-06 J.-C. Gebelin, M.R. Jolly and F.-Y. Hsu, ‘Designing-in’ Controlled Filling Using Numerical Simulation for Gravity Sand Casting of Aluminium Alloys, Int. J. Cast Met. Res., 2006, Vol.19 No.1

1-06 Michael Barkhudarov, Using Simulation to Control Microporosity Reduces Die Iterations, Die Casting Engineer, January 2006, pp. 52-54

30-05 H. Xue, K. Kabiri-Bamoradian, R.A. Miller, Modeling Dynamic Cavity Pressure and Impact Spike in Die Casting, Cast Expo ’05, April 16-19, 2005

22-05 Blas Melissari & Stavros A. Argyropoulous, Measurement of Magnitude and Direction of Velocity in High-Temperature Liquid Metals; Part I, Mathematical Modeling, Metallurgical and Materials Transactions B, Volume 36B, October 2005, pp. 691-700

21-05 M.R. Jolly, State of the Art Review of Use of Modeling Software for Casting, TMS Annual Meeting, Shape Casting: The John Campbell Symposium, Eds, M. Tiryakioglu & P.N Crepeau, TMS, Warrendale, PA, ISBN 0-87339-583-2, Feb 2005, pp 337-346

20-05 J-C Gebelin, M.R. Jolly & F-Y Hsu, ‘Designing-in’ Controlled Filling Using Numerical Simulation for Gravity Sand Casting of Aluminium Alloys, TMS Annual Meeting, Shape Casting: The John Campbell Symposium, Eds, M. Tiryakioglu & P.N Crepeau, TMS, Warrendale, PA, ISBN 0-87339-583-2, Feb 2005, pp 355-364

19-05 F-Y Hsu, M.R. Jolly & J Campbell, Vortex Gate Design for Gravity Castings, TMS Annual Meeting, Shape Casting: The John Campbell Symposium, Eds, M. Tiryakioglu & P.N Crepeau, TMS, Warrendale, PA, ISBN 0-87339-583-2, Feb 2005, pp 73-82

18-05 M.R. Jolly, Modelling the Investment Casting Process: Problems and Successes, Japanese Foundry Society, JFS, Tokyo, Sept. 2005

13-05 Xiaogang Yang, Xiaobing Huang, Xiaojun Dai, John Campbell and Joe Tatler, Numerical Modelling of the Entrainment of Oxide Film Defects in Filling of Aluminium Alloy Castings, International Journal of Cast Metals Research, 17 (6), 2004, 321-331

10-05 Carlos Evaristo Esparza, Martha P. Guerro-Mata, Roger Z. Ríos-Mercado, Optimal Design of Gating Systems by Gradient Search Methods, Computational Materials Science, October 2005

6-05 Birgit Hummler-Schaufler, Fritz Hirning, Jurgen Schaufler, A World First for Hatz Diesel and Schaufler Tooling, Die Casting Engineer, May 2005, pp. 18-21

4-05 Rolf Krack, The W35 Topic—A World First, Die Casting World, March 2005, pp. 16-17

3-05 Joerg Frei, Casting Simulations Speed Up Development, Die Casting World, March 2005, p. 14

2-05 David Goettsch and Michael Barkhudarov, Analysis and Optimization of the Transient Stage of Stopper-Rod Pour, Shape Casting: The John Campbell Symposium, The Minerals, Metals & Materials Society, 2005

36-04  Ik Min Park, Il Dong Choi, Yong Ho Park, Development of Light-Weight Al Scroll Compressor for Car Air Conditioner, Materials Science Forum, Designing, Processing and Properties of Advanced Engineering Materials, 449-452, 149, March 2004.

32-04 D.H. Kirkwood and P.J Ward, Numerical Modelling of Semi-Solid Flow under Processing Conditions, steel research int. 75 (2004), No. 8/9

30-04 Haijing Mao, A Numerical Study of Externally Solidified Products in the Cold Chamber Die Casting Process, thesis: The Ohio State University, 2004 (Available upon request)

28-04 Z. Cao, Z. Yang, and X.L. Chen, Three-Dimensional Simulation of Transient GMA Weld Pool with Free Surface, Supplement to the Welding Journal, June 2004.

23-04 State of the Art Use of Computational Modelling in the Foundry Industry, 3rd International Conference Computational Modelling of Materials III, Sicily, Italy, June 2004, Advances in Science and Technology,  Eds P. Vincenzini & A Lami, Techna Group Srl, Italy, ISBN: 88-86538-46-4, Part B, pp 479-490

22-04 Jerry Fireman, Computer Simulation Helps Reduce Scrap, Die Casting Engineer, May 2004, pp. 46-49

21-04 Joerg Frei, Simulation—A Safe and Quick Way to Good Components, Aluminium World, Volume 3, Issue 2, pp. 42-43

20-04 J.-C. Gebelin, M.R. Jolly, A. M. Cendrowicz, J. Cirre and S. Blackburn, Simulation of Die Filling for the Wax Injection Process – Part II Numerical Simulation, Metallurgical and Materials Transactions, Volume 35B, August 2004

14-04 Sayavur I. Bakhtiyarov, Charles H. Sherwin, and Ruel A. Overfelt, Hot Distortion Studies In Phenolic Urethane Cold Box System, American Foundry Society, 108th Casting Congress, June 12-15, 2004, Rosemont, IL, USA

13-04 Sayavur I. Bakhtiyarov and Ruel A. Overfelt, First V-Process Casting of Magnesium, American Foundry Society, 108th Casting Congress, June 12-15, 2004, Rosemont, IL, USA

5-04 C. Schlumpberger & B. Hummler-Schaufler, Produktentwicklung auf hohem Niveau (Product Development on a High Level), Druckguss Praxis, January 2004, pp 39-42 (in German).

3-04 Charles Bates, Dealing with Defects, Foundry Management and Technology, February 2004, pp 23-25

1-04 Laihua Wang, Thang Nguyen, Gary Savage and Cameron Davidson, Thermal and Flow Modeling of Ladling and Injection in High Pressure Die Casting Process, International Journal of Cast Metals Research, vol. 16 No 4 2003, pp 409-417

2-03 J-C Gebelin, AM Cendrowicz, MR Jolly, Modeling of the Wax Injection Process for the Investment Casting Process – Prediction of Defects, presented at the Third International Conference on Computational Fluid Dynamics in the Minerals and Process Industries, December 10-12, 2003, Melbourne, Australia, pp. 415-420

29-03 C. W. Hirt, Modeling Shrinkage Induced Micro-porosity, Flow Science Technical Note (FSI-03-TN66)

28-03 Thixoforming at the University of Sheffield, Diecasting World, September 2003, pp 11-12

26-03 William Walkington, Gas Porosity-A Guide to Correcting the Problems, NADCA Publication: 516

22-03 G F Yao, C W Hirt, and M Barkhudarov, Development of a Numerical Approach for Simulation of Sand Blowing and Core Formation, in Modeling of Casting, Welding, and Advanced Solidification Process-X”, Ed. By Stefanescu et al pp. 633-639, 2003

21-03 E F Brush Jr, S P Midson, W G Walkington, D T Peters, J G Cowie, Porosity Control in Copper Rotor Die Castings, NADCA Indianapolis Convention Center, Indianapolis, IN September 15-18, 2003, T03-046

12-03 J-C Gebelin & M.R. Jolly, Modeling Filters in Light Alloy Casting Processes,  Trans AFS, 2002, 110, pp. 109-120

11-03 M.R. Jolly, Casting Simulation – How Well Do Reality and Virtual Casting Match – A State of the Art Review, Intl. J. Cast Metals Research, 2002, 14, pp. 303-313

10-03 Gebelin., J-C and Jolly, M.R., Modeling of the Investment Casting Process, Journal of  Materials Processing Tech., Vol. 135/2-3, pp. 291 – 300

9-03 Cox, M, Harding, R.A. and Campbell, J., Optimised Running System Design for Bottom Filled Aluminium Alloy 2L99 Investment Castings, J. Mat. Sci. Tech., May 2003, Vol. 19, pp. 613-625

8-03 Von Alexander Schrey and Regina Reek, Numerische Simulation der Kernherstellung, (Numerical Simulation of Core Blowing), Giesserei, June 2003, pp. 64-68 (in German)

7-03 J. Zuidema Jr., L Katgerman, Cyclone separation of particles in aluminum DC Casting, Proceedings from the Tenth International Conference on Modeling of Casting, Welding and Advanced Solidification Processes, Destin, FL, May 2003, pp. 607-614

6-03 Jean-Christophe Gebelin and Mark Jolly, Numerical Modeling of Metal Flow Through Filters, Proceedings from the Tenth International Conference on Modeling of Casting, Welding and Advanced Solidification Processes, Destin, FL, May 2003, pp. 431-438

5-03 N.W. Lai, W.D. Griffiths and J. Campbell, Modelling of the Potential for Oxide Film Entrainment in Light Metal Alloy Castings, Proceedings from the Tenth International Conference on Modeling of Casting, Welding and Advanced Solidification Processes, Destin, FL, May 2003, pp. 415-422

21-02 Boris Lukezic, Case History: Process Modeling Solves Die Design Problems, Modern Casting, February 2003, P 59

20-02 C.W. Hirt and M.R. Barkhudarov, Predicting Defects in Lost Foam Castings, Modern Casting, December 2002, pp 31-33

19-02 Mark Jolly, Mike Cox, Ric Harding, Bill Griffiths and John Campbell, Quiescent Filling Applied to Investment Castings, Modern Casting, December 2002 pp. 36-38

18-02 Simulation Helps Overcome Challenges of Thin Wall Magnesium Diecasting, Foundry Management and Technology, October 2002, pp 13-15

17-02 G Messmer, Simulation of a Thixoforging Process of Aluminum Alloys with FLOW-3D, Institute for Metal Forming Technology, University of Stuttgart

16-02 Barkhudarov, Michael, Computer Simulation of Lost Foam Process, Casting Simulation Background and Examples from Europe and the USA, World Foundrymen Organization, 2002, pp 319-324

15-02 Barkhudarov, Michael, Computer Simulation of Inclusion Tracking, Casting Simulation Background and Examples from Europe and the USA, World Foundrymen Organization, 2002, pp 341-346

14-02 Barkhudarov, Michael, Advanced Simulation of the Flow and Heat Transfer of an Alternator Housing, Casting Simulation Background and Examples from Europe and the USA, World Foundrymen Organization, 2002, pp 219-228

8-02 Sayavur I. Bakhtiyarov, and Ruel A. Overfelt, Experimental and Numerical Study of Bonded Sand-Air Two-Phase Flow in PUA Process, Auburn University, 2002 American Foundry Society, AFS Transactions 02-091, Kansas City, MO

7-02 A Habibollah Zadeh, and J Campbell, Metal Flow Through a Filter System, University of Birmingham, 2002 American Foundry Society, AFS Transactions 02-020, Kansas City, MO

6-02 Phil Ward, and Helen Atkinson, Final Report for EPSRC Project: Modeling of Thixotropic Flow of Metal Alloys into a Die, GR/M17334/01, March 2002, University of Sheffield

5-02 S. I. Bakhtiyarov and R. A. Overfelt, Numerical and Experimental Study of Aluminum Casting in Vacuum-sealed Step Molding, Auburn University, 2002 American Foundry Society, AFS Transactions 02-050, Kansas City, MO

4-02 J. C. Gebelin and M. R. Jolly, Modelling Filters in Light Alloy Casting Processes, University of Birmingham, 2002 American Foundry Society AFS Transactions 02-079, Kansas City, MO

3-02 Mark Jolly, Mike Cox, Jean-Christophe Gebelin, Sam Jones, and Alex Cendrowicz, Fundamentals of Investment Casting (FOCAST), Modelling the Investment Casting Process, Some preliminary results from the UK Research Programme, IRC in Materials, University of Birmingham, UK, AFS2001

49-01   Hua Bai and Brian G. Thomas, Bubble formation during horizontal gas injection into downward-flowing liquid, Metallurgical and Materials Transactions B, Vol. 32, No. 6, pp. 1143-1159, 2001. doi.org/10.1007/s11663-001-0102-y

45-01 Jan Zuidema; Laurens Katgerman; Ivo J. Opstelten;Jan M. Rabenberg, Secondary Cooling in DC Casting: Modelling and Experimental Results, TMS 2001, New Orleans, Louisianna, February 11-15, 2001

43-01 James Andrew Yurko, Fluid Flow Behavior of Semi-Solid Aluminum at High Shear Rates,Ph.D. thesis; Massachusetts Institute of Technology, June 2001. Abstract only; full thesis available at http://dspace.mit.edu/handle/1721.1/8451 (for a fee).

33-01 Juang, S.H., CAE Application on Design of Die Casting Dies, 2001 Conference on CAE Technology and Application, Hsin-Chu, Taiwan, November 2001, (article in Chinese with English-language abstract)

32-01 Juang, S.H. and C. M. Wang, Effect of Feeding Geometry on Flow Characteristics of Magnesium Die Casting by Numerical Analysis, The Preceedings of 6th FADMA Conference, Taipei, Taiwan, July 2001, Chinese language with English abstract

26-01 C. W. Hirt., Predicting Defects in Lost Foam Castings, December 13, 2001

21-01 P. Scarber Jr., Using Liquid Free Surface Areas as a Predictor of Reoxidation Tendency in Metal Alloy Castings, presented at the Steel Founders’ Society of American, Technical and Operating Conference, October 2001

20-01 P. Scarber Jr., J. Griffin, and C. E. Bates, The Effect of Gating and Pouring Practice on Reoxidation of Steel Castings, presented at the Steel Founders’ Society of American, Technical and Operating Conference, October 2001

19-01 L. Wang, T. Nguyen, M. Murray, Simulation of Flow Pattern and Temperature Profile in the Shot Sleeve of a High Pressure Die Casting Process, CSIRO Manufacturing Science and Technology, Melbourne, Victoria, Australia, Presented by North American Die Casting Association, Oct 29-Nov 1, 2001, Cincinnati, To1-014

18-01 Rajiv Shivpuri, Venkatesh Sankararaman, Kaustubh Kulkarni, An Approach at Optimizing the Ingate Design for Reducing Filling and Shrinkage Defects, The Ohio State University, Columbus, OH, Presented by North American Die Casting Association, Oct 29-Nov 1, 2001, Cincinnati, TO1-052

5-01 Michael Barkhudarov, Simulation Helps Overcome Challenges of Thin Wall Magnesium Diecasting, Diecasting World, March 2001, pp. 5-6

2-01 J. Grindling, Customized CFD Codes to Simulate Casting of Thermosets in Full 3D, Electrical Manufacturing and Coil Winding 2000 Conference, October 31-November 2, 20

20-00 Richard Schuhmann, John Carrig, Thang Nguyen, Arne Dahle, Comparison of Water Analogue Modelling and Numerical Simulation Using Real-Time X-Ray Flow Data in Gravity Die Casting, Australian Die Casting Association Die Casting 2000 Conference, September 3-6, 2000, Melbourne, Victoria, Australia

15-00 M. Sirvio, Vainola, J. Vartianinen, M. Vuorinen, J. Orkas, and S. Devenyi, Fluid Flow Analysis for Designing Gating of Aluminum Castings, Proc. NADCA Conf., Rosemont, IL, Nov 6-8, 1999

14-00 X. Yang, M. Jolly, and J. Campbell, Reduction of Surface Turbulence during Filling of Sand Castings Using a Vortex-flow Runner, Conference for Modeling of Casting, Welding, and Advanced Solidification Processes IX, Aachen, Germany, August 2000

13-00 H. S. H. Lo and J. Campbell, The Modeling of Ceramic Foam Filters, Conference for Modeling of Casting, Welding, and Advanced Solidification Processes IX, Aachen, Germany, August 2000

12-00 M. R. Jolly, H. S. H. Lo, M. Turan and J. Campbell, Use of Simulation Tools in the Practical Development of a Method for Manufacture of Cast Iron Camshafts,” Conference for Modeling of Casting, Welding, and Advanced Solidification Processes IX, Aachen, Germany, August, 2000

14-99 J Koke, and M Modigell, Time-Dependent Rheological Properties of Semi-solid Metal Alloys, Institute of Chemical Engineering, Aachen University of Technology, Mechanics of Time-Dependent Materials 3: 15-30, 1999

12-99 Grun, Gerd-Ulrich, Schneider, Wolfgang, Ray, Steven, Marthinusen, Jan-Olaf, Recent Improvements in Ceramic Foam Filter Design by Coupled Heat and Fluid Flow Modeling, Proc TMS Annual Meeting, 1999, pp. 1041-1047

10-99 Bongcheol Park and Jerald R. Brevick, Computer Flow Modeling of Cavity Pre-fill Effects in High Pressure Die Casting, NADCA Proceedings, Cleveland T99-011, November, 1999

8-99 Brad Guthrie, Simulation Reduces Aluminum Die Casting Cost by Reducing Volume, Die Casting Engineer Magazine, September/October 1999, pp. 78-81

7-99 Fred L. Church, Virtual Reality Predicts Cast Metal Flow, Modern Metals, September, 1999, pp. 67F-J

19-98 Grun, Gerd-Ulrich, & Schneider, Wolfgang, Numerical Modeling of Fluid Flow Phenomena in the Launder-integrated Tool Within Casting Unit Development, Proc TMS Annual Meeting, 1998, pp. 1175-1182

18-98 X. Yang & J. Campbell, Liquid Metal Flow in a Pouring Basin, Int. J. Cast Metals Res, 1998, 10, pp. 239-253

15-98 R. Van Tol, Mould Filling of Horizontal Thin-Wall Castings, Delft University Press, The Netherlands, 1998

14-98 J. Daughtery and K. A. Williams, Thermal Modeling of Mold Material Candidates for Copper Pressure Die Casting of the Induction Motor Rotor Structure, Proc. Int’l Workshop on Permanent Mold Casting of Copper-Based Alloys, Ottawa, Ontario, Canada, Oct. 15-16, 1998

10-98 C. W. Hirt, and M.R. Barkhudarov, Lost Foam Casting Simulation with Defect Prediction, Flow Science Inc, presented at Modeling of Casting, Welding and Advanced Solidification Processes VIII Conference, June 7-12, 1998, Catamaran Hotel, San Diego, California

9-98 M. R. Barkhudarov and C. W. Hirt, Tracking Defects, Flow Science Inc, presented at the 1st International Aluminum Casting Technology Symposium, 12-14 October 1998, Rosemont, IL

5-98 J. Righi, Computer Simulation Helps Eliminate Porosity, Die Casting Management Magazine, pp. 36-38, January 1998

3-98 P. Kapranos, M. R. Barkhudarov, D. H. Kirkwood, Modeling of Structural Breakdown during Rapid Compression of Semi-Solid Alloy Slugs, Dept. Engineering Materials, The University of Sheffield, Sheffield S1 3JD, U.K. and Flow Science Inc, USA, Presented at the 5th International Conference Semi-Solid Processing of Alloys and Composites, Colorado School of Mines, Golden, CO, 23-25 June 1998

1-98 U. Jerichow, T. Altan, and P. R. Sahm, Semi Solid Metal Forming of Aluminum Alloys-The Effect of Process Variables Upon Material Flow, Cavity Fill and Mechanical Properties, The Ohio State University, Columbus, OH, published in Die Casting Engineer, p. 26, Jan/Feb 1998

8-97 Michael Barkhudarov, High Pressure Die Casting Simulation Using FLOW-3D, Die Casting Engineer, 1997

15-97 M. R. Barkhudarov, Advanced Simulation of the Flow and Heat Transfer Process in Simultaneous Engineering, Flow Science report, presented at the Casting 1997 – International ADI and Simulation Conference, Helsinki, Finland, May 28-30, 1997

14-97 M. Ranganathan and R. Shivpuri, Reducing Scrap and Increasing Die Life in Low Pressure Die Casting through Flow Simulation and Accelerated Testing, Dept. Welding and Systems Engineering, Ohio State University, Columbus, OH, presented at 19th International Die Casting Congress & Exposition, November 3-6, 1997

13-97 J. Koke, Modellierung und Simulation der Fließeigenschaften teilerstarrter Metallegierungen, Livt Information, Institut für Verfahrenstechnik, RWTH Aachen, October 1997

10-97 J. P. Greene and J. O. Wilkes, Numerical Analysis of Injection Molding of Glass Fiber Reinforced Thermoplastics – Part 2 Fiber Orientation, Body-in-White Center, General Motors Corp. and Dept. Chemical Engineering, University of Michigan, Polymer Engineering and Science, Vol. 37, No. 6, June 1997

9-97 J. P. Greene and J. O. Wilkes, Numerical Analysis of Injection Molding of Glass Fiber Reinforced Thermoplastics. Part 1 – Injection Pressures and Flow, Manufacturing Center, General Motors Corp. and Dept. Chemical Engineering, University of Michigan, Polymer Engineering and Science, Vol. 37, No. 3, March 1997

8-97 H. Grazzini and D. Nesa, Thermophysical Properties, Casting Simulation and Experiments for a Stainless Steel, AT Systemes (Renault) report, presented at the Solidification Processing ’97 Conference, July 7-10, 1997, Sheffield, U.K.

7-97 R. Van Tol, L. Katgerman and H. E. A. Van den Akker, Horizontal Mould Filling of a Thin Wall Aluminum Casting, Laboratory of Materials report, Delft University, presented at the Solidification Processing ’97 Conference, July 7-10, 1997, Sheffield, U.K.

6-97 M. R. Barkhudarov, Is Fluid Flow Important for Predicting Solidification, Flow Science report, presented at the Solidification Processing ’97 Conference, July 7-10, 1997, Sheffield, U.K.

22-96 Grun, Gerd-Ulrich & Schneider, Wolfgang, 3-D Modeling of the Start-up Phase of DC Casting of Sheet Ingots, Proc TMS Annual Meeting, 1996, pp. 971-981

9-96 M. R. Barkhudarov and C. W. Hirt, Thixotropic Flow Effects under Conditions of Strong Shear, Flow Science report FSI96-00-2, to be presented at the “Materials Week ’96” TMS Conference, Cincinnati, OH, 7-10 October 1996

4-96 C. W. Hirt, A Computational Model for the Lost Foam Process, Flow Science final report, February 1996 (FSI-96-57-R2)

3-96 M. R. Barkhudarov, C. L. Bronisz, C. W. Hirt, Three-Dimensional Thixotropic Flow Model, Flow Science report, FSI-96-00-1, published in the proceedings of (pp. 110- 114) and presented at the 4th International Conference on Semi-Solid Processing of Alloys and Composites, The University of Sheffield, 19-21 June 1996

1-96 M. R. Barkhudarov, J. Beech, K. Chang, and S. B. Chin, Numerical Simulation of Metal/Mould Interfacial Heat Transfer in Casting, Dept. Mech. & Process Engineering, Dept. Engineering Materials, University of Sheffield and Flow Science Inc, 9th Int. Symposium on Transport Phenomena in Thermal-Fluid Engineering, June 25-28, 1996, Singapore

11-95 Barkhudarov, M. R., Hirt, C.W., Casting Simulation Mold Filling and Solidification-Benchmark Calculations Using FLOW-3D, Modeling of Casting, Welding, and Advanced Solidification Processes VII, pp 935-946

10-95 Grun, Gerd-Ulrich, & Schneider, Wolfgang, Optimal Design of a Distribution Pan for Level Pour Casting, Proc TMS Annual Meeting, 1995, pp. 1061-1070

9-95 E. Masuda, I. Itoh, K. Haraguchi, Application of Mold Filling Simulation to Die Casting Processes, Honda Engineering Co., Ltd., Tochigi, Japan, presented at the Modelling of Casting, Welding and Advanced Solidification Processes VII, The Minerals, Metals & Materials Society, 1995

6-95 K. Venkatesan, Experimental and Numerical Investigation of the Effect of Process Parameters on the Erosive Wear of Die Casting Dies, presented for Ph.D. degree at Ohio State University, 1995

5-95 J. Righi, A. F. LaCamera, S. A. Jones, W. G. Truckner, T. N. Rouns, Integration of Experience and Simulation Based Understanding in the Die Design Process, Alcoa Technical Center, Alcoa Center, PA 15069, presented by the North American Die Casting Association, 1995

2-95 K. Venkatesan and R. Shivpuri, Numerical Simulation and Comparison with Water Modeling Studies of the Inertia Dominated Cavity Filling in Die Casting, NUMIFORM, 1995

1-95 K. Venkatesan and R. Shivpuri, Numerical Investigation of the Effect of Gate Velocity and Gate Size on the Quality of Die Casting Parts, NAMRC, 1995.

15-94 D. Liang, Y. Bayraktar, S. A. Moir, M. Barkhudarov, and H. Jones, Primary Silicon Segregation During Isothermal Holding of Hypereutectic AI-18.3%Si Alloy in the Freezing Range, Dept. of Engr. Materials, U. of Sheffield, Metals and Materials, February 1994

13-94 Deniece Korzekwa and Paul Dunn, A Combined Experimental and Modeling Approach to Uranium Casting, Materials Division, Los Alamos National Laboratory, presented at the Symposium on Liquid Metal Processing and Casting, El Dorado Hotel, Santa Fe, New Mexico, 1994

12-94 R. van Tol, H. E. A. van den Akker and L. Katgerman, CFD Study of the Mould Filling of a Horizontal Thin Wall Aluminum Casting, Delft University of Technology, Delft, The Netherlands, HTD-Vol. 284/AMD-Vol. 182, Transport Phenomena in Solidification, ASME 1994

11-94 M. R. Barkhudarov and K. A. Williams, Simulation of ‘Surface Turbulence’ Fluid Phenomena During the Mold Filling Phase of Gravity Castings, Flow Science Technical Note #41, November 1994 (FSI-94-TN41)

10-94 M. R. Barkhudarov and S. B. Chin, Stability of a Numerical Algorithm for Gas Bubble Modelling, University of Sheffield, Sheffield, U.K., International Journal for Numerical Methods in Fluids, Vol. 19, 415-437 (1994)

16-93 K. Venkatesan and R. Shivpuri, Numerical Simulation of Die Cavity Filling in Die Castings and an Evaluation of Process Parameters on Die Wear, Dept. of Industrial Systems Engineering, Presented by: N.A. Die Casting Association, Cleveland, Ohio, October 18-21, 1993

15-93 K. Venkatesen and R. Shivpuri, Numerical Modeling of Filling and Solidification for Improved Quality of Die Casting: A Literature Survey (Chapters II and III), Engineering Research Center for Net Shape Manufacturing, Report C-93-07, August 1993, Ohio State University

1-93 P-E Persson, Computer Simulation of the Solidification of a Hub Carrier for the Volvo 800 Series, AB Volvo Technological Development, Metals Laboratory, Technical Report No. LM 500014E, Jan. 1993

13-92 D. R. Korzekwa, M. A. K. Lewis, Experimentation and Simulation of Gravity Fed Lead Castings, in proceedings of a TMS Symposium on Concurrent Engineering Approach to Materials Processing, S. N. Dwivedi, A. J. Paul and F. R. Dax, eds., TMS-AIME Warrendale, p. 155 (1992)

12-92 M. A. K. Lewis, Near-Net-Shaiconpe Casting Simulation and Experimentation, MST 1992 Review, Los Alamos National Laboratory

2-92 M. R. Barkhudarov, H. You, J. Beech, S. B. Chin, D. H. Kirkwood, Validation and Development of FLOW-3D for Casting, School of Materials, University of Sheffield, Sheffield, UK, presented at the TMS/AIME Annual Meeting, San Diego, CA, March 3, 1992

1-92 D. R. Korzekwa and L. A. Jacobson, Los Alamos National Laboratory and C.W. Hirt, Flow Science Inc, Modeling Planar Flow Casting with FLOW-3D, presented at the TMS/AIME Annual Meeting, San Diego, CA, March 3, 1992

12-91 R. Shivpuri, M. Kuthirakulathu, and M. Mittal, Nonisothermal 3-D Finite Difference Simulation of Cavity Filling during the Die Casting Process, Dept. Industrial and Systems Engineering, Ohio State University, presented at the 1991 Winter Annual ASME Meeting, Atlanta, GA, Dec. 1-6, 1991

3-91 C. W. Hirt, FLOW-3D Study of the Importance of Fluid Momentum in Mold Filling, presented at the 18th Annual Automotive Materials Symposium, Michigan State University, Lansing, MI, May 1-2, 1991 (FSI-91-00-2)

11-90 N. Saluja, O.J. Ilegbusi, and J. Szekely, On the Calculation of the Electromagnetic Force Field in the Circular Stirring of Metallic Melts, accepted in J. Appl. Physics, 1990

10-90 N. Saluja, O. J. Ilegbusi, and J. Szekely, On the Calculation of the Electromagnetic Force Field in the Circular Stirring of Metallic Molds in Continuous Castings, presented at the 6th Iron and Steel Congress of the Iron and Steel Institute of Japan, Nagoya, Japan, October 1990

9-90 N. Saluja, O. J. Ilegbusi, and J. Szekely, Fluid Flow in Phenomena in the Electromagnetic Stirring of Continuous Casting Systems, Part I. The Behavior of a Cylindrically Shaped, Laboratory Scale Installation, accepted for publication in Steel Research, 1990

8-89 C. W. Hirt, Gravity-Fed Casting, Flow Science Technical Note #20, July 1989 (FSI-89-TN20)

6-89 E. W. M. Hansen and F. Syvertsen, Numerical Simulation of Flow Behaviour in Moldfilling for Casting Analysis, SINTEF-Foundation for Scientific and Industrial Research at the Norwegian Institute of Technology, Trondheim, Norway, Report No. STS20 A89001, June 1989

1-88 C. W. Hirt and R. P. Harper, Modeling Tests for Casting Processes, Flow Science report, Jan. 1988 (FSI-88-38-01)

2-87 C. W. Hirt, Addition of a Solidification/Melting Model to FLOW-3D, Flow Science report, April 1987 (FSI-87-33-1)

FLOW-3D What’s New Ver.12.0

FLOW-3D v12.0은 그래픽 사용자 인터페이스 (GUI)의 설계 및 기능에서 매우 큰 변화를 이룬 제품으로 모델 설정을 단순화하고 사용자 워크 플로를 향상시킵니다. 최첨단 Immersed Boundary Method(침수경계 방법)은 FLOW-3D v12.0 솔루션의 정확성을 높여줍니다. 다른 주요 기능으로는 슬러지 침강 모델, 2-Fluid 2-Temperature 모델 및 Steady State Accelerator가 있으며,이를 통해 사용자는 자유 표면 흐름을 더욱 빠르게 모델링 할 수 있습니다.

Physical and Numerical Model

Immersed boundary method

힘과 에너지 손실에 대한 정확한 예측은 고체 주위의 흐름과 관련된 많은 엔지니어링 문제를 모델링하는 데 중요합니다. 새 릴리스 FLOW-3 Dv1.2.0에는 이러한 문제점 해결을 위해 설계된 새로운 고스트 셀 기반 Immersed Boundary Method (IBM)가 있습니다. IBM은 내 외부 흐름 해석을 위해, 벽 근처에서 보다 정확한 해를 제공하여 드래그 앤 리프트 힘의 계산을 향상시킵니다.힘과 에너지 손실의 정확한 예측은 고체 주위의 흐름을 포함하는 많은 공학적 문제를 모델링 하는데 중요합니다.

Two-field temperature for the two-fluid model

2 유체 열전달 모델은 각 유체에 대한 에너지 전달 방정식을 분리하기 위해 확장되었습니다. 각 유체는 이제 자체 온도 변수를 가지므로 인터페이스 근처의 열 및 물질 전달 솔루션의 정확도가 향상됩니다. 인터페이스에서의 열전달은 이제 시간의 표 함수가 될 수 있는 사용자 정의 열전달 계수에 의해 제어됩니다.

블로그 보기

Sludge settling model

새로운 슬러지 정착 모델은 수처리 애플리케이션에 부가되어 사용자들이 수 처리 탱크와 클래리퍼의 고형 폐기물 역학을 모델링 할 수 있게 해 줍니다. 침전 속도가 분산상의 액적 크기의 함수 인 드리프트-플럭스 모델과 달리, 침전 속도는 슬러지 농도의 함수이며 기능 및 표 형식으로 입력 할 수 있습니다.

개발노트 읽기

Steady-state accelerator for free surface flows

이름에서 알 수 있듯이 정상 상태 가속기는 정상 상태 솔루션에 대한 접근을 빠르게합니다.
이것은 작은 진폭 중력과 모세관 표면파를 감쇠시킴으로써 달성되며 자유 표면 흐름에만 적용 할 수 있습니다.

개발노트 읽기

Void particles

Void particles 가 기포 및 상 변화 모델에 추가되었습니다. Void particles는 붕괴 된 Void 영역을 나타내며, 항력 및 압력을 통해 유체와 상호 작용하는 작은 기포로 작용합니다. 주변 유체 압력에 따라 크기가 변하고 시뮬레이션이 끝날 때의 최종 위치는 공기 유입 가능성을 나타냅니다.

Sediment scour model

퇴적물 수송 및 침식 모델은 정확성과 안정성을 향상시키기 위해 정비되었습니다. 특히 퇴적물 종의 질량 보존이 크게 개선되었습니다.

개발 노트 읽기>

Outflow pressure boundary condition

고정 압력 경계 조건에는 압력 및 유체 분율을 제외한 모든 유량이 해당 경계의 상류의 유량 조건을 반영하는 ‘유출’옵션이 포함됩니다. 유출 압력 경계 조건은 고정 압력 및 연속 경계 조건의 하이브리드입니다.

Moving particle sources

시뮬레이션 중에 입자 소스를 이동할 수 있습니다. 시간에 따른 병진 및 회전 속도는 표 형식으로 정의됩니다. 입자 소스의 운동은 소스에서 방출 된 입자의 초기 속도에 추가됩니다.

Variable center of gravity

기변 무게중심은 중력 및 비관 성 기준 프레임 모델에서, 시간의 함수로서 무게 중심의 위치는 외부 파일에서 테이블로서 정의 될 수있다. 이 기능은 연료를 소비하고 분리 단계를 수행하는 로켓과 같은 모형을 모델링 할 때 유용합니다.

공기 유입 모델

가장 간단한 부피 기반 공기 유입 모델 옵션이 기존 질량 기반 모델로 대체되었습니다. 질량 기반 모델은 부피와 달리 주변 유체 압력에 따라 부피가 변화하는 동안 흡입된 공기량이 보존되기 때문에 물리학적 모델입니다.

Tracer diffusion

유동 표면에서 생성된 추적 물질은 분자 및 난류 확산 과정에 의해 확산될 수 있으며, 예를 들어 실제 오염 물질의 동작을 모방한다.

Model Setup

Simulation units

온도를 포함하여 단위 시스템은 완전히 정의해야하는데 표준 단위 시스템이 제공됩니다. 또한 사용자는 다양한 옵션 중에서 질량, 시간 및 길이 단위를 정의 할 수 있으므로 사용자 정의가 가능한 편리한 단위를 사용할 수 있습니다. 사용자는 압력이 게이지 또는 절대 단위로 정의되는지 여부도 지정해야합니다. 기본 시뮬레이션 단위는 기본 설정에서 설정할 수 있습니다. 단위를 완전히 정의하면 FLOW-3D 가 물리량의 기본값을 정의하고 범용 상수를 설정하여 사용자가 요구하는 작업량을 최소화 할 수 있습니다.

Shallow water model

Manning’s roughness in shallow water model

Manning의 거칠기 계수는 지형 표면의 전단 응력 평가를 위해 얕은 물 모델에서 구현되었습니다. 표면 결함의 크기를 기반으로 기존 거칠기 모델을 보완하며 이 모델과 함께 사용할 수 있습니다. 표준 거칠기와 마찬가지로 매닝 계수는 구성 요소 또는 하위 구성 요소의 속성이거나 지형 래스터 데이터 세트에서 가져올 수 있습니다.

Mesh generation

하단 및 상단 경계 좌표의 정의만으로 수직 방향의 메시 설정이 단순화되었습니다.

Component transformations

사용자는 이제 여러 하위 구성 요소로 구성된 구성 요소에 회전, 변환 및 스케일링 변환을 적용하여 복잡한 형상 어셈블리 설정 프로세스를 단순화 할 수 있습니다. GMO (General Moving Object) 구성 요소의 경우, 이러한 변환을 구성 요소의 대칭 축과 정렬되도록 신체에 맞는 좌표계에 적용 할 수 있습니다.

Changing the number of threads at runtime

시뮬레이션 중에 솔버가 사용하는 스레드 수를 변경하는 기능이 런타임 옵션 대화 상자에 추가되어 사용 가능한 스레드를 추가하거나 다른 태스크에 자원이 필요한 경우 스레드 수를 줄일 수 있습니다.

Probe-controlled heat sources

활성 시뮬레이션 제어가 형상 구성 요소와 관련된 heat sources로 확장되었습니다. 히스토리 프로브로 열 방출을 제어 할 수 있습니다.

Time-dependent temperature at sources     

질량 및 질량 / 운동량 소스의 유체 온도는 이제 테이블 입력을 사용하여 시간의 함수로 정의 할 수 있습니다.

Emissivity coefficients

공극으로의 복사 열 전달을위한 방사율 계수는 이제 사용자가 방사율과 스테판-볼츠만 상수를 지정하도록 요구하지 않고 직접 정의됩니다. 후자는 이제 단위 시스템을 기반으로 솔버에 의해 자동으로 설정됩니다.

Output

  • 등속 필드 솔버 옵션을 사용할 때 유량 속도를 선택한 데이터 로 출력 할 수 있습니다 .
  • 벽 접착력으로 인한 지오메트리 구성 요소의 토크 는 기존 벽 접착력의 출력 외에도 일반 이력 데이터에 별도의 수량으로 출력됩니다.
  • 난류 모델 출력이 요청 될 때 난류 에너지 및 소산과 함께 전단 속도 및 y +가 선택된 데이터로 자동 출력됩니다 .
  • 공기 유입 모델 출력에 몇 가지 수량이 추가되었습니다. 자유 표면을 포함하는 모든 셀에서 혼입 된 공기 및 빠져 나가는 공기의 체적 플럭스가 재시작 및 선택된 데이터로 출력되어 사용자에게 공기가 혼입 및 탈선되는 위치 및 시간에 대한 자세한 정보를 제공합니다. 전체 계산 영역 및 각 샘플링 볼륨 에 대해이 두 수량의 시간 및 공간 통합 등가물 이 일반 히스토리 로 출력됩니다.
  • 솔버의 출력 파일 flsgrf 의 최종 크기 는 시뮬레이션이 끝날 때보 고됩니다.
  • 2 유체 시뮬레이션의 경우, 기존의 출력 수량 유체 체류 시간 및 유체 가 이동 한 거리는 이제 유체 # 1 및 # 2와 유체의 혼합물에 대해 별도로 계산됩니다.
  • 질량 입자의 경우 각 종의 총 부피와 질량이 계산되어 전체 계산 영역, 샘플링 볼륨 및 플럭스 표면에 대한 일반 히스토리 로 출력되어 입자 종 수에 대한 현재 출력을 보완합니다.
  • 예를 들어 사용자가 가스 미순환을 식별하고 연료 탱크의 환기 시스템을 설계하는 데 도움이 되도록 마지막 국부적 가스 압력이 옵션 출력량으로 추가되었습니다. 이 양은 유체가 채워지기 전에 셀의 마지막 간극 압력을 기록하며, 단열 버블 모델과 함께 사용됩니다.

New Customizable Source Routines

사용자 정의 가능한 새로운 소스 루틴이 추가되었으며 사용자의 개발 환경에서 액세스 할 수 있습니다.

소스 루틴 이름설명
cav_prod_cal캐비 테이션 생산 및 확산 속도
sldg_uset슬러지 정착 속도
phchg_mass_flux증발 및 응축에 의한 질량 흐름
flhtccl유체#1과#2사이의 열 전달 계수
dsize_cal2상 유동에서의 동적 낙하 크기 모델의 충돌 및 이탈율
elstc_custom.점탄성 유체에 대한 응력 방정식의 소스 용어

Brand New User Interface

FLOW-3D의 사용자 인터페이스가 완전히 재설계되어 사용자의 작업 흐름을 획기적으로 간소화하는 최신의 타일 구조를 제공합니다.

Dock widgets 설정

Physics, Fluids, Mesh 및 FAVOR ™를 포함한 모든 설정 작업이 형상 창 주위의 dock widgets으로 변환되어 모델 설정을 단일 탭으로 압축 할 수 있습니다. 이 전환을 통해 이전 버전의 복잡한 트리가 훨씬 깔끔하고 효율적인 메뉴 표시로 바뀌어 모델 설정 탭을 떠나지 않고도 모든 매개 변수에 쉽게 액세스 할 수 있습니다.

New Model Setup icons
With our new Model Setup design comes new icons, representing each step of the setup process.
New Physics icons
Our Physics icons are designed to be easily differentiated from one another at a glance, while providing clear visual representation of each model’s purpose and use.

RSS feed

새 RSS 피드부터 FLOW-3D v12.0 의 시뮬레이션 관리자 탭이 개선되었습니다 . FLOW-3D 를 시작하면 사용자에게 Flow Science의 최신 뉴스, 이벤트 및 블로그 게시물이 표시됩니다.

Configurable simulation monitor

시뮬레이션을 실행할 때 중요한 작업은 모니터링입니다. FLOW-3Dv12.0에서는 사용자가 시뮬레이션을 더 잘 모니터링할 수 있도록 Simulation Manager의 플로팅 기능이 향상되었습니다. 사용자는 시뮬레이션 런타임 그래프를 통해 모니터링할 사용 가능한 모든 일반 기록 데이터 변수를 선택하고 각 그래프에 여러 변수를 추가할 수 있습니다. 이제 런타임에서 사용할 수 있는 일반 기록 데이터는 다음과 같습니다.

  • 최소/최대 유체 온도
  • 프로브 위치의 온도
  • 유동 표면 위치에서의 유량
  • 시뮬레이션 진단(예:시간 단계, 안정성 한계)
Runtime plots of the flow rate at the gates of the large dam / Large dam with flux surfaces at the gates

Conforming mesh visualization

사용자는 이제 새로운 FAVOR ™ 독 위젯을 통해 적합한 메쉬 블록을 시각화 할 수 있습니다 .

Large raster and STL data

데이터를 처리하는 데 걸리는 시간으로 인해 큰 형상 데이터를 처리하는 것은 어려울 수 있습니다. 대형 지오메트리 데이터를 처리하는 데 여전히 상당한 시간이 소요될 수 있지만 FLOW-3D는 이제 이러한 대형 데이터 세트를 백그라운드 작업으로로드하여 사용자가 데이터를 처리하는 동안 완벽하게 응답하고 중단없는 인터페이스에서 계속 작업 할 수 있습니다.

Additive Manufacturing & Welding Bibliography

적층제조 및 용접 해석 참고문헌

아래는 당사의 적층 제조 및 용접 참고 문헌에 수록된 기술 문서 모음입니다. 이 모든 논문에는 FLOW-3D AM 결과가 나와 있습니다. FLOW-3D AM을 사용하여 적층 제조, 레이저 용접 및 기타 용접 기술에 있는 프로세스를 성공적으로 시뮬레이션하는 방법에 대해 자세히 알아봅니다.

Additive Manufacturing & Welding Bibliography

Below is a collection of technical papers in our Additive Manufacturing and Welding Bibliography. All of these papers feature FLOW-3D AM results. Learn more about how FLOW-3D AM can be used to successfully simulate the processes found in Additive ManufacturingLaser Welding, and other welding technologies.

61-20       Raphael Comminal, Wilson Ricardo Leal da Silva, Thomas Juul Andersen, Henrik Stang, Jon Spangenberg, Influence of processing parameters on the layer geometry in 3D concrete printing: Experiments and modelling, 2nd RILEM International Conference on Concrete and Digital Fabrication, RILEM Bookseries, 28; pp. 852-862, 2020. doi.org/10.1007/978-3-030-49916-7_83

60-20       Marcin P. Serdeczny, Raphaël Comminal, Md. Tusher Mollah, David B. Pedersen, Jon Spangenberg, Numerical modeling of the polymer flow through the hot-end in filament-based material extrusion additive manufacturing, Additive Manufacturing, 36; 101454, 2020. doi.org/10.1016/j.addma.2020.101454

58-20       H.L. Wei, T. Mukherjee, W. Zhang, J.S. Zuback, G.L. Knapp, A. De, T. DebRoy, Mechanistic models for additive manufacturing of metallic components, Progress in Materials Science, preprint, 2020. doi.org/10.1016/j.pmatsci.2020.100703

55-20       Masoud Mohammadpour, Experimental study and numerical simulation of heat transfer and fluid flow in laser welded and brazed joints, Thesis, Southern Methodist University, Dallas, TX, US; Available in Mechanical Engineering Research Theses and Dissertations, 24, 2020.

48-20     Masoud Mohammadpour, Baixuan Yang, Hui-Ping Wang, John Forrest, Michael Poss, Blair Carlson, Radovan Kovacevica, Influence of laser beam inclination angle on galvanized steel laser braze quality, Optics and Laser Technology, 129; 106303, 2020. doi.org/10.1016/j.optlastec.2020.106303

34-20       Binqi Liu, Gang Fang, Liping Lei, Wei Liu, A new ray tracing heat source model for mesoscale CFD simulation of selective laser melting (SLM), Applied Mathematical Modeling, 79; pp. 506-520, 2020. doi.org/10.1016/j.apm.2019.10.049

27-20   Xuesong Gao, Guilherme Abreu Farira, Wei Zhang and Kevin Wheeler, Numerical analysis of non-spherical particle effect on molten pool dynamics in laser-powder bed fusion additive manufacturing, Computational Materials Science, 179, art. no. 109648, 2020. doi.org/10.1016/j.commatsci.2020.109648

26-20   Yufan Zhao, Yuichiro Koizumi, Kenta Aoyagi, Kenta Yamanaka and Akihiko Chiba, Isothermal γ → ε phase transformation behavior in a Co-Cr-Mo alloy depending on thermal history during electron beam powder-bed additive manufacturing, Journal of Materials Science & Technology, 50, pp. 162-170, 2020. doi.org/10.1016/j.jmst.2019.11.040

21-20   Won-Ik Cho and Peer Woizeschke, Analysis of molten pool behavior with buttonhole formation in laser keyhole welding of sheet metal, International Journal of Heat and Mass Transfer, 152, art. no. 119528, 2020. doi.org/10.1016/j.ijheatmasstransfer.2020.119528

06-20   Wei Xing, Di Ouyang, Zhen Chen and Lin Liu, Effect of energy density on defect evolution in 3D printed Zr-based metallic glasses by selective laser melting, Science China Physics, Mechanics & Astronomy, 63, art. no. 226111, 2020. doi.org/10.1007/s11433-019-1485-8

04-20    Santosh Reddy Sama, Tony Badamo, Paul Lynch and Guha Manogharan, Novel sprue designs in metal casting via 3D sand-printing, Additive Manufacturing, 25, pp. 563-578, 2019. doi.org/10.1016/j.addma.2018.12.009

02-20   Dongsheng Wu, Shinichi Tashiro, Ziang Wu, Kazufumi Nomura, Xueming Hua, and Manabu Tanaka, Analysis of heat transfer and material flow in hybrid KPAW-GMAW process based on the novel three dimensional CFD simulation, International Journal of Heat and Mass Transfer, 147, art. no. 118921, 2020. doi.org/10.1016/j.ijheatmasstransfer.2019.118921

01-20   Xiang Huang, Siying Lin, Zhenxiang Bu, Xiaolong Lin, Weijin Yi, Zhihong Lin, Peiqin Xie, and Lingyun Wang, Research on nozzle and needle combination for high frequency piezostack-driven dispenser, International Journal of Adhesion and Adhesives, 96, 2020. doi.org/10.1016/j.ijadhadh.2019.102453

101-19   Wei Xing, Di Ouyang, Zhen Chen and Lin Liu, Effect of energy density on defect evolution in 3D printed Zr-based metallic glasses by selective laser melting, Science China Physics, Mechanics & Astronomy, 63, art. no. 226111, 2019.

88-19   Bo Cheng and Charles Tuffile, Numerical study of porosity formation with implementation of laser multiple reflection in selective laser melting, Proceedings Volume 1: Additive Manufacturing; Manufacturing Equipment and Systems; Bio and Sustainable Manufacturing, ASME 2019 14th International Manufacturing Science and Engineering Conference, Erie, Pennsylvania, USA, June 10-14, 2019. doi.org/10.1115/MSEC2019-2891

87-19   Shuhao Wang, Lida Zhu, Jerry Ying His Fuh, Haiquan Zhang, and Wentao Yan, Multi-physics modeling and Gaussian process regression analysis of cladding track geometry for direct energy deposition, Optics and Lasers in Engineering, 127:105950, 2019. doi.org/10.1016/j.optlaseng.2019.105950

78-19   Bo Cheng, Lukas Loeber, Hannes Willeck, Udo Hartel, and Charles Tuffile, Computational investigation of melt pool process dynamics and pore formation in laser powder bed fusion, Journal of Materials Engineering and Performance, 28:11, 6565-6578, 2019. doi.org/10.1007/s11665-019-04435-y

77-19   David Souders, Pareekshith Allu, Anurag Chandorkar, and Ruendy Castillo, Application of computational fluid dynamics in developing process parameters for additive manufacturing, Additive Manufacturing Journal, 9th International Conference on 3D Printing and Additive Manufacturing Technologies (AM 2019), Bangalore, India, September 7-9, 2019.

75-19   Raphaël Comminal, Marcin Piotr Serdeczny, Navid Ranjbar, Mehdi Mehrali, David Bue Pedersen, Henrik Stang, Jon Spangenberg, Modelling of material deposition in big area additive manufacturing and 3D concrete printing, Proceedings, Advancing Precision in Additive Manufacturing, Nantes, France, September 16-18, 2019.

73-19   Baohua Chang, Zhang Yuan, Hao Cheng, Haigang Li, Dong Du 1, and Jiguo Shan, A study on the influences of welding position on the keyhole and molten pool behavior in laser welding of a titanium alloy, Metals, 9:1082, 2019. doi.org/10.3390/met9101082

60-19   Binqi Liu, Gang Fang, Liping Lei, and Wei Liu, A new ray tracing heat source model for mesoscale CFD simulation of selective laser melting (SLM), Applied Mathematical Modeling, in press, 2019. doi.org/10.1016/j.apm.2019.10.049

57-19     Shengjie Deng, Hui-Ping Wang, Fenggui Lu, Joshua Solomon, and Blair E. Carlson, Investigation of spatter occurrence in remote laser spiral welding of zinc-coated steels, International Journal of Heat and Mass Transfer, Vol. 140, pp. 269-280, 2019. doi.org/10.1016/j.ijheatmasstransfer.2019.06.009

53-19     Mohamad Bayat, Aditi Thanki, Sankhya Mohanty, Ann Witvrouw, Shoufeng Yang, Jesper Thorborg, Niels Skat Tieldje, and Jesper Henri Hattel, Keyhole-induced porosities in Laser-based Powder Bed Fusion (L-PBF) of Ti6Al4V: High-fidelity modelling and experimental validation, Additive Manufacturing, Vol. 30, 2019. doi.org/10.1016/j.addma.2019.100835

51-19     P. Ninpetch, P. Kowitwarangkul, S. Mahathanabodee, R. Tongsri, and P. Ratanadecho, Thermal and melting track simulations of laser powder bed fusion (L-PBF), International Conference on Materials Research and Innovation (ICMARI), Bangkok, Thailand, December 17-21, 2018. IOP Conference Series: Materials Science and Engineering, Vol. 526, 2019. doi.org/10.1088/1757-899X/526/1/012030

46-19     Hongze Wang and Yu Zou, Microscale interaction between laser and metal powder in powder-bed additive manufacturing: Conduction mode versus keyhole mode, International Journal of Heat and Mass Transfer, Vol. 142, 2019. doi.org/10.1016/j.ijheatmasstransfer.2019.118473

45-19     Yufan Zhao, Yuichiro Koizumi, Kenta Aoyagi, Kenta Yamanaka, and Akihiko Chiba, Manipulating local heat accumulation towards controlled quality and microstructure of a Co-Cr-Mo alloy in powder bed fusion with electron beam, Materials Letters, Vol. 254, pp. 269-272, 2019. doi.org/10.1016/j.matlet.2019.07.078

44-19     Guoxiang Xu, Lin Li, Houxiao Wang, Pengfei Li, Qinghu Guo, Qingxian Hu, and Baoshuai Du, Simulation and experimental studies of keyhole induced porosity in laser-MIG hybrid fillet welding of aluminum alloy in the horizontal position, Optics & Laser Technology, Vol. 119, 2019. doi.org/10.1016/j.optlastec.2019.105667

38-19     Subin Shrestha and Y. Kevin Chou, A numerical study on the keyhole formation during laser powder bed fusion process, Journal of Manufacturing Science and Engineering, Vol. 141, No. 10, 2019. doi.org/10.1115/1.4044100

34-19     Dae-Won Cho, Jin-Hyeong Park, and Hyeong-Soon Moon, A study on molten pool behavior in the one pulse one drop GMAW process using computational fluid dynamics, International Journal of Heat and Mass Transfer, Vol. 139, pp. 848-859, 2019. doi.org/10.1016/j.ijheatmasstransfer.2019.05.038

30-19     Mohamad Bayat, Sankhya Mohanty, and Jesper Henri Hattel, Multiphysics modelling of lack-of-fusion voids formation and evolution in IN718 made by multi-track/multi-layer L-PBF, International Journal of Heat and Mass Transfer, Vol. 139, pp. 95-114, 2019. doi.org/10.1016/j.ijheatmasstransfer.2019.05.003

29-19     Yufan Zhao, Yuichiro Koizumi, Kenta Aoyagi, Daixiu Wei, Kenta Yamanaka, and Akihiko Chiba, Comprehensive study on mechanisms for grain morphology evolution and texture development in powder bed fusion with electron beam of Co–Cr–Mo alloy, Materialia, Vol. 6, 2019. doi.org/10.1016/j.mtla.2019.100346

28-19     Pareekshith Allu, Computational fluid dynamics modeling in additive manufacturing processes, The Minerals, Metals & Materials Society (TMS) 148th Annual Meeting & Exhibition, San Antonio, Texas, USA, March 10-14, 2019.

24-19     Simulation Software: Use, Advantages & Limitations, The Additive Manufacturing and Welding Magazine, Vol. 2, No. 2, 2019

22-19     Hunchul Jeong, Kyungbae Park, Sungjin Baek, and Jungho Cho, Thermal efficiency decision of variable polarity aluminum arc welding through molten pool analysis, International Journal of Heat and Mass Transfer, Vol. 138, pp. 729-737, 2019. doi.org/10.1016/j.ijheatmasstransfer.2019.04.089

07-19   Guangxi Zhao, Jun Du, Zhengying Wei, Ruwei Geng and Siyuan Xu, Numerical analysis of arc driving forces and temperature distribution in pulsed TIG welding, Journal of the Brazilian Society of Mechanical Sciences and Engineering, Vol. 41, No. 60, 2019. doi.org/10.1007/s40430-018-1563-0

04-19   Santosh Reddy Sama, Tony Badamo, Paul Lynch and Guha Manogharan, Novel sprue designs in metal casting via 3D sand-printing, Additive Manufacturing, Vol. 25, pp. 563-578, 2019. doi.org/10.1016/j.addma.2018.12.009

03-19   Dongsheng Wu, Anh Van Nguyen, Shinichi Tashiro, Xueming Hua and Manabu Tanaka, Elucidation of the weld pool convection and keyhole formation mechanism in the keyhold plasma arc welding, International Journal of Heat and Mass Transfer, Vol. 131, pp. 920-931, 2019. doi.org/10.1016/j.ijheatmasstransfer.2018.11.108

84-18   Bo Cheng, Xiaobai Li, Charles Tuffile, Alexander Ilin, Hannes Willeck and Udo Hartel, Multi-physics modeling of single track scanning in selective laser melting: Powder compaction effect, Proceedings of the 29th Annual International Solid Freeform Fabrication Symposium, pp. 1887-1902, 2018.

81-18 Yufan Zhao, Yuichiro Koizumi, Kenta Aoyagi, Daixiu Wei, Kenta Yamanaka and Akihiko Chiba, Molten pool behavior and effect of fluid flow on solidification conditions in selective electron beam melting (SEBM) of a biomedical Co-Cr-Mo alloy, Additive Manufacturing, Vol. 26, pp. 202-214, 2019. doi.org/10.1016/j.addma.2018.12.002

77-18   Jun Du and Zhengying Wei, Numerical investigation of thermocapillary-induced deposited shape in fused-coating additive manufacturing process of aluminum alloy, Journal of Physics Communications, Vol. 2, No. 11, 2018. doi.org/10.1088/2399-6528/aaedc7

76-18   Yu Xiang, Shuzhe Zhang, Zhengying We, Junfeng Li, Pei Wei, Zhen Chen, Lixiang Yang and Lihao Jiang, Forming and defect analysis for single track scanning in selective laser melting of Ti6Al4V, Applied Physics A, 124:685, 2018. doi.org/10.1007/s00339-018-2056-9

74-18   Paree Allu, CFD simulations for laser welding of Al Alloys, Proceedings, Die Casting Congress & Exposition, Indianapolis, IN, October 15-17, 2018.

72-18   Hunchul Jeong, Kyungbae Park, Sungjin Baek, Dong-Yoon Kim, Moon-Jin Kang and Jungho Cho, Three-dimensional numerical analysis of weld pool in GMAW with fillet joint, International Journal of Precision Engineering and Manufacturing, Vol. 19, No. 8, pp. 1171-1177, 2018. doi.org/10.1007/s12541-018-0138-4

60-18   R.W. Geng, J. Du, Z.Y. Wei and G.X. Zhao, An adaptive-domain-growth method for phase field simulation of dendrite growth in arc preheated fused-coating additive manufacturing, IOP Conference Series: Journal of Physics: Conference Series 1063, 012077, 2018. doi.org/10.1088/1742-6596/1063/1/012077 (Available at http://iopscience.iop.org/article/10.1088/1742-6596/1063/1/012077/pdf and in shared drive)

59-18   Guangxi Zhao, Jun Du, Zhengying Wei, Ruwei Geng and Siyuan Xu, Coupling analysis of molten pool during fused coating process with arc preheating, IOP Conference Series: Journal of Physics: Conference Series 1063, 012076, 2018. doi.org/10.1088/1742-6596/1063/1/012076 (Available at http://iopscience.iop.org/article/10.1088/1742-6596/1063/1/012076/pdf and in shared drive)

58-18   Siyuan Xu, Zhengying Wei, Jun Du, Guangxi Zhao and Wei Liu, Numerical simulation and analysis of metal fused coating forming, IOP Conference Series: Journal of Physics: Conference Series 1063, 012075, 2018. doi.org/10.1088/1742-6596/1063/1/012075

55-18   Jason Cheon, Jin-Young Yoon, Cheolhee Kim and Suck-Joo Na, A study on transient flow characteristic in friction stir welding with realtime interface tracking by direct surface calculation, Journal of Materials Processing Tech., vol. 255, pp. 621-634, 2018.

54-18   V. Sukhotskiy, P. Vishnoi, I. H. Karampelas, S. Vader, Z. Vader, and E. P. Furlani, Magnetohydrodynamic drop-on-demand liquid metal additive manufacturing: System overview and modeling, Proceedings of the 5th International Conference of Fluid Flow, Heat and Mass Transfer, Niagara Falls, Canada, June 7 – 9, 2018; Paper no. 155, 2018. doi.org/10.11159/ffhmt18.155

52-18   Michael Hilbinger, Claudia Stadelmann, Matthias List and Robert F. Singer, Temconex® – Kontinuierliche Pulverextrusion: Verbessertes Verständnis mit Hilfe der numerischen Simulation, Hochleistungsmetalle und Prozesse für den Leichtbau der Zukunft, Tagungsband 10. Ranshofener Leichtmetalltage, 13-14 Juni 2018, Linz, pp. 175-186, 2018.

38-18   Zhen Chen, Yu Xiang, Zhengying Wei, Pei Wei, Bingheng Lu, Lijuan Zhang and Jun Du, Thermal dynamic behavior during selective laser melting of K418 superalloy: numerical simulation and experimental verification, Applied Physics A, vol. 124, pp. 313, 2018. doi.org/10.1007/s00339-018-1737-8

19-18   Chenxiao Zhu, Jason Cheon, Xinhua Tang, Suck-Joo Na, and Haichao Cui, Molten pool behaviors and their influences on welding defects in narrow gap GMAW of 5083 Al-alloy, International Journal of Heat and Mass Transfer, vol. 126:A, pp.1206-1221, 2018. doi.org/10.1016/j.ijheatmasstransfer.2018.05.132

16-18   P. Schneider, V. Sukhotskiy, T. Siskar, L. Christie and I.H. Karampelas, Additive Manufacturing of Microfluidic Components via Wax Extrusion, Biotech, Biomaterials and Biomedical TechConnect Briefs, vol. 3, pp. 162 – 165, 2018.

09-18   The Furlani Research Group, Magnetohydrodynamic Liquid Metal 3D Printing, Department of Chemical and Biological Engineering, © University at Buffalo, May 2018.

08-18   Benjamin Himmel, Dominik Rumschöttel and Wolfram Volk, Thermal process simulation of droplet based metal printing with aluminium, Production Engineering, March 2018 © German Academic Society for Production Engineering (WGP) 2018.

07-18   Yu-Che Wu, Cheng-Hung San, Chih-Hsiang Chang, Huey-Jiuan Lin, Raed Marwan, Shuhei Baba and Weng-Sing Hwang, Numerical modeling of melt-pool behavior in selective laser melting with random powder distribution and experimental validation, Journal of Materials Processing Tech. 254 (2018) 72–78.

60-17   Pei Wei, Zhengying Wei, Zhen Chen, Yuyang He and Jun Du, Thermal behavior in single track during selective laser melting of AlSi10Mg powder, Applied Physics A: Materials Science & Processing, 123:604, 2017. doi.org/10.1007/z00339-017-1194-9

51-17   Koichi Ishizaka, Keijiro Saitoh, Eisaku Ito, Masanori Yuri, and Junichiro Masada, Key Technologies for 1700°C Class Ultra High Temperature Gas Turbine, Mitsubishi Heavy Industries Technical Review, vol. 54, no. 3, 2017.

49-17   Yu-Che Wu, Weng-Sing Hwang, Cheng-Hung San, Chih-Hsiang Chang and Huey-Jiuan Lin, Parametric study of surface morphology for selective laser melting on Ti6Al4V powder bed with numerical and experimental methods, International Journal of Material Forming, © Springer-Verlag France SAS, part of Springer Nature 2017. doi.org/10.1007/s12289-017-1391-2.

37-17   V. Sukhotskiy, I. H. Karampelas, G. Garg, A. Verma, M. Tong, S. Vader, Z. Vader, and E. P. Furlani, Magnetohydrodynamic Drop-on-Demand Liquid Metal 3D Printing, Solid Freeform Fabrication 2017: Proceedings of the 28th Annual International Solid Freeform Fabrication Symposium – An Additive Manufacturing Conference

14-17   Jason Cheon and Suck-Joo Na, Prediction of welding residual stress with real-time phase transformation by CFD thermal analysis, International Journal of Mechanical Sciences 131–132 (2017) 37–51.

91-16   Y. S. Lee and D. F. Farson, Surface tension-powered build dimension control in laser additive manufacturing process, Int J Adv Manuf Technol (2016) 85:1035–1044, doi.org/10.1007/s00170-015-7974-5.

84-16   Runqi Lin, Hui-ping Wang, Fenggui Lu, Joshua Solomon, Blair E. Carlson, Numerical study of keyhole dynamics and keyhole-induced porosity formation in remote laser welding of Al alloys, International Journal of Heat and Mass Transfer 108 (2017) 244–256, Available online December 2016.

68-16   Dongsheng Wu, Xueming Hua, Dingjian Ye and Fang Li, Understanding of humping formation and suppression mechanisms using the numerical simulation, International Journal of Heat and Mass Transfer, Volume 104, January 2017, Pages 634–643, Published online 2016.

26-16   Y.S. Lee and W. Zhang, Modeling of heat transfer, fluid flow and solidification microstructure of nickel-base superalloy fabricated by laser powder bed fusion, S2214-8604(16)30087-2, doi.org/10.1016/j.addma.2016.05.003, ADDMA 86.

123-15   Koji Tsukimoto, Masashi Kitamura, Shuji Tanigawa, Sachio Shimohata, and Masahiko Mega, Laser welding repair for single crystal blades, Proceedings of International Gas Turbine Congress, pp. 1354-1358, 2015.

116-15   Yousub Lee, Simulation of Laser Additive Manufacturing and its Applications, Ph.D. Thesis: Graduate Program in Welding Engineering, The Ohio State University, 2015, Copyright by Yousub Lee 2015

103-15   Ligang Wu, Jason Cheon, Degala Venkata Kiran, and Suck-Joo Na, CFD Simulations of GMA Welding of Horizontal Fillet Joints based on Coordinate Rotation of Arc Models, Journal of Materials Processing Technology, Available online December 29, 2015

96-15   Jason Cheon, Degala Venkata Kiran, and Suck-Joo Na, Thermal metallurgical analysis of GMA welded AH36 steel using CFD – FEM framework, Materials & Design, Volume 91, February 5 2016, Pages 230-241, published online November 2015

25-15   Dae-Won Cho and Suck-Joo Na, Molten pool behaviors for second pass V-groove GMAW, International Journal of Heat and Mass Transfer 88 (2015) 945–956.

21-15   Jungho Cho, Dave F. Farson, Kendall J. Hollis and John O. Milewski, Numerical analysis of weld pool oscillation in laser welding, Journal of Mechanical Science and Technology 29 (4) (2015) 1715~1722, www.springerlink.com/content/1738-494x, doi.org/10.1007/s12206-015-0344-2.

82-14  Yousub Lee, Mark Nordin, Sudarsanam Suresh Babu, and Dave F. Farson, Effect of Fluid Convection on Dendrite Arm Spacing in Laser Deposition, Metallurgical and Materials Transactions B, August 2014, Volume 45, Issue 4, pp 1520-1529

59-14   Y.S. Lee, M. Nordin, S.S. Babu, and D.F. Farson, Influence of Fluid Convection on Weld Pool Formation in Laser Cladding, Welding Research/ August 2014, VOL. 93

18-14  L.J. Zhang, J.X. Zhang, A. Gumenyuk, M. Rethmeier, and S.J. Na, Numerical simulation of full penetration laser welding of thick steel plate with high power high brightness laser, Journal of Materials Processing Technology (2014), doi.org/10.1016/j.jmatprotec.2014.03.016.

36-13  Dae-Won Cho,Woo-Hyun Song, Min-Hyun Cho, and Suck-Joo Na, Analysis of Submerged Arc Welding Process by Three-Dimensional Computational Fluid Dynamics Simulations, Journal of Materials Processing Technology, 2013. doi.org/10.1016/j.jmatprotec.2013.06.017

12-13 D.W. Cho, S.J. Na, M.H. Cho, J.S. Lee, A study on V-groove GMAW for various welding positions, Journal of Materials Processing Technology, April 2013, doi.org/10.1016/j.jmatprotec.2013.02.015.

01-13  Dae-Won Cho & Suck-Joo Na & Min-Hyun Cho & Jong-Sub Lee, Simulations of weld pool dynamics in V-groove GTA and GMA welding, Weld World, doi.org/10.1007/s40194-012-0017-z, © International Institute of Welding 2013.

63-12  D.W. Cho, S.H. Lee, S.J. Na, Characterization of welding arc and weld pool formation in vacuum gas hollow tungsten arc welding, Journal of Materials Processing Technology, doi.org/10.1016/j.jmatprotec.2012.09.024, September 2012.

77-10  Lim, Y. C.; Yu, X.; Cho, J. H.; et al., Effect of magnetic stirring on grain structure refinement Part 1-Autogenous nickel alloy welds, Science and Technology of Welding and Joining, Volume: 15 Issue: 7, Pages: 583-589, doi.org/10.1179/136217110X12720264008277, October 2010

18-10 K Saida, H Ohnishi, K Nishimoto, Fluxless laser brazing of aluminium alloy to galvanized steel using a tandem beam–dissimilar laser brazing of aluminium alloy and steels, Welding International, 2010

58-09  Cho, Jung-Ho; Farson, Dave F.; Milewski, John O.; et al., Weld pool flows during initial stages of keyhole formation in laser welding, Journal of Physics D-Applied Physics, Volume: 42 Issue: 17 Article Number: 175502 ; doi.org/10.1088/0022-3727/42/17/175502, September 2009

57-09  Lim, Y. C.; Farson, D. F.; Cho, M. H.; et al., Stationary GMAW-P weld metal deposit spreading, Science and Technology of Welding and Joining, Volume: 14 Issue: 7 ;Pages: 626-635, doi.org/10.1179/136217109X441173, October 2009

1-09 J.-H. Cho and S.-J. Na, Three-Dimensional Analysis of Molten Pool in GMA-Laser Hybrid Welding, Welding Journal, February 2009, Vol. 88

52-07   Huey-Jiuan Lin and Wei-Kuo Chang, Design of a sheet forming apparatus for overflow fusion process by numerical simulation, Journal of Non-Crystalline Solids 353 (2007) 2817–2825.

50-07  Cho, Min Hyun; Farson, Dave F., Understanding bead hump formation in gas metal arc welding using a numerical simulation, Metallurgical and Mateials Transactions B-Process Metallurgy and Materials Processing Science, Volume: 38, Issue: 2, Pages: 305-319, doi.org/10.1007/s11663-007-9034-5, April 2007

49-07  Cho, M. H.; Farson, D. F., Simulation study of a hybrid process for the prevention of weld bead hump formation, Welding Journal Volume: 86, Issue: 9, Pages: 253S-262S, September 2007

48-07  Cho, M. H.; Farson, D. F.; Lim, Y. C.; et al., Hybrid laser/arc welding process for controlling bead profile, Science and Technology of Welding and Joining, Volume: 12 Issue: 8, Pages: 677-688, doi.org/10.1179/174329307X236878, November 2007

47-07   Min Hyun Cho, Dave F. Farson, Understanding Bead Hump Formation in Gas Metal Arc Welding Using a Numerical Simulation, Metallurgical and Materials Transactions B, Volume 38, Issue 2, pp 305-319, April 2007

36-06  Cho, M. H.; Lim, Y. C.; Farson, D. F., Simulation of weld pool dynamics in the stationary pulsed gas metal arc welding process and final weld shape, Welding Journal, Volume: 85 Issue: 12, Pages: 271S-283S, December 2006

Sand Core Making / 모래 코어 제작

Sand Core Making / 모래 코어 제작

This article on sand core making was contributed by Dr. Matthias Todte and Frieder Semler, Flow Science Deutschland GmbH.

주조 품질에 대한 수요가 증가하고 고성능 구성 요소에 대한 박막형 구조로의 추세로 인해 품질에 대한 요구가 강화되었으며 동시에 모래 코어의 기하학적 복잡성도 증가했습니다. 시뮬레이션은 코어 박스의 설계를 최적화하는 데 도움이 되며, 저온 및 고온 코어 박스를 위한 유기 및 무기 바인더 시스템의 촬영, 가스 처리 및 경화를 위한 강력한 공정 조건을 확립합니다.

기체 주입, 건조 및 템퍼링의 기본 프로세스에 대한 논의는 실험적 검증을 거쳐야 합니다. 그런 다음 주물 결함을 방지하기 위해 코어 사격 공정 시뮬레이션이 필수적이었는지를 보여 줍니다. 마지막으로 코어 박스의 마모와 수명을 예측하는 수치모델을 개발한 연구 프로젝트를 소개합니다.

Water jacket core

Simulation of sand core making processes

Shooting

Shooting Simulation에서 모래로 채워진 타격 헤드가 공기를 통해 가압되고, 이로 인해 공기/모래/실린더/바인더 혼합물로 구성된 “유체”가 생성됩니다. 이 유체는 분사 노즐을 통해 코어 박스로 흐르고 배출 노즐을 통해 상자 밖으로 공기가 배출됩니다. Shooting Simulation의 목적은 코어 박스에 있는 모래의 밀도분포를 높히고 균일하게 하는 것입니다.

촬영 과정에서 모래로 채워진 블로 헤드가 공기를 통해 가압되어 공기/모래/바인더 혼합물로 구성된 “유체”가 생성됩니다. 이 유체는 블로우 헤드에서 분사 노즐을 통해 코어 박스로 흘러 나와 공기를 환기 노즐을 통해 박스 밖으로 밀어냅니다. Shooting 의 목표는 가능한 한 높고 균일하게 코어 박스에 있는 모래의 밀도 분포를 달성하는 것입니다. 변경할 수 있는 프로세스 매개 변수는 분사 압력과 발사 및 배기 노즐의 수와 위치입니다. 시간과 비용을 절약하기 위해 코어의 품질을 저하시키지 않고 가능한 한 노즐을 적게 사용하는 것이 바람직합니다.

Sand density distribution

Sand density distribution after the shooting

시뮬레이션을 사용하여 다양한 사격 및 환기 노즐 구성과 그 구성이 결과 모래 밀도 분포에 미치는 영향을 분석할 수 있습니다. 엔지니어는 속도와 전단 응력을 예측하여 코어 상자의 마모 및 이에 따른 수명에 대한 결론을 도출할 수 있습니다.

Gassing

유기 바인더 시스템에서는 모래가 유기 수지로 코팅됩니다. 이 수지의 경화는 보통 아민이라는 기체에 의해 이루어지는데, 이것은 일반적으로 분사에 사용된 노즐을 통해 주입됩니다. 이 가스는 코어가 모든 부분에서 경화되도록 하기위해 모든부분에 도달할 만큼 길어야 한다. 반면에, 유독 가스를 줄이기 위해서는 가스 배출이 필요이상으로 길어서는 안됩니다.

유기 바인더 시스템에서는 모래가 유기 레진으로 코팅되어 있습니다. 이 레진의 경화는 보통 아민 가스 작용제에 의해 이루어지는데, 아민은 주로 인젝션에 사용되는 노즐을 통해 분사됩니다. 이 가스 주입은 가스가 코어의 모든 부분에 도달할 수 있도록 충분히 길어야 합니다. 코어가 모든 곳에서 경화되도록 하기 위해서입니다. 반면, 가스 배출은 독성 가스를 절약하기 위해 필요 이상으로 길지 않아야 합니다.

Amine concentration core

Amine concentration in a core

시뮬레이션은 시간 경과에 따른 코어의 아민 농도 분포를 예측하며, 이는 코어의 경도와 동일하다. 이를 통해 엔지니어들은 가스 생성 공정에 대한 합리적인 시간 규모를 결정할 수 있습니다.

Drying

주조물의 수가 증가하는 경우, 독성이 있는 유기적 시스템 대신 무기, 수성-기반 바인더 시스템이 사용됩니다. 배기 가스 배출이 없는 코어 생산 공정의 이점 외에도 이 시스템은 주조 공정 중 코어 가스 생산량을 줄여 주조 품질을 향상시킵니다.

모래 코어의 경화를 위해서는 일반적으로 뜨거운 공기가 주입되어 이루어지는 코어에서 물을 제거해야 합니다. 이러한 바인더 시스템의 경우, 코어의 잔류 수분은 경도에 대한 측정 값입니다. 시뮬레이션은 코어를 통과하는 공기의 흐름뿐만 아니라 물이나 증기의 증발과 응축, 뜨거운 공기와 함께 증기의 이동을 모델링 해야 합니다.

아래 이미지는 예측된 잔류 수분과 실제 코어의 강도(또는 손상)의 상관 관계를 보여 줍니다.

Correlation of predicted residual moisture and the damage of a real core

Tempering of core boxes                                                                    

핫 박스 및 크로닝과 같은 특정 코어 제조 공정에서는 가열된 코어 박스에 있는 바인더의 열 반응을 통해 코어의 경화가 이루어집니다. 상자의 가열은 가열 채널과 전기 가열 요소를 사용하여 수행됩니다. 좋은 코어 품질을 위해서는 코어 상자의 균일한 온도 분포가 바람직합니다. 시뮬레이션은 특정 가열 소자 구성에 대한 온도 분포를 시간 경과에 따른 예측하고 발열의 균일성과 원하는 온도에 도달하는 데 필요한 시간을 표시합니다.

Heated core box

Temperature distribution in a heated core box

Validation of the core blowing model

Experiments and simulations for a water jacket core

핵심 shooting 실험은 TU 뮌헨의 파운드리 연구소에서 실시되었습니다. shooting  시간과 압력, 흡입구와 환기구의 수 등의 공정 매개 변수들이 다양하였으며 이들 매개 변수들이 분석된 코어 품질에 미치는 영향이 다양하였다. 실제 코어에서 발생한 결점은 시뮬레이션에서 모래 밀도가 낮은 영역과 상관 관계가 있습니다(아래 그림 참조).

Core blowing validation

Core defects compared to simulated density distribution

Application of the core blowing model : 리어 액슬 하우징의 주조 품질 개선

품질 보증에서 리어 액슬 하우징의 주물 결함을 감지했습니다(아래 그림 참조). 그 결함들은 중심부의 표면 결함의 결과인 것처럼 보였다. 이 가설을 뒷받침하고 코어 표면 품질을 개선하기 위한 조치를 권고하기 위해 시뮬레이션이 수행되었다. 마지막으로, 코어 박스 환기구의 다른 구성(숫자 및 위치)을 통해 주조 품질을 개선할 수 있었습니다.

Casting defects of a rear axle housing

Casting defects of a rear axle housing

Validation surface defects

Correlation of surface defects and simulated density distribution

Research project: Prediction of the lifetime of core boxes

코어 박스는 대부분 폴리우레탄 수지 코팅의 알루미늄으로 제작된다. 사격 과정에서 모래에 의한 코어 박스 표면의 침식은 코어 박스의 수명을 제한하는 요인이다. 프로젝트 목표는 표면 처리가 수명에 미치는 영향을 이해하고 단일 시뮬레이션에서 다수의 샷에 의해 발생하는 침식을 예측할 수 있는 연산 모델을 개발하는 침식 프로세스를 분석하는 것이었다.

일반적인 코어 상자(아래 참조)는 다른 모양의 삽입물로 제작되었습니다.

Core box with different inserts

Core box with different inserts

수치 모델은 코어 박스 벽의 압력과 전단력의 공간적, 시간적 통합에 기초하여 부식에 대한 양을 도출한다. 모형에 의해 예측된 침식은 실험 값과 일치했습니다(아래 그림 참조).

Measured and simulated erosion

Comparison of measured and simulated erosion

FLOW-3D 제품소개

About FLOW-3D


HPC-enabled FLOW-3D v12.0

FLOW-3D 개발 회사

Flow Science Inc Logo Green.svg
IndustryComputational Fluid Dynamics Software
Founded1980
FounderDr. C.W. “Tony” Hirt
Headquarters
Santa Fe, New Mexico, USA
United States
Key people
Dr. Amir Isfahani, President & CEO
ProductsFLOW-3D, FLOW-3D CAST, FLOW-3D AM, FLOW-3D CLOUD, FlowSight
ServicesCFD consultation and services

FLOW-3D 개요

FLOW-3D는 미국 뉴멕시코주(New Mexico) 로스알라모스(Los Alamos)에 있는 Flow Scicence, Inc에서 개발한 범용 전산유체역학(Computational Fluid Dynamics) 프로그램입니다. 로스알라모스 국립연구소의 수치유체역학 연구실에서 F.Harlow, B. Nichols 및 T.Hirt 등에 의해 개발된 MAC(Marker and Cell) 방법과 SOLA-VOF 방식을 기초로 하여, Hirt 박사가 1980년에 Flow Science, Inc사를 설립하여 계속 프로그램을 발전시켰으며 1985년부터 FLOW-3D를 전세계에 배포하였습니다.

유체의 3차원 거동 해석을 수행하는데 사용되는 CFD모형은 몇몇 있으나, 유동해석에 적용할 물리모델 선정은 해석의 정밀도와 밀접한 관계가 있으므로, 해석하고자 하는 대상의 유동 특성을 분석하여 신중하게 결정하여야 합니다.

FLOW-3D는 자유표면(Free Surface) 해석에 있어서 매우 정확한 해석 결과를 제공합니다. 해석방법은 자유표면을 포함한 비정상 유동 상태를 기본으로 하며, 연속방정식, 3차원 운동량 보전방정식(Navier-Stokes eq.) 및 에너지 보존방정식 등을 적용할 수 있습니다.

FLOW-3D는 유한차분법을 사용하고 있으며, 유한요소법(FEM, Finite Element Method), 경계요소법(Boundary Element Method)등을 포함하여 자유표면을 포함하는 유동장 해석(Fluid Flow Analysis)에서 공기와 액체의 경계면을 정밀하게 표현 가능합니다.

유체의 난류 해석에 대해서는 혼합길이 모형, 난류 에너지 모형, RNG(Renormalized Group Theory)  k-ε 모형, k-ω 모형, LES 모형 등 6개 모형을 적용할 수 있으며, 자유표면 해석을 위하여 VOF(Volume of Fluid) 방정식을 사용하고, 격자 생성시 사용자가 가장 쉽게 만들 수 있는 직각형상격자는 형상을 더욱 정확하게 표현하기 위해 FAVOR(Fractional Area Volume Obstacle Representation) 기법을 각 방정식에 적용하고 있습니다.

FLOW-3D는 비압축성(Incompressible Fluid Flow), 압축성 유체(Compressible Fluid Flow)의 유동현상 뿐만 아니라 고체와의 열전달 현상을 해석할 수 있으며, 비정상 상태의 해석을 기본으로 합니다.

FLOW-3D v12.0은 모델 설정을 간소화하고 사용자 워크 플로우를 개선하는 GUI(그래픽 사용자 인터페이스)의 설계 및 기능에 있어 중요한 변화를 가져왔습니다. 최첨단 Immersed Boundary Method는 FLOW-3Dv12.0솔루션의 정확도를 높여 줍니다. 다른 특징적인 주요 개발에는 슬러지 안착 모델, 2-유체 2-온도 모델, 사용자가 자유 표면 흐름을 훨씬 더 빠르게 모델링 할 수 있는 Steady State Accelerator등이 있습니다.

물리 및 수치 모델

Immersed Boundary Method

힘과 에너지 손실에 대한 정확한 예측은 솔리드 바디 주변의 흐름과 관련된 많은 엔지니어링 문제를 모델링하는 데 중요합니다. FLOW-3D v12.0의 릴리스에는 이러한 문제 해결을 위해 설계된 새로운 고스트 셀 기반 Immersed Boundary Method (IBM)가 포함되어 있습니다. IBM은 내부 및 외부 흐름을 위해 벽 근처 해석을 위해 보다 정확한 솔루션을 제공하여 드래그 앤 리프트 힘의 계산을 개선합니다.

Two-field temperature for the two-fluid model

2유체 열 전달 모델은 각 유체에 대한 에너지 전달 공식을 분리하도록 확장되었습니다. 이제 각 유체에는 고유한 온도 변수가 있어 인터페이스 근처의 열 및 물질 전달 솔루션의 정확도를 향상시킵니다. 인터페이스에서의 열 전달은 시간의 표 함수가 될 수 있는 사용자 정의 열 전달 계수에 의해 제어됩니다.

슬러지 침전 모델 / Sludge settling model

중요 추가 기능인 새로운 슬러지 침전 모델은 도시 수처리 시설물 응용 분야에 사용하면 수처리 탱크 및 정화기의 고형 폐기물 역학을 모델링 할 수 있습니다. 침전 속도가 확산된 위상의 방울 크기에 대한 함수인 드리프트-플럭스 모델과 달리, 침전 속도는 슬러지 농도의 함수이며 기능적인 형태와 표 형태로 모두 입력 할 수 있습니다.

Steady-state accelerator for free surface flows

이름이 암시하듯이, 정상 상태 가속기는 안정된 상태의 솔루션에 대한 접근을 가속화합니다. 이는 작은 진폭의 중력과 모세관 현상을 감쇠하여 이루어지며 자유 표면 흐름에만 적용됩니다.

꾸준한 상태 가속기

Void particles

보이드 입자가 버블 및 위상 변경 모델에 추가되었습니다. 보이드 입자는 항력과 압력 힘을 통해 유체와 상호 작용하는 작은 기포의 역할을 하는 붕괴된 보이드 영역을 나타냅니다. 주변 유체 압력에 따라 크기가 변경되고 시뮬레이션이 끝난 후 최종 위치는 공기 침투 가능성을 나타냅니다.

Sediment scour model

침전물의 정확성과 안정성을 향상시키기 위해 침전물의 운반과 침식 모델을 정밀 조사하였다. 특히, 침전물 종에 대한 질량 보존이 크게 개선되었습니다.

Outflow pressure boundary condition

고정 압력 경계 조건에는 이제 압력 및 유체 비율을 제외한 모든 유량이 해당 경계의 상류에 있는 흐름 조건을 반영하는 ‘유출’ 옵션이 포함됩니다. 유출 압력 경계 조건은 고정 압력 및 연속성 경계 조건의 혼합입니다.

Moving particle sources

시뮬레이션 중에 입자 소스는 이동할 수 있습니다. 시간에 따른 변환 및 회전 속도는 표 형식으로 정의됩니다. 입자 소스의 운동은 소스에서 방출 된 입자의 초기 속도에 추가됩니다.

Variable center of gravity

중력 및 비 관성 기준 프레임 모델에서 시간 함수로서의 무게 중심의 위치는 외부 파일의 표로 정의할 수 있습니다. 이 기능은 연료를 소모하는 로켓을 모델링하고 단계를 분리할 때 유용합니다.

공기 유입 모델

가장 간단한 부피 기반 공기 유입 모델 옵션이 기존 질량 기반 모델로 대체되었습니다.  질량 기반 모델은 부피와 달리 주변 유체 압력에 따라 부피가 변화하는 동안 흡입된 공기량이 보존되기 때문에 물리학적 모델입니다.

Air entrainment model in FLOW-3D v12.0

Tracer diffusion / 트레이서 확산

유동 표면에서 생성된 추적 물질은 분자 및 난류 확산 과정에 의해 확산될 수 있으며, 예를 들어 실제 오염 물질의 거동을 모방합니다.

모델 설정

시뮬레이션 단위

이제 온도를 포함하여 단위계 시스템을 완전히 정의해야 합니다. 표준 단위 시스템이 제공됩니다. 또한 사용자는 선택한 옵션에서 질량, 시간 및 길이 단위를 정의하여 편리하며, 사용자 정의된 단위를 사용할 수 있습니다. 사용자는 또한 압력이 게이지 단위로 정의되는지 절대 단위로 정의되는지 여부를 지정해야 합니다. 기본 시뮬레이션 단위는 Preferences(기본 설정)에서 설정할 수 있습니다. 단위를 완벽하게 정의하면 FLOW-3D는 물리적 수량에 대한 기본 값을 정의하고 범용 상수를 설정할 수 있으므로 사용자가 필요로 하는 작업량을 최소화할 수 있습니다.

Shallow water model

얕은 물 모델에서 매닝의 거칠기

Manning의 거칠기 계수는 지형 표면의 전단 응력 평가를 위해 얕은 물 모델에서 구현되었습니다. 표면 결함의 크기를 기반으로 기존 거칠기 모델을 보완하며이 모델과 함께 사용할 수 있습니다. 표준 거칠기와 마찬가지로 매닝 계수는 구성 요소 또는 하위 구성 요소의 속성이거나 지형 래스터 데이터 세트에서 가져올 수 있습니다.

메시 생성

하단 및 상단 경계 좌표의 정의만으로 수직 방향의 메시 설정이 단순화되었습니다.

구성 요소 변환

사용자는 이제 여러 하위 구성 요소로 구성된 구성 요소에 회전, 변환 및 스케일링 변환을 적용하여 복잡한 형상 어셈블리 설정 프로세스를 단순화 할 수 있습니다. GMO (General Moving Object) 구성 요소의 경우, 이러한 변환을 구성 요소의 대칭 축과 정렬되도록 신체에 맞는 좌표계에 적용 할 수 있습니다.

런타임시 스레드 수 변경

시뮬레이션 중에 솔버가 사용하는 스레드 수를 변경하는 기능이 런타임 옵션 대화 상자에 추가되어 사용 가능한 스레드를 추가하거나 다른 태스크에 자원이 필요한 경우 스레드 수를 줄일 수 있습니다.

프로브 제어 열원

활성 시뮬레이션 제어가 형상 구성 요소와 관련된 heat sources로 확장되었습니다.  history probes로 열 방출을 제어 할 수 있습니다.

소스에서 시간에 따른 온도

질량 및 질량/모멘트 소스의 유체 온도는 이제 테이블 입력을 사용하여 시간의 함수로 정의 할 수 있습니다.

방사율 계수

공극으로의 복사 열 전달을위한 방사율 계수는 이제 사용자가 방사율과 스테판-볼츠만 상수를 지정하도록 요구하지 않고 직접 정의됩니다. 후자는 이제 단위 시스템을 기반으로 솔버에 의해 자동으로 설정됩니다.

Output

  • 등속 필드 솔버 옵션을 사용할 때 유량 속도를 선택한 데이터로 출력 할 수 있습니다.
  • 벽 접착력으로 인한 지오메트리 구성 요소의 토크는 기존 벽 접착력 출력과 함께 별도의 수량으로 일반 이력 데이터에 출력됩니다.
  • 난류 모델 출력이 요청 될 때 난류 에너지 및 소산과 함께 전단 속도 및 y +가 선택된 데이터로 자동 출력됩니다.
  • 공기 유입 모델 출력에 몇 가지 수량이 추가되었습니다. 자유 표면을 포함하는 모든 셀에서 혼입 된 공기 및 빠져 나가는 공기의 체적 플럭스가 재시작 및 선택된 데이터로 출력되어 사용자에게 공기가 혼입 및 탈선되는 위치 및 시간에 대한 자세한 정보를 제공합니다. 전체 계산 영역 및 각 샘플링 볼륨 에 대해이 두 수량의 시간 및 공간 통합 등가물이 일반 히스토리 로 출력됩니다.
  • 솔버의 출력 파일 flsgrf 의 최종 크기는 시뮬레이션이 끝날 때 보고됩니다.
  • 2 유체 시뮬레이션의 경우, 기존의 출력 수량 유체 체류 시간 및 유체 가 이동 한 거리는 이제 유체 # 1 및 # 2와 유체의 혼합물에 대해 별도로 계산됩니다.
  • 질량 입자의 경우, 각 종의 총 부피 및 질량이 계산되어 전체 계산 영역, 샘플링 볼륨 및 플럭스 표면에 대한 일반 히스토리 로 출력되어 입자 종 수에 대한 현재 출력을 보완합니다.
  • 최종 로컬 가스 압력 은 사용자가 가스 포획을 식별하고 연료 탱크의 배기 시스템 설계를 지원하는 데 도움이되는 선택적 출력량으로 추가되었습니다. 이 양은 유체로 채워지기 전에 셀의 마지막 공극 압력을 기록하며 단열 버블 모델과 함께 사용됩니다.

새로운 맞춤형 소스 루틴

새로운 사용자 정의 가능 소스 루틴이 추가되었으며 사용자의 개발 환경에서 액세스 할 수 있습니다.

소스 루틴 이름기술
cav_prod_calCavitation 생성과 소산 비율
sldg_uset슬러지 침전 속도
phchg_mass_flux증발 및 응축으로 인한 질량 플럭스
flhtccl유체 # 1과 # 2 사이의 열전달 계수
dsize_cal2 상 흐름에서 동적 액적 크기 모델의 응집 및 분해 속도
elstc_custom점탄성 유체에 대한 응력 방정식의 Source Terms

새로운 사용자 인터페이스

FLOW-3D 사용자 인터페이스는 완전히 새롭게 디자인되어 현대적이고 평평한 구조로 사용자의 작업 흐름을 획기적으로 간소화합니다.

Setup dock widgets

Physics, Fluids, Mesh 및 FAVOR ™를 포함한 모든 설정 작업이 지오 메트리 윈도우 주변에서 독 위젯으로 변환되어 모델 설정을 단일 탭으로 요약할 수 있습니다. 이러한 전환으로 인해 이전 버전의 복잡한 접이식 트리가 훨씬 깨끗하고 효율적인 메뉴 프레젠테이션으로 대체되어 사용자는 ModelSetup탭을 떠나지 않고도 모든 매개 변수에 쉽게 액세스 할 수 있습니다.

New Model Setup icons

새로운 모델 설정 디자인에는 설정 프로세스의 각 단계를 나타내는 새로운 아이콘이 있습니다.

Model setup icons - FLOW-3D v12.0

New Physics icons

RSS feed

새 RSS 피드부터 FLOW-3D v12.0의 시뮬레이션 관리자 탭이 개선되었습니다. FLOW-3D 를 시작하면 사용자에게 Flow Science의 최신 뉴스, 이벤트 및 블로그 게시물이 표시됩니다.

RSS feed - FLOW-3D

Configurable simulation monitor

시뮬레이션을 실행할 때 중요한 작업은 모니터링입니다. FLOW-3Dv1.0에서는 사용자가 시뮬레이션을 더 잘 모니터링할 수 있도록 SimulationManager의 플로팅 기능이 향상되었습니다. 사용자는 시뮬레이션 런타임 그래프를 통해 모니터링할 사용 가능한 모든 일반 기록 데이터 변수를 선택하고 각 그래프에 여러 변수를 추가할 수 있습니다. 이제 런타임에서 사용할 수 있는 일반 기록 데이터는 다음과 같습니다.

  • 최소/최대 유체 온도
  • 프로브 위치의 온도
  • 유동 표면 위치에서의 유량
  • 시뮬레이션 진단(예:시간 단계, 안정성 한계)
출입문에 유동 표면이 있는 대형 댐
Runtime plots of the flow rate at the gates of the large dam

Conforming 메쉬 시각화

사용자는 이제 새로운 FAVOR ™ 독 위젯을 통해 적합한 메쉬 블록을 시각화 할 수 있습니다.Visualize conforming mesh blocks

Large raster and STL data

데이터를 처리하는 데 걸리는 시간 때문에 큰 지오 메트리 데이터를 처리하는 것은 수고스러울 수 있습니다. 대형 지오 메트리 데이터를 처리하는 데는 여전히 상당한 시간이 걸릴 수 있지만, FLOW-3D는 이제 이러한 대규모 데이터 세트를 백그라운드 작업으로 로드하여 사용자가 데이터를 처리하는 동안 완전히 응답하고 중단 없는 인터페이스에서 작업을 계속할 수 있습니다

[FLOW-3D 물리모델]General Moving Objects / 일반이동물체

General Moving Objects / 일반이동물체

Basics / 기초

The general moving objects (GMO) model in FLOW-3D can simulate rigid body motion, which is either userprescribed (prescribed motion) or dynamically coupled with fluid flow (coupled motion). If an object’s motion is prescribed, fluid flow is affected by the object’s motion, but the object’s motion is not affected by fluid flow. If an object has coupled motion, however, the object’s motion and fluid flow are coupled dynamically and affect each other. In both cases, a moving object can possess six degrees of freedom (DOF), or rotate about a fixed point or a fixed axis. The GMO model allows the location of the fixed point or axis to be arbitrary (it can be inside or outside the object and the computational domain), but the fixed axis must be parallel to one of the three coordinate axes of the space reference system. In one simulation, multiple moving objects with independent motion types can exist (the total number of moving and non-moving components cannot exceed 500). Any object under coupled motion can undergo simultaneous collisions with other moving and non-moving objects and wall and symmetry mesh boundaries (See Collision). The model also allows the existence of multiple (up to 100) elastic linear and torsion springs, elastic ropes and mooring lines which are attached to moving objects and apply forces or torques to them (See Elastic Springs & Ropes and Mooring Lines).

FLOW-3D에서 일반 이동물체인 GMO 모델은 강체운동을 모사(simulate)할 수 있는데, 이는 사용자가 기술하는 운동(지정운동)이거나 유체 유동과 동력학적인(결합된) 운동일 수 있다. 물체의 운동이 지정되면 유체 유동은 이 운동에 의해 영향을 받으나, 물체의 운동은 유체에 의해 영향을 받지 않는다. 그러나 물체가 결합된 운동을 하면 물체와 유체는 동역학적으로 연결되어 서로 영향을 미친다.

이 두 경우에 물체는6 자유도 운동을 할 수 있고, 고정된 점이나 축에 대해 회전할 수가 있다. GMO모델은 고정점이나 고정축의 위치를 임의로 설정할 수 있으나(이는 물체나 계산영역의 내부 또는 외부가 될 수 있다) 고정축은 공간좌표계의 좌표중의 하나에 평행하여야 한다.

어떤 모사(simulate)에서 고유의 운동형태를 갖는 다수의 운동물체가 존재할 수 있다(이동 및 고정된 물체의 전체수는500개를 초과하지 못한다). 결합운동을 하는 물체는 다른 이동/비이동 물체 그리고 벽과 대칭 경계 격자면에서 충돌할 수가 있다(충돌참조). 이 모델은 (100개까지) 다수의 탄성선형과 비틀림 스프링, 탄성로프와 이동 물체에 부착된 탄성력과 회전력을 갖는 계류선들을 표현할 수 있다(Elastic Springs & Ropes 와 Mooring Lines참조). .

In general, the motion of a rigid body can be described with six velocity components: three for translation and three for rotation. In the most general cases of coupled motion, all the available velocity components are coupled with fluid flow. However, the velocity components can also be partially prescribed and partially coupled in complex coupledmotion problems (e.g., a ship in a stream can have its pitch, roll and heave to be coupled but yaw, sway and surge prescribed). For coupled motion only, in addition to the hydraulic, gravitational, inertial and spring forces and torques which are calculated by the code, additional control forces can be prescribed by the user. The control forces can be defined either as up to five forces with their application points fixed on the object or as a net control force and torque. The net control force is applied to the GMO’s mass center, while the control torque is applied about the mass center for 6-DOF motion, and about the fixed point or fixed axis for those kinds of motions. The inertial force and torque exist only if the Non-inertial Reference Frame model is activated.

일반적으로 강체의 운동은 6개의 속도 성분으로 기술될 수 있다: 3개의 이동과3개의 회전. 가장 일반적인 결합 운동의 경우에, 모든 가능한 속도성분들은 유동과 연결되어 있다. 그러나 속도 성분들은 복잡한 결합운동 문제에서는 부분적으로 지정되고 일부는 결합될 수 있다(즉 유속내의 선박에서 pitch, roll and heave는 결합된 운동을 하고 yaw, sway and surge 는 지정될 수있다). 단 결합운동 문제에서는 코드 내에서 계산되는 수력, 중력, 관성 그리고 스프링 힘과 토크에 추가적인 조절할 수 있는 힘(control force) 들이 사용자에 의해 기술될 수 있다. 조절 힘(control force)들은 물체의 지정된 위치에 작용하는5개까지의 힘이나 또는 순수 힘과 토크로 정의 될 수 있다. 순수 조절힘은 GMO의 질량 중심에 작용하지만, 조절토크는6 자유도 운동의 질량중심에 대해 이런 운동을 하기 위한 고정축이나 점들에 대해 적용된다. 관성력과 토크는 단지 비 관성계 모델이 활성화되면 존재한다.

In FLOW-3D, a GMO is classified as a geometry component that is either porous or non-porous. As with stationary components, a GMO can be composed of a number of geometry subcomponents. Each subcomponent can be defined either by quadratic functions and primitives, or by STL data, and can be solid, hole or complement. If STL files are used, since GMO geometry is re-generated at every time step in the computation, the user should strive to minimize the number of triangle facets used to define the GMO to achieve faster execution of the solver while maintaining the necessary level of the geometry resolution. For mass properties, different subcomponents of an object can possess different mass densities.

FLOW-3D 에서 한 개의 GMO 는 다공질 또는 비 다공질의 형상요소로 간주된다. 정지된 구성요소에서와 같이 한 개의 GMO 는 다수의 형상 서브구성요소로 구성될 수 있다. 각 서브구성요소는 2차 함수와 기초 요소 또는 STL 데이터로 정의될 수 있고 고체, 공간 또는 이의 보완일 수 있다. 만약 STL 파일이 사용된다면 GMO 형상은 계산 중에 매 시간에서 재 생성되므로 사용자는 형상 정밀도에 필요한 수준을 유지하는 한편, 빠른 계산을 위해 GMO를 정의하는데 사용되는 삼각면의 수를 줄이려고 노력해야 한다. 질량물성을 위해 한 물체의 다른 서브구성요소는 다른 질량밀도를 가질 수 있다.

In order to define the motion of a GMO and interpret the computational results correctly, the user needs to understand the body-fixed reference system (body system) which is always fixed on the object and experiences the same motion. In the FLOW-3D preprocessor, the body system (x’, y’, z’) is automatically set up for each GMO. The initial directions of its coordinate axes (at t = 0) are the same as those of the space system (x, y, z). The origin of the body system is fixed at the GMO’s reference point which is a point automatically set on each moving object in accordance with the object’s motion type.

GMO 의 운동을 정의하고 계산결과를 정확히 이해하기 위해, 사용자는 항상 물체에 고정되고, 물체와 같은 운동을 하는 물체에, 고정된 기준계(물체계)를 이해할 필요가 있다. FLOW-3D 의 전처리에서 물체계(x’, y’, z’) 가 자동으로 각 GMO 에 대해 설정된다. 좌표축(t = 0에서) 의 초기방향은 공간계(x, y, z) 의 것과 같다. 물체계의 원점은 물체의 이동형상에 일치하는 각 이동체 상에 자동으로 설정된 GMO 의 기준점에 고정되어 있다.

 

The reference point is: 기준점은 다음과 같다.

  • the object’s mass center for the coupled 6-DOF motion;

결합된6자유도 운동의 질량중심

  • the fixed point for the fixed-point motion;

고정점 운동을 위한 고정점

  • a point on the fixed axis for the fixed-axis rotation;

고정축 회전을 위한 고정축 상의 점

  • a user-defined reference point for the prescribed 6-DOF motion.

기술된6자유도 운동을 위한 사용자 지정의 기준점

  • If the reference point is not given by users for the prescribed 6-DOF motion, it is set by the code at the mass center (if mass properties are given) or the geometry center (if mass properties are not given) of the object.

기준점이 기술된6자유도 운동을 위해 사용자가 지정하지 않으면 코드에 의해 질량중심 (질량물성이 주어지면) 또는 형상중심(질량물성이 안 주어지면)에 지정된다.

 

The GMO’s motion can be defined through the GUI using four steps:

GMO 운동은 4단계를 거쳐 GUI 를통하여 정의될수있다.

  1. Activate the GMO model;

GMO 모델을 활성화한다

  1. Create the GMO’s initial geometry;

GMO의 초기형상을 생성한다

  1. Specify the GMO’s motion-related parameters, and

GMO의 운동관련 변수들을 지정하고.

  1. Define the GMO’s mass properties.

GMO 질량물성을 정의한다

Without the activation of the GMO model in step 1, the object created as a GMO will be treated as a non-moving object, even if steps 2 to 4 are accomplished.

1단계의 GMO 모델 활성화가 없으면 2~4의 단계가 이루어져도 GMO 로 생성된 물체는 비 이동 물체로 간주될 것이다.

Step 1: Activate the GMO Model GMO 모델활성화

To activate the GMO model, go to Model Setup Physics Moving and simple deforming objects and check the Activate general moving objects (GMO) model box.

GMO 모델을 활성화하기 위해 Model Setup Physics Moving and simple deforming objects 로 가서 Activate general moving objects (GMO) model 박스를 체크한다.

The GMO model has two numerical methods to treat the interaction between fluid and moving objects: an explicit and an implicit method. If no coupled motion exists, the two methods are identical. For coupled motion, the explicit method, in general, works only for heavy GMO problem, i.e., all moving objects under coupled motion have larger mass densities than that of fluid and their added mass is relatively small. The implicit method, however, works for both heavy and light GMO problems. A light GMO problem means at least one of the moving objects under coupled motion has smaller mass densities than that of fluid or their added mass is large. The user may change the selection on the Moving and deforming objects panel or on the Numerics tab Moving object/fluid coupling.

GMO 모델은 유체와 움직이는 물체간의 상호작용을 다루기위해 두 수치해석법을 이용한다: explicit 방법과implicit 방법. 결합 운동이 없으면 두 방법은 동일하다. 결합된 운동에서는 외재적 방법은 일반적으로 무거운 GMO 문제에 사용된다, 즉 결합된 운동을 하는 모든 이동물체는 유체밀도보다 크고 이의 부가질량이 작을 경우이다. 그러나 내재적 방법은 무겁거나 가벼운 GMO 문제에 모두 사용된다. 가벼운 GMO 문제는 결합운동 시에 최소한 하나의 이동물체가 유체밀도보다 작고 이의 부가질량이 클 경우이다. 사용자는 Moving and deforming objects패널이나 Numerics tab Moving object/fluid coupling 상에서 선택을 바꿀 수 있다.

  1. Step 2: Create the GMO’s Initial Geometry GMO의 초기형상을 생성한다

 

In the Meshing & Geometry tab, create the desired geometry for the GMO components using either primitives and/or imported STL files in the same way as is done for any stationary component. The component can be either standard or porous. To set up a porous component, refer to Porous Media. Note that the Copy function cannot be used with geometry components representing GMOs.

정지상태의 구성요소 생성의 경우와 마찬가지로 Meshing & Geometry 탭에서 기초 요소와/또는 외부로부터의 STL 파일을 이용하여 GMO 구성요소의 원하는 형상을 생성한다. 구성요소는 standard이거나porous일 수 있다. 다공성요소를 설정하기 위해 Porous Media 를 참조하라. Copy 기능은 GMO를 나타내는 형상 구성요소에 사용할 수 없음에 주목한다.

Step 3: Specify the GMO’s Motion Related Parameters GMO의 운동관련변수들을 지정한다

The following section discusses how to set up parameters for prescribed and coupled 6-DOF motion, fixed-point motion and fixed-axis motion. The user can go directly to the appropriate part.

다음 섹션은 “지정되고 결합된 6자유도운동”, “고정점 운동과 고정축 운동을 위한 매개변수를 어떻게 설정하는지”에 대해 논한다. 사용자는 직접 해당부분을 참조할 수 있다.

Prescribed 6-DOF Motion 지정된 6자유도운동

In Meshing & Geometry Geometry Component (the desired GMO component) Type of Moving Object, select Prescribed motion. Go to Component Properties Type of Moving Object Moving Object Properties Edit Motion Constraints. Under Type of Constraint, select 6 Degrees of Freedom in the combo box.

Meshing & Geometry Geometry Component (the desired GMO component) Type of Moving Object 에서 Prescribed motion 을 선택한다. Component Properties Type of Moving Object Moving Object Properties Edit Motion Constraints 로 가서 Type of Constraint 밑에서 combo 박스에 있는 6 Degrees of Freedom 를 선택한다.

To define the object’s velocity, go to the Initial/Prescribed Velocities tab in the Moving object setup window. The prescribed 6-DOF motion is described as a superimposition of a translation of a reference point and a rotation about the reference point. The reference point can be anywhere inside or outside the moving object and the computational domain. The user needs to enter its initial x, y and z coordinates (at t = 0) in the provided edit boxes. By default, the reference point is determined by the preprocessor in two different ways depending on whether the object’s mass properties are given: if mass properties (either mass density or integrated mass properties) are given, then the mass center of the moving object is used as the reference point; otherwise, the object’s geometric center will be calculated and used as the reference point.

물체의 속도를 정의하기 위해 Moving object setup 의 창에 있는 Initial/Prescribed Velocities 탭으로 이동한다. 지정된 6자유도 운동은 기준점의 이동과 기준점에 대한 회전의 중첩으로 기술된다. 기준점은 이동체의 내부 또는 외부 그리고 계산영역 외부일 수도 있다. 사용자는 주어진 편집박스 내에 이의 초기 x, y 와 z 좌표값(t = 0에서)을 입력할 필요가 있다. 디폴트로 기준점은 물체의 질량 물성이 주어지는가에 따라 두 가지로 전처리 과정에서 결정된다: 질량물성(질량밀도나 전체질량물성)이 주어지면 이동체의 질량중심이 기준점으로 사용되고 아니면 이동체의 형상중심이 계산되고 기준점으로 이용된다.

With the reference point provided (or left for the code to calculate), users can define the translational velocity components for the reference point in space system and the angular velocity components (in radians/time) in body system. Each velocity component can be defined either as a sinusoidal or a piecewise linear function of time by making a selection in the corresponding combo box. For a constant velocity component, choose Non-Sinusoidal and simply enter its value in the corresponding input box (the default value is 0.0). If a velocity component is Non-sinusoidal and time-dependent, click on the corresponding Tabular button to open a data table and enter values for the velocity component and time. Alternatively, the user can also import a data file for the velocity component versus time by clicking Tabular Import Values. The file must have two columns of data which represent time and velocity from left to right and must have a csv extension. If the velocity component is sinusoidal in time, then enter the values for Amplitude, Frequency (in Hz) and Initial Phase (in degrees) in the input boxes.

기준점이 주어지면(또는 코드 내에서 계산이 되면) 사용자는 공간계 기준점에 대해 translational velocity components 를 그리고 물체계에서angular velocity components (radians/시간으로)를 정의할 수 있다. 각 속도 성분은 상응하는 combo box 에서 선택함으로써 사인파 또는 구간적 시간함수로써 정의될 수 있다. 일정 속도 성분에 대해서 Non-Sinusoidal 을 선택하고 단순히 상응하는 combo 박스에 값을 넣는다(디폴트 값은0이다). 속도성분이 Non-Sinusoidal 이고 시간의 함수이면 데이터 테이블을 열고 상응하는 Tabular 버튼을 클릭하고 속도성분과 시간을 넣는다. 다른 방법으로는 사용자가 Tabular Import Values를 클릭함으로써 속도성분대 시간의 데이터파일을 읽어 들일 수가 있다. 이 파일은 시간과 속도를 나타내는 좌로부터 우로의 두 데이터 열이 있어야 하며 csv 확장자를 가져야 한다. 속도 성분이 시간에 따른 사인파이면 입력박스에서의 Amplitude, Frequency (in Hz) 그리고 Initial Phase (in degrees) 값을 입력한다.

The expression for the sinusoidal velocity component is

사인파 속도의 식은

v = Asin(2πft + ϕ0)

where: 여기서

  • A is the amplitude, 진폭
  • f is the frequency, and주기이며
  • ϕ0 is the initial phase. 초기위상이다.
  •  
  • Users can set limits for the translational displacements of the object’s reference point in both negative and positive x, y and z directions in space system. The displacements are measured from the initial location of the reference point. During motion, the reference point cannot go beyond these limits but can move back to the allowed range after it reaches a limit. To set the limits for translation, go to the Motion Constraints tab and enter the maximum displacements allowed in the corresponding input boxes, using absolute values. By default, these values are infinite. Note the Limits for rotation is only for fixed-axis rotation thus cannot be set for 6-DOF motion.사용자는 공간계에서 음이나 양의 x, y 그리고 z 방향으로 물체 기준점의 이동변위를 제한할 수 있다. 변위는 기준점의 초기위치로부터 정해진다. 운동중에 기준점은 이 제한을 넘어갈 수 없지만 이 제한에 도달한 후에 허용된 범위만큼 돌아올 수 있다. 이동의 제한을 설정하기 위해 Motion Constraints 탭으로가서 절대값을 사용하여 상응하는 입력박스 안에 허용된 최대변위를 넣는다. the Limits for rotation 는 고정축 회전에만 해당하므로 6자유도 운동에는 지정될 수 없다.Prescribed Fixed-point Motion지정된 고정점운동In Meshing & Geometry Geometry Component (the desired GMO component) Component Properties Type of Moving Object, select Prescribed motion. Go to Moving object properties Edit Motion Constraints. Under Type of Constraint, select Fixed point rotation in the combo box and enter the x, y and z coordinates of the fixed point in the corresponding input boxes.Meshing & Geometry Geometry Component (the desired GMO component) Component Properties Type of Moving Object 에서 Prescribed motion 을 선택한다. Moving object properties Edit Motion Constraints 로 가서 Type of Constraint 밑에서 combo box 에있는 Fixed point rotation을 선택하고 상응하는 입력박스에서 고정점의 the x, y 및 z 좌표를 입력한다.To define the velocity of the object, go to the Initial/Prescribed Velocities tab in the Moving object setup window. The velocity components to be defined are the x, y and z components of the angular velocity (in radians/time) in the body system. Each velocity component can be defined as either a sinusoidal or a piecewise linear function of time by making a selection in the corresponding combo box. For a constant velocity component, choose Non-Sinusoidal and simply enter its value in its input box (the default value is 0.0). If a velocity component is time-variant and Non-sinusoidal, click on the Tabular button to open a data table and enter the values for the velocity component and time. Alternatively, the user can also import a data file for the velocity component versus time by clicking Tabular Import Values. The file must have two columns of data which represent time and velocity component from left to right and must have a csv extension. If the velocity component is sinusoidal in time, then enter the values for Amplitude, Frequency (in cycles/time) and Initial Phase (in degrees) in the corresponding input boxes.

    물체의 속도를 정의하기 위해 Moving object setup 의 창에 있는 Initial/Prescribed Velocities 탭으로 간다. 정의되어야 할 속도성분은 물체계에서 각속도  (radians/시간으로) 를 x, y 및 z 성분으로 정의할 수 있다

    각 속도 성분은 상응하는 combo box 에서 사인파 또는 구간적 시간함수로써 정의될 수 있다.

    일정속도 성분에 대해서 Non-Sinusoidal 을 선택하고 단순히 상응하는 combo box 박스에 값을 넣는다(디폴트 값은0이다). 속도성분이 Non-Sinusoidal 이고 시간의 함수이면 데이터 테이블을 열고 상응하는 Tabular 버튼을 클릭하고 속도성분과 시간을 넣는다. 그렇지 않으면 사용자가 Tabular Import Values 를 클릭함으로써 속도성분대 시간의 데이터 파일을 읽어 들일 수가 있다. 이 파일은 시간과 속도를 나타내는 좌로부터 우로의 두 데이터 열이 있어야 하며 csv 확장자를 가져야 한다. 속도성분이 시간에 따른 사인파이면 상응하는 입력박스에서 Amplitude, Frequency (in Hz) 와 Initial Phase (in degrees) 값을 입력한다.

    The expression for a sinusoidal angular velocity component is

    ω = Asin(2πft + ϕ0)

    where: 여기서

    • A is the amplitude, 진폭
    • f is the frequency, and주기이며
    • ϕ0 is the initial phase. 초기위상이다.

    Prescribed Fixed-Axis Motion

    In Meshing & Geometry Geometry Component (the desired GMO component) Component Properties Type of Moving Object, select Prescribed motion. Go to Moving Object Properties Edit Motion Constraints. Under Type of Constraint, select Fixed X-Axis Rotation or Fixed Y-Axis Rotation or Fixed Z-Axis Rotation in the combo box depending on which coordinate axis the rotational axis is parallel to.

    Meshing & Geometry Geometry Component (the desired GMO component) Component Properties Type of Moving Object 에서 Prescribed motion 을 선택한다. Moving object properties Edit Motion Constraints 로 가서Type of Constraint밑에서 회전축이 어떤 좌표축에 평행인가에 따라 combo box 에있는 Fixed X-Axis Rotation 또는 Fixed Y-Axis Rotation 또는 Fixed Z-Axis Rotation 를 선택한다.

    Coordinates of the rotational axis need be given in two of the three input boxes for Fixed Axis/Point X Coordinate, Fixed Axis/Point Y Coordinate and Fixed Axis/Point Z Coordinate. For example, if the rotational axis is parallel to the z-axis, then the x and y coordinates for the rotational axis must be defined. Users can also set limits for the object’s rotational angle in both positive and negative directions. The rotational angle (i.e., angular displacement) is a vector and measured from the object’s initial orientation based on the right-hand rule. Its value is positive if it points in the positive direction of the coordinate axis which the rotational axis is parallel to. The object cannot rotate beyond these limits but can rotate back to the allowed angular range after it reaches a limit. To set the limits for rotation, in Motion Constraints Limits for rotation, enter the Maximum rotational angle allowed in negative and positive directions in the corresponding input boxes, using absolute values in degrees. By default, these values are infinite.

    회전축 좌표는 3개 Fixed Axis/Point X Coordinate, Fixed Axis/Point Y Coordinate Fixed Axis/Point Z Coordinate 중 2개의 입력박스에서 주어져야 한다. 예를 들면 회전축이 z 축에 평행 하다면 이 회전축의 the x 와 y 좌표가 정의 되어야 한다. 사용자는 물체의 양음 방향의 회전각도를 제한할 수 있다. 회전각 (즉, 각변위)은 벡터이며 오른손 법칙에 따른 물체의 초기 방향으로부터 측정된다. 이는 회전축에 평행한 좌표축의 양방향을 가리키면 양의 값이다. 물체는 제한 값을 지나 회전할 수 없지만 이 값에 도달한 후 허용된 각변위로 되돌아갈 수 있다. 회전의 제한을 설정하기 위해 Motion Constraints Limits for rotation 내에서 상응하는 입력박스에서 음이나 양의방향으로 허용된 Maximum rotational angle 을 입력한다. 이의 디폴트 값은 무한대이다.

To define the angular velocity of an object (in radians/time), go to Initial/Prescribed Velocities. The angular velocity can be defined either as a sinusoidal or a piecewise linear function of time by making a selection in the corresponding combo box. For a constant angular velocity, choose Non-Sinusoidal and simply enter its value in its input box (the default value is 0.0). If it is Non-sinusoidal in time, click on the corresponding Tabular button to open a data table and enter the values for the angular velocity and time. Alternatively, the user can also import a data file for the velocity component versus time by clicking Tabular Import Values. The file must have two columns of data which represent time and angular velocity from left to right and must have a csv extension. If the angular velocity is sinusoidal in time, then enter the values for Amplitude, Frequency (in cycles/time) and Initial Phase (in degrees) in the corresponding input boxes.

물체의 각속도(radians/시간으로)를 정의하기 위해 Initial/Prescribed Velocities 탭으로 간다. 각속도는 상응하는 combo box 에서 사인파 또는 구간적 시간함수로써 정의될 수 있다. 일정 각속도에 대해서 Non-Sinusoidal 을 선택하고, 이에 상응하는 combo box 에 단순히 값을 넣는다(디폴트 값은0.0이다). 이것이 Non-Sinusoidal 이고 시간의 함수이면 데이터 테이블을 불러와, 상응하는 Tabular 버튼을 클릭하고 각속도와 시간을 넣는다. 그렇지 않으면 사용자가 Tabular Import Values 를 클릭함으로써 속도 성분대 시간의 데이터 파일을 읽어 들일 수가 있다. 이 파일은 시간과 각속도를 나타내는 좌로부터 우로의 두 데이터 열이 있어야 하며 csv 확장자를 가져야 한다. 각속도가 시간에 따른 사인파이면 입력박스에서의 Amplitude, Frequency (in Hz) 그리고 Initial Phase (in degrees) 값을 입력한다.

 

The expression for a sinusoidal angular velocity is사인파 각속도식은

ω = Asin(2πft + ϕ0)

where: 여기서

  • A is the amplitude, 진폭
  • f is the frequency, and주기이며
  • ϕ0 is the initial phase. 초기위상이다.

Coupled 6-DOF motion 결합된 6자유도운동

In Meshing & Geometry → Geometry → Component (the desired GMO component) → Component Properties → Type of Moving Object, select Coupled motion. Go to Moving Object Properties → Edit → Motion Constraints. Under Type of Constraint, select 6 Degrees of Freedom in the combo box.

Meshing & Geometry → Geometry → Component (the desired GMO component) → Type of Moving Object 에서 Coupled motion 을 선택한다. Moving Object Properties → Edit → Motion Constraints 로가서 Type of Constraint 밑에서 combo 박스에 있는 6 Degrees of Freedom 를 선택한다.

 

Users need to define the initial velocities for the object. Go to the Initial/Prescribed Velocities tab. Enter the x, y, and z components of the initial velocity of the GMO’s mass center in X Initial Velocity, Y Initial Velocity and Z Initial Velocity, respectively. Enter the x’, y’ and z’ components of the initial angular velocity (in radians/time) in the body system in X Initial Angular Velocity, Y Initial Angular Velocity and Z Initial Angular Velocity, respectively. By default, the initial velocity components are zero.

사용자는 물체에 대한 초기속도를 정의해야 한다. Initial/Prescribed Velocities 탭으로 간다. 각 X Initial Velocity, Y Initial Velocity 그리고 Z Initial Velocity 로 GMO 질량중심의 초기속도의 x, y 와 z 성분값(t = 0에서)을 입력한다. 물체 계에서의 X Initial Angular Velocity, Y Initial Angular Velocity 그리고 Z Initial Angular Velocity (radians/시간으로)로 초기 각속도의 x’, y’ 및 z’ 성분값을 입력한다.

 

For coupled 6-DOF motion, user-prescribed control force(s) and torque exerting on the object can be defined either in the space system or the body system. They are combined with the hydraulic, gravitational, inertial and spring forces and torques to determine the object’s motion. There are two different ways to define control force(s) and torque: prescribe either a total force and a total torque about the object’s mass center or multiple forces with their application points fixed on the object. By default, all the control force(s) and torque are equal to zero.

결합된6자유도운동에서 물체에 미치는 사용자 지정 조절 힘과 토크는 물체계 또는 공간계에서 정의될 수 있다. 이들은 물체의 운동을 결정하는 수력, 중력, 관성력 스프링 힘 그리고 토크이다. 이 조절 힘과 토크를 정의하는 두 가지 방법이 있다: 물체의 질량중심에 대한 전체의 힘과 토크를 지정하거나 물체에 고정된 점들에 작용하는 다수의 힘들을 지정하는 것이다. 디폴트는 모든 조절 힘과 토크가0이다.

To prescribe total force and total torque, in the Control Forces and Torques tab, choose Define Total Force and Total Torque in the combo box. Further select In Space System or In Body System depending on which reference system the control force and torque are define in. If a component of the force or the torque is a constant, it can be specified in the corresponding edit box (default is zero). If it varies with time, then click on the Tabular button to bring up a data input table and enter the values for the component and time. The time-variant force and torque are treated as piecewise-linear functions of time during simulation. Alternatively, instead of filling the data table line by line, the user can also import a data file for the force/torque component versus time by clicking Tabular Import Values. The file must have two columns of data which represent time and the force/torque component from left to right and must have a csv extension.

전체의 힘과 토크를 지정하기 위해 Control Forces and Torques 탭 안의 combo box 에서 Define Total Force and Total Torque 를 선택한다. 추가로 조절 힘과 토크가 정의되는 기준계에 따른 In Space System 이나 In Body System 을 선택한다. 힘 또는 토크의 한 성분이 상수이면 상응하는 편집박스에 지정된다(디폴트는0). 이것이 시간에 따라 변하면 데이터 테이블을 불러오기 위해 상응하는 Tabular 버튼을 클릭하고 성분과 시간 값을 넣는다. 그렇지 않으면 한 줄씩 데이터 테이블을 채우는 대신에 사용자가 Tabular Import Values 를 클릭함으로써 force/torque component versus time 을 읽어 들일 수가 있다. 이 파일은 시간과 힘/토크를 나타내는 좌로부터 우로의 두 데이터 열이 있어야 하며 csv 확장자를 가져야 한다

If, instead, control forces and their application points need to be defined, then in the Control Forces and Torques tab choose Define Multiple Forces and Application Points in the combo box. Users can specify up to five forces. For each force, in the editor boxes, choose the force index (1 to 5) and then select Force components in Space System or Body System depending on which reference system the force is defined in. In field on the left, enter the initial coordinates (at t = 0) for the force’s application point. In the field on the right, prescribe components of the force in x, y and z directions of the body or space system. For a constant force component, enter its value in the corresponding edit box. If it varies with time, then click on the Tabular button to bring up a data input table and enter values for the force component versus time. Tabular force input is approximated with a piecewise-linear function of time. Alternatively, the user can import a data file for the force versus time by clicking Tabular Import Values. The file must have two columns of data which represent time and from left to right and must have a csv extension.

대신에 조절힘과 그 적용점들이 정의되어야 한다면 Control Forces and Torques 탭에서 combo box 안에 있는 Define Multiple Forces and Application Points 를 선택한다. 사용자는5개까지의 힘을 지정할 수 있다. 각 힘에 대해, 편집박스 내에서, force index(1에서 5) 를 선정하고 힘이 정의되는 기준계에 따라 Force components in 에서 Space System Body System 을 선택한다. 좌측 칸에 힘 적용점의 초기좌표(t=0에서)를 입력한다. 우측 칸에 물체 또는 공간계에 따른 x, y 그리고 z 방향에서의 힘의 성분을 넣는다. 힘 성분이 상수이면 그 값을 상응하는 편집박스에서 입력한다. 이것이 시간에 따라 변하면 데이터 테이블을 불러오기 위해 상응하는 Tabular 버튼을 클릭하고 힘성분 대 시간값을 넣는다. 이렇게 입력된 값들은 구간별 선형함수로 근사 된다.  다른 방법으로 사용자가 Tabular Import Values 를 클릭함으로써 힘과 시간에 대한 데이터파일을 읽어 들일 수가 있다. 이파일은 시간과 힘/토크를 나타내는 좌로부터 우로의 두 데이터 열이 있어야 하며 csv 확장자를 가져야 한다.

 

Motion constraints can be imposed to the object to decrease the number of the degrees of freedom to less than six. This selection is made by setting part of its translational and rotational velocity components as Prescribed motion while leaving the other components to coupled motion in Motion Constraints tab Translational and Rotational Options. Note that the translational and rotational components are in the space system and the body system, respectively. Then go to the Initial/Prescribed Velocities tab to define their values. A prescribed velocity component can be defined as either a sinusoidal or piecewise linear function of time in the combo box. For a constant velocity component, choose Non-Sinusoidal and enter its value in its input box (the default value is 0.0). If the velocity component is timedependent and non-sinusoidal, click on the Tabular button to open a data table and enter the values for the velocity component and time. Alternatively, the user can import a data file for the velocity component versus time by clicking Tabular Import values. The file must have two columns of data which represent time and the angular velocity component from left to right and must have a csv extension. It is treated as a piecewise-linear function of time in the code. If it is a sinusoidal function of time, instead, enter its Amplitude, Frequency (in Hz) and Initial Phase (in degrees) in the edit boxes.

6자유도 보다 운동의 자유도를 줄이기 위해 운동의 제약이 물체에 가해질 수 있다. 이 선택은 일부의 이동과 회전속도 성분을 Prescribed motion 으로 다른 성분들은 Motion Constraints tab Translational and Rotational Options 에서 coupled motion 결합운동으로 설정함으로써 이루어진다. 이동과 회전은 각기 공간계와 물체계로 되어있다는 것에 주목한다. 이 때에 Initial/Prescribed Velocities 탭으로 가서 이 값을 정의한다. 지정속도 성분은 상응하는 combo box 에서 사인파 또는 구간적 시간함수로써 정의될 수 있다. 일정속도 성분에 대해서 Non-Sinusoidal 을 선택하고 입력박스에서 값을 넣는다(디폴트 값은0이다). 속도성분이 시간의 함수이고 Non-Sinusoidal 이면 데이터 테이블을 열고 Tabular 버튼을 클릭하고 속도 성분과 시간 값을 넣는다. 다른 방법으로는 사용자가 Tabular Import Values 를 클릭함으로써 속도성분 대 시간의 데이터 파일을 읽어 들일 수가 있다. 이 파일은 좌로부터 우로의 시간과 각속도 성분을 나타내는 두 데이터 열이 있어야 하며 csv 확장자를 가져야 한다. 이렇게 입력된 값들은 코드 내에서 구간별 선형함수로 근사 된다. 대신에 시간의 함수이면 편집박스에서의 Amplitude, Frequency (in Hz) 그리고 Initial Phase (in degrees) 값을 입력한다.

 

The expression for a sinusoidal velocity component is사인파 속도식은

v = Asin(2πft + ϕ0)

where:

  • A is the amplitude, 진폭
  • f is the frequency, and주기이며
  • ϕ0 is the initial phase. 초기위상이다.

Users can also set limits for displacements of the object’s mass center in both negative and positive x, y and z directions in the space system, measured from its initial location. The mass center cannot go beyond these limits but can move back to the allowed motion range after it reaches a limit. To specify these limits, open the Motion Constraints tab and in the Limits for translation area, enter the absolute values of maximum displacements in the desired coordinate directions. There are no Limits for rotation for an object with 6-DOF coupled motion.

사용자는 초기 조건으로부터 측정된 공간계에서의 음이나 양의 x, y 그리고 z 방향으로 물체 질량중심의 변위를 제한할 수 있다. 질량중심은 이 제한을 지나갈 수 없지만 이 제한에 도달한 후에 허용된 범위로 돌아올 수 있다. 이동의 제한을 설정하기 위해 Motion Constraints 탭을 열고 Limits for translation에서 원하는 좌표방향에서의 최대 절대변위 값을 넣는다. 6자유도 운동을 갖는 물체에 대한 Limits for rotation 은 없다.

 

Coupled Fixed-Point Motion 결합된 고정점운동

In Meshing & Geometry Geometry Component (the desired GMO component) Component Properties Type of Moving Object, select Coupled motion. Go to Moving Object Properties Edit Motion Constraints. Under Type of Constraint, select Fixed point rotation in the combo box and enter the x, y and z coordinates of the fixed point in the corresponding input boxes. The Limits for rotation and Limits for translation cannot be set for fixed-point motion.

Meshing & Geometry → Geometry → Component (the desired GMO component) → Component Properties → Type of Moving Object 에서 Coupled motion 을 선택한다. Moving Object Properties → Edit → Motion Constraints 로 가서 Type of Constraint 밑에서 combo 박스에있는 Fixed point rotation 를 선택하고 상응하는 입력 상자 안에 있는 고정점의 x, y 및 z 좌표를 입력한다. Limits for rotation 와 Limits for translation 는 고정점 운동에 대해 선택될 수 없다.

 

Definition of the initial velocity for the object is required. Go to the Initial/Prescribed Velocities tab and enter the x, y and z components of initial angular velocity (in rad/time) in the boxes for X Initial Angular velocity, Y Initial Angular velocity and Z Initial Angular velocity. Their default values are zero.

물체의 초기속도 정의가 필요하다. Initial/Prescribed Velocities 탭으로 가서 X Initial Angular velocity, Y Initial Angular velocity 그리고 Z Initial Angular velocity 를 위한 상자에서 초기 각속도  (rad/시간) 의 the x, y 및 z 성분을 넣는다.

 

Further constraints of motion can be imposed to the object to decrease its number of degrees of freedom. This is done in the Motion Constraints tab by setting part of its rotational components as prescribed motion while leaving the others as coupled motion in the combo box for Translational and rotational options. Note that the rotational components are in the body system. By default, the prescribed velocity components are equal to zero. To specify a non-zero velocity component, go to the Initial/Prescribed Velocities tab. It can be defined as either a sinusoidal or a piecewise linear function of time by making selection in the corresponding combo box. For a constant velocity component, choose Non-Sinusoidal and simply enter its value in the input box (the default value is 0.0). If it is non-sinusoidal timedependent, click on the Tabular button to open a data table and enter the values for the velocity component and time. Alternatively, the user can import a data file for the velocity component versus time by clicking Tabular Import values. The file must have two columns of data which represent time and the angular velocity component from left to right and must have a csv extension. If the velocity component is a sinusoidal function of time, enter the values for Amplitude, Frequency (in Hz) and Initial Phase (in degrees) in the input boxes.

운동의 자유도를 줄이기 위해 운동의 제약이 물체에 가해질 수 있다. 이 선택은 일부의 회전속도 성분을 Prescribed motion 으로 다른 성분들은 Translational and rotational options를 위한 상자에서 coupled motion 으로 Motion Constraints 탭에서 설정함으로써 이루어진다. 회전성분은 물체계로 되어있다는 것에 주목한다. 디폴트로 지정속도 성분들은 0이다. 0이 아닌 속도성분을 지정하기 위해 Initial/Prescribed Velocities탭으로 간다. 지정속도 성분은 상응하는 combo box 에서 사인파 또는 구간적 시간함수로써 정의될 수 있다. 일정속도 성분에 대해서 Non-Sinusoidal 을 선택하고 단순히 입력박스에서 값을 넣는다(디폴트 값은0이다). 속도성분이 시간의 함수이고 Non-Sinusoidal 이면 데이터 테이블을 열고 Tabular 버튼을 클릭하고 속도 성분과 시간 값을 넣는다. 다른 방법으로는   사용자가 Tabular Import Values 를 클릭함으로써 속도 성분 대 시간의 데이터파일을 읽어들일 수 가 있다. 이 파일은 좌로부터 우로의 시간과 각속도 성분을 나타내는 두 데이터 열이 있어야 하며 csv 확장자를 가져야 한다. 속도성분이 사인파의 시간의 함수이면 입력상자에서 Amplitude, Frequency (in Hz) and Initial Phase (in degrees) 값을 넣는다.

The expression for a sinusoidal velocity component is사인파속도성분식은

ω = Asin(2πft + ϕ0)

where: 여기서

  • A is the amplitude진폭,
  • f is the frequency, and주기이며
  • ϕ0 is the initial phase. 초기위상이다

 

User-prescribed total torque exerting on the object can also be defined. They are combined with the hydraulic, gravitational, inertial and spring torques to determine the object’s rotation.

또한 사용자에 의해 지정된 물체에 작용하는 전체 토크가 지정될 수 있다. 이들은 물체의 회전을 결정하기 위해 수력, 중력, 관성력과 스프링에 의한 토크와 결합되어 있다.

In the Control Forces and Torques tab, choose Define Total Force and Total Torque in the combo box. Further, select In Space System or In Body System depending on which reference system the control torque is define in. If the torque is constant, it can be simply set in the provided edit box for its x, y and z components. For a time-dependent control torque, click the Tabular button to bring up data tables and then enter the values of time and the torque components. The control torque is treated as a piecewise-linear function of time. As an option, instead of filling the data table line by line, the user can also import a data file for the angular velocity versus time by clicking Tabular Import Values. The file must have two columns of data which represent time and velocity from left to right and must have a csv extension.

Control Forces and Torques 탭에서 combo box 상자 안의 Define Total Force and Total Torque 를 선택한다. 추가로 조절 토크가 정의되는 기준계에 따른 공간계 In Space System 나 물체계 In Body System 을 선택한다.  토크가 상수이면 its x, y 및 z 성분을 위한 주어진 편집상자에서 지정된다. 이것이   시간에 따라 변하는 조절 토크이면 데이터 테이블을 불러오기 위해 상응하는 Tabular 버튼을 클릭하고 성분과 토크 성분값을 넣는다. 제어토크는 구간 내 시간의 선형함수로 간주된다. 선택으로 한 줄씩 데이터 테이블을 채우는 대신에 사용자가 Tabular Import Values 을 클릭함으로써 각속도 대 시간 읽어 들일 수가 있다. 이 파일은 시간과 속도를 나타내는 좌로부터 우로의 두 데이터 열이 있어야 하며  csv 확장자를 가져야 한다

 

Coupled Fixed-Axis Motion  결합된 고정축운동

In Meshing & Geometry Geometry Component (the desired GMO component) Component Properties Type of Moving Object, select Coupled motion. Go to Moving Object Properties Edit Motion Constraints. Under Type of Constraint, select Fixed X-Axis Rotation or Fixed Y-Axis Rotation or Fixed Z-Axis Rotation in the combo box depending on which coordinate axis the rotational axis is parallel to.

Meshing & Geometry Geometry Component (the desired GMO component) Component Properties Type of Moving Object 에서 Coupled motion 을 선택한다. Moving Object Properties Edit Motion Constraints 로 가서 Type of Constraint 밑에서 회전축이 어느 좌표축과 평행한지에 따라 combo 박스에있는 Fixed X-Axis Rotation또는Fixed Y-Axis Rotation 또는 Fixed Z-Axis Rotation 를 선택한다.

 

Coordinates of the rotational axis need be given in two of the three input boxes for Fixed Axis/Point X Coordinate, Fixed Axis/Point Y Coordinate and Fixed Axis/Point Z Coordinate. For example, if the rotational axis is parallel to the z-axis, then the x and y coordinates for the rotational axis must be defined. Users can also set limits for the object’s rotational angle in both positive and negative directions. The rotational angle (i.e., angular displacement) is a vector and measured from the object’s initial orientation based on the right-hand rule. Its value is positive if it points to the positive direction of the coordinate axis which the rotational axis is parallel to. The object cannot rotate beyond these limits but can rotate back to the allowed angular range after it reaches a limit. To set the limits for rotation, in Motion Constraints Limits for rotation, enter the maximum rotational allowed in negative and positive directions in the corresponding input boxes, using absolute values in degrees. By default, these values are infinite.

회전축좌표는 3개 Fixed Axis/Point X Coordinate, Fixed Axis/Point Y Coordinate Fixed Axis/Point Z Coordinate 중 2개의 입력박스에서 주어져야 한다. 예를들면 회전축이 z 축에 평행하다면 이 회전축의 the x 와 y 좌표가 정의되어야 한다. 사용자는 물체의 양과 음 방향의 회전각도를 제한할 수 있다. 회전각 (즉, 각변위)은 벡터이며 오른손 법칙에 따라 물체의 초기 방향으로 부터 측정된다. 이것이 회전축에 평행한 좌표축의 양방향을 가리키면 양의 값이다. 물체는 제한 값을 지나 회전할 수 없지만 이 값에 도달한 후 허용된 각 변위로 되돌아갈 수 있다. 회전의 제한을 설정하기 위해 Motion Constraints Limits for rotation 내에서 상응하는 입력박스에서 음이나 양의방향으로 허용된 Maximum rotational angle 을 입력한다. 이의 디폴트 값은 무한대이다.

 

A definition of the initial angular velocity for the object is required. In the Initial/Prescribed Velocities tab, enter the initial angular velocity (in radians per time) in x, y or z direction in the corresponding input box in the Angular velocity components area, depending on the orientation of the rotational axis. The default value is zero.

User-prescribed total torque exerting on the object can be defined. They are combined with the hydraulic, gravitational, inertial and spring torques to determine the object’s rotation. In the Control Forces and Torques tab, choose Define Total Force and Total Torque in the combo box. If the torque is constant, it can be simply set in the provided edit box for x, y or z component of the torque, depending on direction of the coordinate axis which the rotational axis is parallel to. For a time-dependent control torque, click the corresponding Tabular button to bring up a data table and then enter the values of time and the torque. The control torque is treated as a piecewise-linear function of time in computation. As an option, instead of filling the data table line by line, the user can also import a data file for the torque versus time by clicking Tabular Import Values. The file must have two columns of data which represent time and torque from left to right and must have a csv extension. The torque about the fixed axis is the same in the space and body systems, thus the choice of In space system or In body system options makes no difference to the computation. User-prescribed total control force and multiple forces are not allowed for the fixed-axis motion.

물체의 초기 각속도 정의가 필요하다. Initial/Prescribed Velocities 탭에서 회전축의 방향에 따라 the Angular velocity components 면에서 x, y 및 z 방향으로 초기 각속도(시간당radians으로)를 넣는다. 디폴트는0이다. 사용자에 의해 지정된 물체에 작용하는 전체 토크가 정의될 수 있다, 이들은 물체의 회전을 결정하기 위해 수력, 중력, 관성력과 스프링에 의한 토크와 결합되어 있다. Control Forces and Torques 탭 안의 combo box 에서 Define Total Force and Total Torque 을 선택한다.  토크가 상수이면 회전축이 평행한 좌표축의 방향에 따라, 토크의 x, y 또는 z 성분을 위한 주어진 편집박스에서 단순히 지정된다. 따라 변하면 데이터테이블을 불러오기 위해 상응하는 Tabular 버튼을 클릭하고 시간과 토크를 넣는다. 제어토크는 계산시 구간 내 시간의 함수로 간주된다. 선택으로 한 줄씩 데이터 테이블을 채우는 대신에 사용자가 Tabular Import Values 를 클릭함으로써 토크대 시간의 파일을 읽어 들일 수 가 있다. 이 파일은 시간과 토크를 나타내는 좌로부터 우로의 두 데이터 열이 있어야 하며 csv 확장자를 가져야 한다. 고정축에 대한 토크는 공간과 시간계에서 같으므로 In space system 이나 In body system 의 선택은 계산에 차이가 없다. 사용자가 지정하는 전체 제어 힘과 다중의 힘은 고정축 운동에서는 허용되지 않는다.

Step 4: Specify the GMO’s Mass Properties GMO 질량물성을 정의한다

Definition of the mass properties is required for any moving object with coupled motion and is optional for objects with prescribed motion. If the mass properties are provided for a prescribed-motion object, the solver will calculate and output the residual control force and torque, which complement the gravitational, hydraulic, spring, inertial and user-prescribed control forces and torques to maintain the prescribed motion. To specify the mass properties, click on Mass Properties to open the dialog window. Two options are available for the mass properties definition: provide mass density or the integrated mass properties including the total mass, mass center and the moment of inertia tensor.

질량물성의 정의가 결합운동을 하는 이동체에 대해 필요하지만 지정운동을 하는 이동체에는 선택적이다. 지정운동체에 대해 질량 물성이 주어지면 solver 는 지정 운동을 유지하기 위해 중력, 수력, 관성력, 스프링 힘과 사용자 지정의 힘과 토크를 보완하는 잔여 조절 힘과 토크를 계산하고 출력할 것이다. 질량물성을 지정하기 위한 대화창을 열기 위해 Mass Properties를 클릭한다. 이를 위해 두 가지 선택이 있다: 질량밀도 또는 전체질량, 질량중심과 관성모멘트텐서를 포함하는 통합 질량 물성을 제공한다.

The option to provide mass density is convenient if the object has a uniform density or all its subcomponents have uniform densities. In this case, the preprocessor will calculate the integrated mass properties for the object. In the Mass Properties tab, select Define Density in the combo box and enter the density value in the Mass Density input box. By default, each subcomponent of the object takes this value as its own mass density. If a subcomponent has a different density, define it under that subcomponent in the geometry tree, Geometry Component Subcomponents Subcomponent (the desired component) Mass Density.

물체나 이 물체의 소 구성요소가 균일한 밀도를 가지면 질량밀도를 주는 선택이 편하다. 이 경우 전처리과정이 이에 대한 모든 통합 질량물성을 계산할 것이다. Mass Properties 탭에서 combo 박스에 있는 Define Density 를 선택하고 Mass Density 입력박스에서 밀도 값을 넣는다. 디폴트로 물체의 소 구성 요소의 밀도는 물체의 밀도와 같다. 만약에 소 구성요소가 다른 밀도를 가지면 이를 형상체계에 있는 Geometry Component Subcomponents Subcomponent (the desired component) Mass Density 소구성요소에서 정의한다.

 

The option to provide integrated mass properties is useful if the object’s mass, mass center and moment of inertia tensor are known parameters regardless of whether the object’s density is uniform or not. In the Mass Properties tab, choose Define Integrated Mass Properties in the combo box and enter the following parameters in the input boxes depending on the type of motion: Total mass, initial mass center location (at t = 0) and moment of inertia tensor about mass center for 6-DOF and fixed-point motion types;

통합 질량 물성의 사용은 물체의 밀도가 균일한지와 무관하게 물체의 질량, 질량중심, 관성모멘트 텐서 등이 알려진 변수일 경우에 유용하다. Mass Properties 탭에서 combo 박스에있는 Define Integrated Mass Properties 을 선택하고 운동형태에 따라 입력상자 안에 다음 변수들을 넣는다:

 

  • Total mass, initial mass center location (at t = 0) and moment of inertia about fixed axis for fixed-axis motion type.

전체 질량, 초기 질량중심 위치(t=0에서), 그리고 6자유도 및 고정점 운동 형태를 위한 질량중심에 관한 관성모멘트텐서

Output출력

For each GMO component, the solver outputs time variations of several solution variables that characterize the object’s motion. These variables can be accessed during post-processing in the General history data catalog and can be viewed either graphically or in a text format. For both prescribed and coupled types of motion with the mass properties provided, the user can find the following variables:

각 GMO 요소에 대해solver는 물체의 운동 특성을 보여주는 대여섯 개의 해석변수의 시간에 대한 변화를 출력한다. 이 변수들은 General history 데이터카탈로그에서 후처리중에 텍스트나 도식으로 볼 수 있다. 주어진 질량을 갖는 지정과 결합운동에 대해 사용자는 다음 변수들을 이용할 수가 있다.

  1. Mass center coordinates in space system공간계 내의 질량중심좌표
  2. Mass center velocity in space system공간계 내의 질량중심 속도
  3. Angular velocity in body system물체계 내의 각속도
  4. Hydraulic force in space system공간계 내의 수리력
  5. Hydraulic torque in body system물체계 내의 수리토크
  6. Combined kinetic energy of translation and rotation 이동과 회전의 결합운동에너지

There will be no output for items 1, 2 and 6 for any prescribed-motion GMO if the mass properties are not provided. Additional output of history data include:

질량물성이 주어지지 않으면 지정운동을 하는 GMO 에대해 상기 1,2와6에대한 출력은없다. 추가적이력데이터의 출력은

  • Location and velocity of the reference point for a prescribed 6-DOF motion지정된6자유도운동을 위한 기준점의 위치와 속도
  • Rotational angle for a fixed-axis motion

고정축 운동을 위한 회전각

  • Residual control force and torque in both space and body systems for any prescribed motion and a coupled motion with constraints (fixed axis, fixed point and prescribed velocity components)

지정운동 및 구속을 갖는 결합운동(고정축, 고정점, 그리고 지정속도성분)에 대한 두 공간과 물체계에서의 잔여 제어 힘과 토크

  • Spring force/torque and deformation

스프링 힘과 토크 및 변형

  • Mooring line extension and maximum tension force

계류선 신장 및 최대인장력

  • Mooring line tension forces at two ends in the x, y and z directions

x, y 및 z 방향에서 양끝에 작용하는 계류선 인장력

 

As an option, the history data for a GMO with 6-DOF motion can also include the buoyancy center and the metacentric heights for rotations about x and y axes of the space system, which is useful for stability analysis of a floating object. Go to Geometry Component (the desired moving object) Output Buoyancy Center and Metacentric Height, and select Yes. The buoyancy center is defined as the mass center of the fluid displaced by the object. The metacentric height (GM) is the distance from the gravitational center (point G) to the metacenter (point M). It is positive (negative) if point G is below (above) M.

선택사항으로 GMO 6자유도의 이력데이터는 부력중심과 부력물체의 안정성 해석에 유용한 공간계의 x와 y 축에 대한 회전을 위한 metacentric 높이를 포함한다. Geometry Component (the desired moving object) Output Buoyancy Center and Metacentric Height 로가서 Yes 를 선택한다. 부력 중심은 물체에 의해 배수된 부분을 차지하는 유체의 질량중심으로 정의된다. The metacentric height (GM) 은 중력중심(점 G) 에서 metacenter (점M)까지이다. 점 G가 M보다 밑(위)이면 양(음)이다.

 

GMO components can participate in heat transfer just like any stationary solid component. When defining specific heat of a GMO component, Component Properties Solid Properties Density*Specific Heat must be given.

GMO 요소는 여느 정지 고체 요소와 같이 열전달을 포함 할 수 있다. GMO 요소의 비열을 정의할 때 Component Properties Solid Properties Density*Specific Heat 가 주어져야 한다.

 

Two options are available when defining heat sources for a GMO component: use the specific heat flux, or the total power. When the total power is used, the heat fluxes along the open surface of the moving object are adjusted at every time step to maintain a constant total power. If the surface area varies significantly with time, so will the heat fluxes. When the specific heat is used instead, then the fluxes will be constant, but the total power may vary as the surface area changes during the object’s motion. To define heat source for a GMO component, go to Component Properties Solid Properties Heat Source type Total amount or Specific amount.

GMO 요소의 열 소스를 정의할 때 두 가지 선택이 있다: 비열유속 또는 전체 일률(power)를 사용하는 것이다. 전체 일률이 사용되면 이동체의 개표면을 통한 열 유속은 일정 전체 일률을 유지하기 위해 매 시간 단계 마다 조정된다. 표면적이 시간에 따라 상당히 변하면 열유속도 그러할 것이다. 대신에 비열이 사용되면 열 유속은 일정할 것이고 전체일률은 표면적이 이동체의 운동에 따라 변할 때 변할 수도 있다. GMO 요소의 열소스를 정의하기 위해 to Component Properties Solid Properties Heat Source type Total amount or Specific amount 로 간다.

 

Mass sources/sinks can also be defined on the open surfaces of a GMO component. Details can be found in Mass

Sources. 질량소스나 싱크 또한 GMO 요소의 개표면 상에 정의될 수 있다. 자세한 것은 in Mass Sources 에서 볼 수 있다.

Although the GMO model can be used with most physical models and numerical options, limitations exist. To use the model properly, it is noted that

GMO 모델은 대부분의 다른 물리적 모델이나 수치해석 선택과 같이 사용될 수 있지만 제한이 따른다. 모델을 제대로 사용하기 위해 다음 사항들에 유의한다.

  • For coupled motion, the explicit and implicit GMO methods perform differently. The implicit GMO method works for both heavy and light moving objects. The explicit GMO method, however, only works for heavy object problems (i.e., the density of moving object is higher than the fluid density).

결합운동에 대해 내재적과 외재적 GMO 방법은 다르게 작동한다. 내재적 GMO 방법은 무겁거나 가벼운 이동물체에 이용될 수 있지만 외재적 GMO 방법은 무거운 물체의 이동에만 이용한다(즉, 이동물체의 밀도가 유체의 밀도보다 크다).

  • When the explicit GMO method is used, solution for fully coupled moving objects may become unstable if the added mass of the fluid surrounding the object exceeds the object’s mass.

외재적 GMO 방법이 사용될 때 물체 주위 유체의 부가질량이 물체의 질량보다 크면 완전결합 이동물체의 해석은 불안정하게 된다.

  • If there are no GMO components with coupled motion, then the implicit and explicit methods are identical and the choice of one makes no difference to the computational results.

결합운동을 하는 GMO 요소가 없으면 내재적과 외재적 방법은 같고 어느 하나를 사용해도 계산결과에 차이가 없다.

  • The implicit method does not necessarily take more CPU time than the explicit method, even though the former required more computational work, because it improves numerical stability and convergence, and allows for larger time step. It is thus recommended for all GMO problems.

내재적 방법은 수치(해석) 안정성과 수렴이 개선되고 더 큰 시간 단계를 가능하게 해주기 때문에 더 많은 계산을 필요로 하지만 외재적 방법보다 항상 더 많이 CPU시간을 필요로 하지는 않는다. 따라서 모든 문제에 권장된다.

  • It is recommended that the limited compressibility be specified in the fluid properties to improve numerical stability by reducing pressure fluctuations in the fluid.

유체내의 압력 변동을 줄임으로써 수치해석안정성을 증가시키기 위해 제한된 압축성이 유체 물성에서 지정되도록 권장된다.

  • In the simulation result, fluctuations of hydraulic force may exist due to numerical reasons. To reduce these fluctuations, the user can set No f-packing for free-surface problems in Numerics Volume of fluid advection Advanced options and set FAVOR tolerance to 0.0001 in Numerics Time-step controls Advanced Options Stability enhancement. It is noted that an unnecessarily small FAVORTM tolerance factor can cause small time steps and slow down the computation.

모사(simulate)결과에서 수리력의 변동이 수치적인 이유로 존재할 수 있다. 이 변동을 줄이기 위해 사용자는 Numerics Volume of fluid advection Advanced options 에서 자유표면 문제에 대해 No f-packing 을 지정하고 FAVOR tolerance Numerics Time-step controls Advanced Options Stability enhancement 에서 0.0001로 지정할 수 있다. 불필요하게 작은 FAVORTM tolerance 인자는 작은시간 단계를 발생시키고 계산을 더디게 할 수 있다.

  • In order to calculate the fluid force on a moving object accurately, the computational mesh needs to be reasonably fine in every part of the domain where the moving object is expected to be in contact with fluid.

이동물체에 대한 유체의 힘을 정확히 계산하기 위해 이동체가 유체와 접촉할 것으로 예상되는 영역내의 모든 부분에서 적절히 미세한 계산격자를 사용해야한다.

  • An object can move completely outside the computational domain during a computation. When this happens, the hydraulic forces and torques vanish, but the object still moves under actions of gravitational, spring, inertial and control forces and torques. For example, an object experiences free fall outside the domain under the gravitational force in the absence of all other forces and torques.

물체는 계산 동안에 완전히 계산영역 외부로 이동할 수 있다. 이럴 경우 수리력과 토크는 사라지지만 물체는 중력, 스프링힘, 관성력 및 조절 힘과 토크의 영향으로 움직인다. 예를 들면 물체는 모든 다른 힘과 토크가 없는 경우에 중력장 안에 있는 영역외부에서 자유낙하를 할 것이다.

  • If mass density is given, then the moving object must initially be placed completely within the computational domain and the mesh around it should be reasonably fine so that its integrated mass properties (the total mass, mass center and moment of inertia tensor) can be calculated accurately by the code

질량밀도가 주어지면 초기에 물체가 완전히 계산영역 내에 위치하고 있어야 하고 이 주변의 격자는 적절히 미세하게 하여 이의 통합 질량물성(전체질량, 질량중심 그리고 관성모멘트텐서)이 이 코드에 의해 정확히 계산될 수 있어야 한다.

  • If a moving object is composed of multiple subcomponents, they should have overlap in places of contact so that no unphysical gaps are created during motion when the original geometry is converted to area and volume fractions. If different subcomponents are given with different mass densities, this overlap should be small to avoid big errors in mass property calculation.

이동체가 다수의 소 구성요소로 이루어져 있다면 원래 형상이 면적과 체적율로 전환될 때 이들은 접촉부에 중첩이 있어야만 이동 시에 실제로 존재하지 않은 간격이 발생 안 한다. 다른 소구성요소가 다른 질량밀도로 주어지면 이 간격은 질량물성 계산시 큰 에러를 줄이기 위해 작아야 한다.

  • A moving object cannot be of a phantom component type like lost foam or a deforming object.

이동체는 lost foam 이나 변형물체 같은 phantom 구성요소가 될 수 없다.

  • The GMO model works with the electric field model the same way as the stationary objects, but no additional forces associated with electrical field are computed for moving objects.

GMO 모델은 정지 물체와 같은 전장모델과 이용할 수 있으나, 전장 관련 추가적 힘은 계산되지 않는다.

  • If a GMO is porous, light in density and high in porous media drag coefficients, then the simulation may experience convergence difficulties.

GMO가 밀도가 가볍고 다공매질 저항계수가 큰 다공질이면 모사(simulate)에 수렴의 어려움이 있을 수 있다.

  • A Courant-type stability criterion is used to calculate the maximum allowed time-step size for GMO components. The stability limit ensures that the object does not move more than one computational cell in a single time step for accuracy and stability of the solution. Thus the time step is also limited by the speed of the moving objects during computation.

GMO 구성요소에 대해 Courant 형의 안정성 기준이 최대허용 시간 단계 크기를 계산하도록 이용된다. 안정성 제한은 해석의 정확성과 안정성을 위해 물체가 하나의 시간 단계에 하나 이상의 계산 셀을 지나가지 않도록 보장하는 것이다. 그러므로 시간 단계는 계산시 또한 이동체의 속도에 의해 제한된다.

Note:

  • Time-Saving Tip: For prescribed motion, users can preview the object motion in a so-called “dry run” prior to the full flow simulation. To do so, simply remove all fluid from the computational domain to allow for faster execution. Upon the completion of the simulation the motion of the GMO objects can be previewed by post-processing the results. 시간절약팁: 지정운동에서 사용자는 실제 전체 유동 계산 전에 소위 “dry run” 이라는 형태로 GMO 물체의 운동을 미리 볼 수 있다. 이러기 위해 빠른 계산을 하기 위해 계산영역 내로부터 모든 유체를 단순히 제거한다. 모사(simulate)가 끝나면 운동은 결과를 후처리함으로써 미리 볼 수 있다.
  • The residual forces (and torques) are computed for the directions in which the motion of the object is prescribed/constrained. They are defined as the difference between the total force on an object (computed from the prescribed mass*acceleration) and the computed forces on the object from pressure, shear, gravity, specified control forces, etc. As such, they represent the force required to move the object as prescribed.

잔류력(그리고 토크)은 물체의 이동이 지정되거나 제약되는 방향으로 계산된다. 이들은 물체에 작용하는 전체 힘(지정 질량*가속도로부터 구해지는)과 압력, 전단력, 중력, 지정된 조절력 등으로부터 물체에 가해지는 계산된 힘과의 차이로 정의된다.

Collision충돌

The GMO model allows users to have multiple moving objects in one problem, and each of them can possess independent type of coupled or prescribed motion. At any moment of time, each object under coupled motion can collide with any other moving objects (of a coupled- or prescribed-motion type), non-moving objects as well as wall- and symmetry-type mesh boundaries. Without the collision model, objects may penetrate and overlap each other.

GMO 모델에서 사용자는 한 문제에서 다수의 이동체를 지정할 수 있고 각 이동체는 결합 또는 지정된 별도 운동을 할 수가 있다. 어느 순간에서 결합 운동을 하는 각 물체는 벽 또는 대칭형 격자 경계뿐만 아니라 다른 이동체들(결합운동 이나 지정운동을 하는), 그리고 정지하고 있는 물체와 충돌할 수 있다.  충돌모델 없으면 물체는 각기 침투하거나 중첩될 수가 있다.

The GMO collision model is activated by selecting Physics Moving and simple deforming objects Activate collision model. It requires the activation of the GMO model first, done in the same panel. For a GMO problem with only prescribed-motion objects, it is noted that the collision model has no effect on the computation: interpenetration of the objects can still happen.

GMO 충돌모델은 Physics Moving and simple deforming objects Activate collision model 를 선택함으로써 활성화된다. 먼저 같은 패널에서 GMO 모델을 활성화한다. 단지 지정된 운동을 하는 GMO 물체 문제에 대해 충돌모델은 계산에 영향을 안 미친다는 것을 주목한다: 그래도 물체의 침투는 가능하다.

The model allows each individual collision to be fully elastic, completely plastic, or partially elastic, depending on the value of Stronge’s energetic restitution coefficient, which is an input parameter. In general, a collision experiences two phases: compression and restitution, which are associated with loss and recovery of kinetic energy. The Stronge’s restitution coefficient is a measure of kinetic energy recovery in the restitution phase. It depends on the material, surface geometry and impact velocity of the colliding objects. The range of its values is from zero to one. The value of one corresponds to a fully elastic collision, i.e., all kinetic energy lost in the compression is recovered in the restitution (if the collision is frictionless). Conversely, a zero restitution coefficient means a fully plastic collision, that is, there is no restitution phase after compression thus recovery of the kinetic energy cannot occur. A rough estimate of the restitution coefficient can be conducted through a simple experiment. Drop a sphere from height h0 onto a level anvil made of the same material and measure the rebound height h. The restitution coefficient can be obtained as h/h0. In this model, the restitution coefficient is an object-specific constant. A global value of the restitution coefficient that applies to all moving and non-moving objects is set in Physics Moving and simple deforming objects Coefficient of restitution.

입력 변수인 Stronge 의 에너지 반발계수의 값에 따라 모델은 물체의 완전탄성, 완전소성 또는 탄성의 각기 충돌을 다룰 수 있다. 일반적으로 충돌은 두 단계로 나뉜다: 압축과 반발이며 이들은 운동에너지의 손실및 회복과 연관되어 있다. Stronge 의 반발계수는 반발단계에서의 에너지회복의 척도이다. 이는 물질, 표면형상 그리고 충돌하는 물체의 충격속도에 의존한다.

이값은 0과1사이이다. 1은 완전탄성충돌이며 압축에서 손실된 모든 운동에너지가 반발에서 회복된다(충돌에마찰이없다면). 역으로, 0의 반발계수는 완전소성충돌로 즉 압축 후에 반발이 없으며 운동에너지의 회복은 일어나지 않는다. 반발계수의 개략 추정치는 단순한 실험을 통해 얻어질 수 있다.

높이 h0에서 구를 같은 재질로 만들어진 anvil (모루?)위로 떨어뜨려 반발높이 h 를 측정한다. 반발계수는 h/h0로얻어진다. 이모델에서 반발계수는 물질에 특정한 상수이다. 모든 이동과 비 이동물체에 적용되는 반발계수의 포괄적인 값은 Physics Moving and simple deforming objects Coefficient of restitution 에서 지정된다.

 

Friction can be included at the contact point of each pair of colliding bodies by defining the Coulomb’s friction coefficient. A global value of the friction coefficient that applies to all collisions is set in Physics General moving objects Coefficient of friction. Friction forces apply when the friction coefficient is positive; a collision is frictionless for the zero value of the friction coefficient, which is the default. The existence of friction in a collision always causes a loss of kinetic energy.

마찰은 Coulomb 마찰계수를 정의함으로써 충돌하는 각 물체의 접촉 점에 작용한다. 모든 충돌에 적용되는 마찰계수의 포괄적 값은 Physics General moving objects Coefficient of friction 에서 설정된다. 마찰력은 마찰계수가 양일 경우 작용한다; 충돌시 마찰계수가0일 경우 마찰력이 없고, 이는 디폴트이다. 충돌 시 마찰력의 존재는 항상 운동에너지의 손실을 뜻한다.

 

The global values of the restitution and friction coefficients are also used in the collisions at the wall-type mesh boundaries, while collisions of the moving objects with the symmetry mesh boundaries are always fully elastic and frictionless.

포괄적 마찰 및 반발계수는 또한 벽 형태의 경계에서 충돌이 발생할 경우에도 사용될 수 있으나 이동체의 대칭격자 경계와의 충돌은 항상 완전탄성이고 마찰이 없다.

 

The object-specific values for the restitution and friction coefficients are defined in the tab Model Setup Meshing & Geometry. In the geometry tree on the left, click on Geometry Component (the desired component) Component Properties Collision Properties and then enter their values in the corresponding data boxes. If an impact occurs between two objects with different values of restitution coefficients, the smaller value is used in that collision calculation. The same is true for the friction coefficient.

물체에 특정한 반발 및 마찰계수는 탭 Model Setup Meshing & Geometry 에서 정의된다. 좌측의 형상체계에서 on Geometry Component (the desired component) Component Properties Collision Properties 를 클릭하고 상응하는 데이터박스에 그 값들을 입력한다. 다른 반발계수를 갖는 두 물체 사이에 충격이 발생하면 그 충돌 계산에 작은 마찰계수 값이 이용된다. 이는 마찰의 경우에도 마찬가지이다.

Continuous contact, including sliding, rolling and resting of an object on top of another object, is simulated through a series of small-amplitude collisions, called micro-collisions. Micro-collisions are calculated in the same way as the ordinary collisions thus no additional parameters are needed. The amplitude of the micro-collisions is usually small and negligible. In case the collsion strength is obvious in continuous contact, using smaller time step may reduce the collision amplitude.

미끄러짐, 회전, 및 타물체상에 정지하고 있는 물체를 포함하는 지속적인 접촉은 미세충돌이라고 불리는 일련의 소 진폭 충돌에 의해 모사(simulate)된다. 미세 충돌은 추가적인 매개변수 필요 없이 보통충돌과 같은 방식으로 계산된다. 충돌강도가 지속적 접촉에서 현저한 경우 더 작은 시간간격을 시용하는 것이 충돌 진촉을 감소시킬지도 모른다.

 

If the collision model is activated but the user needs two specific objects to have no collision throughout the computation, he can open the text editor (File Edit Simulation) and set ICLIDOB(m,n) = 0 in namelist OBS, where m and n are the corresponding component indexes. An example of such a case is when an object (component index m) rotates about a pivot – another object (component index n). If the former has a fixed-axis motion type, then calculating the collisions with the pivot is not necessary. Moreover, ignoring these collisions makes the computation more accurate and more efficient. If no collisions between a GMO component m with all other objects and mesh boundaries are desired, then set ICLIDOB(m,m) to be zero. By default, ICLIDOB(m,n) = 1 and ICLIDOB(m,m) = 1, which means collision is allowed.

충돌모델이 활성화되고 시용자가 모사(simulate)동안에 충돌하지 않는 두 특정 물체를 필요로 하면 텍스트편집(File Edit Simulation) 을 열어 namelist OBS 에서 ICLIDOB(m,n) = 0 를 지정하는데, 여기서 m n 은 상응하는 구성 요소 색인이다.

이런 예는 한 물체(component index m)가 경첩축인 다른 물체(component index n)에대해 회전할 경우이다. 전자가 고정축에 대한 운동형태이면 경첩 축과의 충돌은 계산할 필요가 없다. 더구나 이런 충돌을 무시하는 것이 계산상 더 정확하고 효율적이다.

한 GMO component 구성요소 m 과 모든 다른 물체나 격자 경계와의 충돌이 없다면 ICLIDOB(m,m) 를 0으로 지정한다. 디폴트는 ICLIDOB(m,n) = 1 이며 이는 충돌이 허용됨을 뜻한다.

 

To use the model prpperly, users should be noted that

모델을 적절히 사용하기 위해서 사용자는 다음에 주목한다.

  • The collision model is based on the impact theory for two colliding objects with one contact point. If multiple contact points exist for two colliding objects (e.g. surface contact) or one object has simultaneous contact with more than one objects, object overlap may and may not occur if the model is used, varing from case to case.

충돌모델은 한 접촉점을 갖는 두 물체의 충돌이론에 의거한다. 이 모델 사용시 두 물체의 충돌에 다수의 접촉점이 존재(즉 표면접촉같이)하거나 한 물체가 동시에 다른 물체들과 충돌하면 경우에 따라 중첩이 발생할 수도 있고 안 할 수도 있다.

  • To use the model, one of the two colliding object must be under coupled motion, and the other can have coupled or prescribed motion or no motion. The coupled motion can be 6-DOF motion, translation, fixed-axis rotation or fixed-point rotation. For other constrained motion, (e.g., rotation is coupled in one direction but prescribed in another direction), the model is not valid, and mechanical energy of the colliding objects may have conservation problem.

이 모델사용 시 두 충돌 물체중의 하나는 결합운동을 하여야 하고 다른 물체는 결합 또는 지정 운동 또는 정지하고 있을 수 있다. 결합운동은 6자유도 운동일 수 있다(이동, 고정축 또는 고정점 회전). 다른 구속 운동(즉, 한 방향에서는 결합 운동이지만 다른 방향에서는 지정 운동)에서 이 모델은 유효하지 않고 충돌물체의 역학에너지는 보존문제가 발생할는지도 모른다.

  • The model works with and without existence of fluid in the computational domain. It is required, however, that the contact point for a collision be within the computational domain, whereas the colliding bodies can be partially outside the domain at the moment of the collision. If two objects are completely outside the domain, their collision is not detected although their motions are still tracked.

이 모델은 계산 영역 내 유체의 존재 유무에 상관없이 작동한다. 그러나 충돌 시 접촉점은 계산 영역 내에 존재해야 하나 충돌체는 충돌 시 부분적으로 영역외부에 있어도 된다. 두 물체가 완전히 영역 외부에 있으면 이들의 운동은 그래도 추적되지만 충돌은 감지되지 못한다.

  • Collisions are not calculated between a baffle and a moving object: they can overlap when they contact.

이동물체와 배플간의 충돌은 계산되지 않는다: 이들이 접촉하면 중첩될 수 있다.

The model does not calculate impact force and collision time. Instead, it calculates impulse that is the product of the two quantities. Therefore, there is no output of impact force and collision time.

이 모델은 충격 힘과 충돌시간은 계산하지 않는다. 대신에 두 양의 곱인 impulse 를계산한다. 그러므로 충격 힘과 충돌시간에 대한 출력이 없다.

PQ2 Analysis PQ2 해석

PQ2 analysis is important for high pressure die casting. The goal of the PQ2 analysis is to optimally match the die’s designed gating system to the part requirements and the machine’s capability. PQ2 diagram is the basic tool used for PQ2 analysis.

PQ2 해석은 고압주조에서 중요하다. 이 해석의 목적은 부품 요건 및 기계의 용량에 따른 다이의 설계된 게이트 시스템을 최적화시키기 위한 것이다. PQ2 도표는 PQ2해석을 위한 기본 도구이다.

According to the Bernoulli’s equation, the metal pressure at the gate is proportional to the flow rate squared:

베르누이 정리에 의하면 게이트에서의 금속압력은 유량의 제곱에 비례한다.

P Q2                                                                                     (11.5)

where: 여기서

  • P is the metal pressure at the gate, and P 는 게이트에서의 압력이며
  • Q is the metal flow rate at the gate. Q 는 게이트에서의 유량이다.
  • The machine performance line follows the same relationship. 기계성능 곡선도 같은 관계를 따른다.

Based on the die resistance, machine performance, and the part requirements, an operating windows can be determined from the PQ2 diagram, as shown below. The die and the machine has to operate within the operating windows.

다이 저항, 기계성능, 그리고 부품 요건에 따라 운영범위가 밑에 보여진 바와 같이 PQ2 도표에서 결정될 수 있다. 다이와 기계는 운영범위 내에서 작동되어야 한다.

Model Setup모델설정

PQ2 analysis can only be performed on moving object with prescribed motion. The PQ2 analysis can be activated in Meshing & Geometry Component Properties Moving Object. PQ2 analysis can only be performed on one component.

PQ2해석은 단지 지정운동을 하는 이동체에서만 실행될 수 있다. 이는 Meshing & Geometry Component Properties Moving Object 에서 활성화된다. 또 이는 단지 한 개의 구성요소에 대해서만 실행될 수 있다.

The parameters Maximum pressure and Maximum flow rate define the machine performance line.

매개변수 Maximum pressure Maximum flow rate 는 기계성능 곡선을 정의한다.

During the design stage, the process parameters specified might not optimal, such that the resulting pressure is beyond the machine capability. If this happens, the option Adjust velocity can be selected so that the piston velocity is automatically adjusted to match the machine capability. If Adjust velocity is selected, at every time step the pressure at the piston head will be compared with the machine performance pressure to see if it is beyond the machine capability. If it is beyond the machine capability, the flow rate is then reduced to match the machine capability. The reduction is instantaneous and no machine inertia is considered. Once the pressure drops below the machine performance line, the piston will then accelerate to the prescribed velocity. The acceleration has to be less than the machine Maximum acceleration specified.

설계시에 초래된 압력이 기계 성능 이상으로 되는 것같이 지정된 공정 변수들이 최적화가 되지 않았을지도 모른다.  이런 경우에 Adjust velocity 를 선택할 수 가 있고 피스톤속도는 기계성능에 맞게끔 자동적으로 조절될 수 있다. 만약 Adjust velocity 가 선택되면 매 시간단계에서 피스톤헤드의 압력이 기계 성능 이상인지를 알기 위해 기계성능 압력과 비교될 것이다. 압력이 기계 성능 이상이라면 유량은 기계성능을 맞추기 위해 감소될 것이다. 감소는 순간적으로 이루어지고 기계의 관성은 고려되지 않는다. 일단 압력이 성능 이하로 줄어들면 피스톤은 지정속도로 가속할 것이다. 가속도는 기계의 지정된 Maximum acceleration 보다 작아야 할 것이다. .

 

If Adjust velocity is selected, the machine parameters Maximum pressure and Maximum flow rate have to be provided. The Maximum acceleration is also required, however, it is by default to be infinite if not provided.

Adjust velocity 가 선택되면 기계시스템 변수 Maximum pressure Maximum flow rate 가 주어져야 한다. 또한 Maximum acceleration 가 필요하나 주어지지 않으면 디폴트 값은0이다.

 

For high pressure die casting, the fast shot stage is very short. But it is this stage that is of interest. The pressure and flow rate are written as general history data. The data output interval has to be very small to capture all the features in this stage. To reduce FLSGRF file size, only when flow rate reaches Minimum flow rate, the history data output interval is reduced to every two time steps. If Minimum flow rate is not provided, it is default to 1/3 of the Maximum flow rate. Note that the only purpose of Minimum flow rate is to change the history data output frequency.

고압주조에서 고속충진단계는 아주 짧은데 우리는 이 단계에 관심이 있다. 압력과 유량은 일반 이력 데이터로 기록된다. 데이터출력 간격은 이 단계에서의 모든 양상을 보기 위해 아주 작아야 한다. FLSGRF 파일 크기를 줄이기 위해 유량이 Minimum flow rate 에 도달했을 때만 이력데이터 출력 간격은 두 시간 간격에 한번으로 감소된다. Minimum flow rate 가 주어지지 않으면 Maximum flow rate 의 1/3이 디폴트값이다. 단지, Minimum flow rate 를 사용하는 목적은 이력 데이터 출력 간격을 변경하는 것임에 주목한다.

 

Due to the limitation of the FAVORTM, the piston head area computed may fluctuate as piston pushing through the shot sleeve. As a result, the metal flow rate computed may also fluctuate. To reduce the fluctuation, Shot sleeve diameter is recommended to be provided, so that it can be used to correct the metal flow rate. If only half of the domain is modeled, the diameter needs to be scaled to reflect the real cross section area in the simulation.

FAVORTM 제약에 따라 계산된 피스톤헤드 면적은 피스톤이 shot sleeve 를 통해 움직일 때 변할 수 있다. 결과적으로 계산된 액체금속 유량이 변할 수 있다. 이를 줄이기 위해 Shot sleeve diameter 를 주는 것이 필요하고, 이로부터 액체금속 유량을 정정할 수 있다.  만약에 단지 영역의 반만 모델이 되면 직경은 모사(simulate)시에 실제 단면적을 나타내기 위해 비례되어야 한다.

Postprocessing 후처리

If PQ2 analysis is chosen, the pressure, flow rate, and prescribed velocity of the specified moving object will be written to FLSGRF file as General history data. If Adjust velocity is selected, the adjusted velocity will also be written as General history data. In addition, the PQ2 diagram can be drawn directly from the history data in FlowSight.

PQ2해석이 선택되면 압력, 유량 그리고 특정 이동체의 지정속도가 General history 데이터로 FLSGRF 파일에 쓰여질 것이다. Adjust velocity 가 선택되면 조절된 속도 또한 General history 데이터로 쓰여질 것이다. 추가로 PQ2 도표는 직접 Flow Sight에서 이력데이터로 그려질 수 있다.

Elastic Springs & Ropes 탄성 스프링과 로프

The GMO model allows existence of elastic springs (linear and torsion springs) and ropes which exert forces or torques on objects under coupled motion. Users can define up to 100 springs and ropes in one simulation, and each moving object can be arbitrarily connected to multiple springs and ropes. For a linear spring, the elastic restoring force Fe is along the length of the spring and satisfies Hooke’s law of elasticity,

GMO 모델은 결합운동하는 물체에 힘과 토크를 미치는 탄성스프링(선형과 비틀림 스프링)과 로프로 이용될 수 있다. 사용자는 한 모사(simulate)에서 100개까지의 스프링과 로프를 정의할 수 있고 각 이동체는 임의로 다수의 스프링과 로프에 연결될 수 있다. 선형 스프링에서 탄성회복력 Fe 는 스프링의 길이 방향을 따라서 작용하며 Hooke 의 탄성법을 만족한다.

Fe = kl l

where: 여기서

  • kl is the spring coefficient,

kl 는스프링상수

  • l is the spring’s length change from its free condition,

l 는 스프링의 길이 변화량

  • Fe is a pressure force when the spring is compressed, and a tension force when stretched.

Fe 는 스프링이 압축되었을 때는 압축힘이며 늘어났을 때는 인장력이다.

An elastic rope also obeys Hooke’s law. It generates tension force only if stretched, but when compressed it is relaxed and the restoring force vanishes as would be the case of a slack rope.

탄성 로프 또한 Hooke 의 탄성법칙을 따른다. 단지 인장의 경우에만 인장력을   발생시키나 압축의 경우 느슨한 로프의 경우에서와 같이 느슨해지고 복원력은 사라진다.

A torsion spring produces a restoring torque T on a moving object with fixed-axis when the spring is twisted, following the angular form of Hooke’s law,

비틀림 스프링은 스프링이 비틀렸을 때 의 각 형태의 Hooke 법칙을 따라 고정 회전축을 갖는 이동체에 복원 토크 T 를 일으킨다.

Te = kθ θ

where: 여기서

  • kθ is the spring coefficient in the unit of [torque]/degree, and

kθ  [torque]/degree 는 단위의 스프링상수 그리고

  • θ is the angular deformation of the spring.

θ 는 스프링의 각변형

  • It is assumed that there is no elastic limit for the springs and ropes, namely Hooke’s law always holds no matter how big the deformation is.

스프링과 로프에는 탄성한계가 없다고 가정된다. 즉 아무리 스프링과 로프의 변형이 커도 Hooke 의 법칙이 작용한다고 가정된다.

A linear damping force associated with a spring/rope and a damping torque associated with a torsion spring may also be defined. The damping force Fd is exerted on the moving object at the attachment point of the spring/rope. Its line of action is along the spring/rope, and its value is proportional to the time rate of the spring/rope length,

스프링/로프에서의 선형 감쇠력 그리고 비틀림 스프링에서의 감쇠토크가 또한 정의된다. 감쇠력 Fd 는 스프링/로프의 부착점이 있는 이동체에 작용한다. 이의 작용선은 스프링/로프를 따라서이며 그 값은 스프링/로프 길이의 시간당 변화율에 비례한다.

dl

Fd = −cl

dt

Note the damping force for a rope vanishes when the rope is relaxed.

로프의 감쇠력은 로프가 느슨해질 때 없어진다.

The damping torque Td can only be applied on an object with a fixed-axis rotation. Its direction is opposite to the angular velocity, and its value is proportional to the angular velocity value,

감쇠 토크 Td 는 단지 고정축 회전을 하는 물체에만 적용된다. 그 방향은 각속도에 반대방향이고 값은 각속도 값에 비례한다.

Td = −cdω

where ω (in rad/time) is the angular velocity of the moving object.

여기서 ω (in rad/time) 는 이동체의 각속도이다.

 

In this model, a linear spring or rope can have one end attached to a moving object under coupled motion and the other end fixed in space or attached to another moving object under either prescribed or coupled motion. A torsion spring, however, must have one end attached to an object under coupled fixed-axis motion and the other end fixed in space. It is assumed that the rotation axis of the object and the axis of the torsion spring are the same. As a result, the torque applied by the spring on the object is around the object’s rotation axis, and the deformation angle of the spring is equal to the angular displacement of the object from where the spring is in free condition.

이 모델에서 선형 스프링 또는 로프는 한쪽 끝은 결합 운동하는 물체에 그리고 다른 끝은 공간에 고정되어 있거나 지정 또는 결합 운동을 하는 다른 이동체에 연결될 수 있다. 그러나 비틀림 스프링은 한 끝은 결합된 운동을 하는 물체에, 그리고 다른 한끝은 공간에 고정되어 있어야 한다. 물체의 회전축 및 비틀림 스프링의 축은 같다고 가정된다. 결과적으로 물체에 스프링에 의해 가해진 토크는 물체의 회전축둘레로 작용하며 스프링의 각 변형은 스프링의 자유위치로부터의 각변위와 같다.

 

A linear spring has a block length due to the thickness of the spring coil. It is the length of the spring at which the spring’s compression motion is blocked by its coil and cannot be compressed any further. This model allows for three types of linear springs:

선형스프링은 스프링 코일의 두께에 의한 차단 거리가 있다. 이는 스프링의 압축 운동이 그 코일에 의해 방해되어 더 이상 압축될 수 없는 스프링의 길이이다. 이 모델은 3가지의 선형 스프링을 고려할 수 있다.

  • Compression and extension spring: a spring that can be both compressed and extended. Its block length, by default, is 10% of its free length (the length of the spring in the force-free condition).

압축 및 확장스프링: 압축되거나 확장될 수 있는 스프링이며 이의 차단거리는 디폴트로 자유길이(힘을 받지 않을 때의 스프링의 길이) 의 10%이다

  • Extension spring: a spring that can only be extended. Its block length is always equal to its free length.

확장스프링: 확장될 수 있는 스프링이며 차단거리는 항상 자유 길이와 같다.

  • Compression spring: a spring that applies force only when it is compressed. When it is stretched, the force on the connected object vanishes. Its default block length is 10% of its free length.

압축스프링: 단지 압축되었을 경우에만 힘이 작용한다.  늘어날 경우 연결된 물체에 힘은 없고, 이의 디폴트 길이는 자유 길이의 10%이다.

To define a spring or rope, go to Model Setup Meshing Geometry. Click on the spring icon to bring up the Springs and Ropes window. Right click on Springs and Ropes to add a spring or rope. In the combo box for Type, select the type for the spring or rope.

스프링이나 로프를 정의하기 위해 Model Setup Meshing Geometry 로 가서 Springs and Ropes 창을 불러오기 위해 스프링 아이콘을 클릭한다. 스프링이나 로프를 추가하기 위해 Springs and Ropes 를 오른쪽 클릭한다. Type 을위한 combo 상자에서 스프링이나 로프를 선택한다.

  • Linear spring and rope: Click to open the branches for End 1 and End 2 which represent the initial coordinates of the ends of the spring/rope. In each branch, go to Component # and select the index of the moving object which the spring end is connected to. If the end is not connected to any moving component, i.e., is fixed in space, select None. In the X, Y and Z edit boxes, enter the initial coordinates of the spring’s end. Each end can be placed anywhere inside or outside the moving object and the computational domain. Enter Free Length (the length of the spring/rope in the force-free condition), Block Length, Spring Coefficient (required) and Damping Coefficient (default is 0.0). Note that the Block Length is deactivated for rope and extension spring because the former has no block length while the latter always has its block length equal to its free length. By default, the free length is set equal to the initial distance between the two ends.

선형 스프링과 로프: 스프링/로프의 양쪽 끝의 초기좌표를 나타내는 End 1 End 2 를 위한 branches를 열기 위해 클릭한다. 각 branch 에서 Component #로 가서 스프링의 끝이 연결되어 있는 이동체의 색인을 설정한다. 끝이 어떤 이동체에 연결되어 있지 않다면, 즉 공간에 고정되어 있다면 None 을 선택한다. X, Y Z 편집상자에서 스프링 끝의 초기좌표를 입력한다. 각 끝은 이동체나 계산 영역의 내, 외부 어디에도 놓여질 수 있다.

Free Length (힘이없는상태에서의 스프링/로프의 길이), Block Length, Spring Coefficient (필요함) 그리고 Damping Coefficient (디폴트는0.0)를 입력한다. 로프와 인장스프링에서는 Block Length 가 비 활성화됨을 주목하는데 그 이유는 전자는 Block Length 가 없고 후자는 항상 자유 길이와 같은 Block Length 를 가지기 때문이다.

디폴트로 자유길이는 양쪽 끝 사이의 초기길이와 같게 설정된다.

  • Torsion spring: End 1 represents the spring’s end that is attached to a moving object under fixed-axis rotation, and End 2 the end fixed in space. Click to open the branch for End 1. In the combo box for Component #, select the index of the moving object which End 1 is attached to. Then enter Spring Coefficient (required, in unit of [torque]/degree) and Damping Coefficient (default is 0.0). Finally enter the Initial Torque in the input box. The initial torque is the torque of the spring applied on the moving object at t = 0. It is positive if it is in the positive direction of the coordinate axis which the rotation axis of the moving object is parallel to.

비틀림 스프링: End 1은 고정축 회전을 하는 이동체에 연결된 스프링의 끝을 나타내고 End 2는 공간에 고정된 끝을 나타낸다. End 1의 branch 를 열기 위해 클릭한다. Component #를위한 combo 상자에서 End 1 이 연결된 이동체의 색인을 선택한다. 그런 후에 Spring Coefficient ([torque]/degree의 단위로 필요) 와 Damping Coefficient (디폴트는0.0)를 입력한다.

마지막으로 입력 상자에서 Initial Torque 를 넣는다. 초기토크는 t = 0일 때 이동체에 적용된 스프링의 토크이다. 이동체의 회전축이 평행한 좌표축의 양의 방향이면 양의 값이다.

After the simulation is complete, users can display the calculated deformation and force (or torque) of each spring and rope as functions of time. Go to Analyze Probe Data source and check General history. In the variable list under Data variables, find the Spring/rope index followed by spring/rope length extension from free state, spring/rope force and/or spring torque. Then check Output form Text or Graphical and click Render to display the data. Positive/negative values of spring force and length extension mean the linear spring or rope is stretched/compressed relative to its free state and the restoring force is a tension/pressure force. Positive/negative values of the torque of a torsion spring means its deformation angle (a vector) measured from its free state is in the negative/positive direction of the coordinate axis which its axis is parallel to.

모사(simulate)가 끝난 후에 사용자는 시간의 함수로 각 스프링의 계산된 변형과 힘(토크)를 나타낼 수 있다. Analyze Probe Data source 로가서 General history 를 체크한다. Data variables 에 있는 변수 목록에서 spring/rope length extension from free state, spring/rope force 과/또는 spring torque 로 이어지는 스프링/로프의 색인을 찾는다. 그리고 Output form Text 또는 Graphical 를 체크하고 데이터를 나타내기 위해 Render 를 클릭한다.

스프링 힘과 인장길이의 양/음의 값은 선 스프링과 로프가 자유상태에 대해 상대적으로 늘어나거나 압축된 것을 뜻한다. 비틀림스프링 토크의 양/음의값은 축에 평행한 좌표 축의 양/음의 방향에 대해 측정된 변형각(벡터)을 뜻한다.

 

It is noted that the spring/rope calculation is explicitly coupled with GMO motion calculation. If a numerical instability occurs it is recommended that users activate the implicit GMO model, define limited compressibility of fluid, or decrease time step.

스프링/로프 계산은 GMO 운동계산과 외재적으로 결합되어 있음에 주목한다. 수치 불안정성이 발생하면 사용자는 내재적 GMO모델을 활성화하고 유체의 제한적 압축성을 정의하던가 또는 시간간격을 줄이는 것을 추천한다.

Mooring Lines 계류선

The mooring line model allows moving objects with prescribed or coupled motion to be connected to fixed anchors or other moving or non-moving objects via compliant mooring lines. Multiple mooring lines are allowed in one simulation, and their connections to the moving objects are arbitrary. The mooring lines can be taut or slack and may fully or partially rest on sea/river floor. The model considers gravity, buoyancy, fluid drag and tension force on the mooring lines. The mooring lines are assumed to be cylinders with uniform diameter and material distributions, and each line can have its own length, diameter, mass density and other physical properties. The model numerically calculates the full 3D dynamics of the mooring lines and their dynamic interactions with the tethered moving objects.

계류선 모델링은 유연한 계류선을 이용하여 지정 또는 결합운동을 하는 이동체가 고정 닻 또는 다른 이동 또는 고정물체에 연결되는 것을 가능하게 해준다. 다수의 계류선도 한 모사(simulate)내에서 가능하며 이들의 이동체에의 연결은 인위적이다.

계류선은 팽팽하거나 느슨할 수 있고 전체 또는 부분이 해저나 하상에 위치할 수 있다. 이 모델은 계류선에 작용하는 중력, 부력, 유체저항 및 인장력을 고려할 수 있다. 계류선은 일정직경과 균일분포의 원통형으로 가정되고 각 선은 각 길이, 직경, 밀도 및 기타 물리적 물성을 가질 수 있다. 이 모델은 수치적으로 3차원계류선 운동 및 선에 의해 묶여진 이동체와의 동적 상호작용을 계산한다.

 

The model allows the mooring lines to be partially or completely outside the computational domain. When a line is anchored deep in water, depending on the vertical size of the domain, the lower part of the line can be located below the domain bottom where there is no computation of fluid flow. In this case, it is assumed that uniform water current exists below the domain for that part of mooring line, and the corresponding drag force is evaluated based on the uniform deep water velocity. Limitations exist for the model. It does not consider bending stiffness of mooring lines. Interactions between mooring lines are ignored. When simulating mooring line networks, free nodes are not allowed.

이 모델은 계류선이 계산 영역의 완전히 또는 부분적으로 외부에 위치하게 할 수 있다. 계류선은 영역의 심해에 앵커되어 있을 때 수직(세로)크기에 따라 선의 하부는 유동 계산이 없는 영역 바닥에 위치할 수 있다. 이 경우 계류선의 하부가 있는 영역하부에는 균일한 유속이 존재한다고 가정되고 이에 상응하는 유속저항은 균일한 심해유속에 근거하여 계산된다.

이모델은 제약이 있는데 선의 굽힘 강도는 고려하지 않는다. 선간의 상호작용도 무시된다. 선간의 관계를 모사(simulate)활 때 자유접속점은 허용되지 않는다.

 

To define a mooring line, go to Model Setup Meshing & Geometry. Click on the spring icon to bring up the Springs, Ropes and Mooring Lines window. Right click on Springs / Ropes / Mooring Lines to add a mooring line. Click on Mooring Lines Deep Water Velocity and enter x, y and z components of the deep water velocity (default value is zero). Click on Mooring Line # and enter the physical and numerical properties of the mooring line.

계류선을 정의하기위해 Model Setup Meshing & Geometry 로간다. Springs, Ropes and Mooring Lines 창을 불러오기 위해 스프링 아이콘을 클릭한다. 계류선을 추가하기위해 Springs / Ropes / Mooring Lines 에서 오른쪽 클릭을 하고 Mooring Lines Deep Water Velocity 를클릭해서 심해속도의 x, y 및 z 성분을 입력한다(디폴트는0이다). Mooring Line # 를 클릭하고 선의 물리적 및 수치적 물성들을 입력한다.

 

Microfluidics Bibliography

다음은 Microfluidics Bibliography의 기술 문서 모음입니다.
이 모든 논문은 FLOW-3D  결과를 특징으로  합니다. 미세 유체 공정 및 장치 를 성공적으로 시뮬레이션하기 위해 FLOW-3D 를 사용 하는 방법에 대해 자세히 알아보십시오  .

Below is a collection of technical papers in our Microfluidics Bibliography. All of these papers feature FLOW-3D results. Learn more about how FLOW-3D can be used to successfully simulate microfluidic processes and devices.

08-20   Li Yong-Qiang, Dong Jun-Yan and Rui Wei, Numerical simulation for capillary driven flow in capsule-type vane tank with clearances under microgravity, Microgravity Science and Technology, 2020. doi.org/10.1007/s12217-019-09773-z

89-19   Tim Dreckmann, Julien Boeuf, Imke-Sonja Ludwig, Jorg Lumkemann, and Jorg Huwyler, Low volume aseptic filling: impact of pump systems on shear stress, European Journal of Pharmeceutics and Biopharmeceutics, in press, 2019. doi:10.1016/j.ejpb.2019.12.006

88-19   V. Amiri Roodan, J. Gomez-Pastora, C. Gonzalez-Fernandez, I.H. Karampelas, E. Bringas, E.P. Furlani, and I. Ortiz, CFD analysis of the generation and manipulation of ferrofluid droplets, TechConnect Briefs, pp. 182-185, 2019. TechConnect World Innovation Conference & Expo, Boston, Massachussetts, USA, June 17-19, 2019.

55-19     Julio Aleman, Sunil K. George, Samuel Herberg, Mahesh Devarasetty, Christopher D. Porada, Aleksander Skardal, and Graça Almeida‐Porada, Deconstructed microfluidic bone marrow on‐a‐chip to study normal and malignant hemopoietic cell–niche interactions, Small, 2019. doi: 10.1002/smll.201902971

37-19     Feng Lin Ng, Miniaturized 3D fibrous scaffold on stereolithography-printed microfluidic perfusion culture, Doctoral Thesis, Nanyang Technological University, Singapore, 2019.

32-19     Jenifer Gómez-Pastora, Ioannis H. Karampelas, Eugenio Bringas, Edward P. Furlani, and Inmaculada Ortiz, Numerical analysis of bead magnetophoresis from flowing blood in a continuous-flow microchannel: Implications to the bead-fluid interactions, Nature: Scientific Reports, Vol. 9, No. 7265, 2019. doi: 10.1038/s41598-019-43827-x

01-19  Jelena Dinic and Vivek Sharma, Computational analysis of self-similar capillary-driven thinning and pinch-off dynamics during dripping using the volume-of-fluid method, Physics of Fluids, Vol. 31, 2019. doi: 10.1063/1.5061715

75-18   Tobias Ladner, Sebastian Odenwald, Kevin Kerls, Gerald Zieres, Adeline Boillon and Julien Bœuf, CFD supported investigation of shear induced by bottom-mounted magnetic stirrer in monoclonal antibody formulation, Pharmaceutical Research, Vol. 35, 2018. doi: 10.1007/s11095-018-2492-4

53-18   Venoos Amiri Roodan, Jenifer Gómez-Pastora, Aditi Verma, Eugenio Bringas, Inmaculada Ortiz and Edward P. Furlani, Computational analysis of magnetic droplet generation and manipulation in microfluidic devices, Proceedings of the 5th International Conference of Fluid Flow, Heat and Mass Transfer, Niagara Falls, Canada, June 7 – 9, 2018; Paper no. 154, 2018.  doi: 10.11159/ffhmt18.154

35-18   Jenifer Gómez-Pastora, Cristina González Fernández, Marcos Fallanza, Eugenio Bringas and Inmaculada Ortiz, Flow patterns and mass transfer performance of miscible liquid-liquid flows in various microchannels: Numerical and experimental studies, Chemical Engineering Journal, vol. 344, pp. 487-497, 2018. doi: 10.1016/j.cej.2018.03.110

16-18   P. Schneider, V. Sukhotskiy, T. Siskar, L. Christie and I.H. Karampelas, Additive Manufacturing of Microfluidic Components via Wax Extrusion, Biotech, Biomaterials and Biomedical TechConnect Briefs, vol. 3, pp. 162 – 165, 2018.

15-18   J. Gómez-Pastora, I.H. Karampelas, A.Q. Alorabi, M.D. Tarn, E. Bringas, A. Iles, V.N. Paunov, N. Pamme, E.P. Furlani, I. Ortiz, CFD analysis and experimental validation of magnetic droplet generation and deflection across multilaminar flow streams, Biotech, Biomaterials and Biomedical TechConnect Briefs, vol. 3, pp. 182-185, 2018.

14-18   J. Gómez-Pastora, C. González-Fernández, I.H. Karampelas, E. Bringas, E.P. Furlani, and I. Ortiz, Design of Magnetic Blood Cleansing Microdevices through Experimentally Validated CFD Modeling, Biotech, Biomaterials and Biomedical TechConnect Briefs, vol. 3, pp. 170-173, 2018.

10-18   A. Gupta, I.H. Karampelas, J. Kitting, Numerical modeling of the formation of dynamically configurable L2 lens in a microchannel, Biotech, Biomaterials and Biomedical TechConnect Briefs, Vol. 3, pp. 186 – 189, 2018.

17-17   I.H. Karampelas, J. Gómez-Pastora, M.J. Cowan, E. Bringas, I. Ortiz and E.P. Furlani, Numerical Analysis of Acoustophoretic Discrete Particle Focusing in Microchannels, Biotech, Biomaterials and Biomedical TechConnect Briefs 2017, Vol. 3

16-17   J. Gómez-Pastora, I.H. Karampelas, E. Bringas, E.P. Furlani and I. Ortiz, CFD analysis of particle magnetophoresis in multiphase continuous-flow bioseparators, Biotech, Biomaterials and Biomedical TechConnect Briefs 2017, Vol. 3

15-17   I.H. Karampelas, S. Vader, Z. Vader, V. Sukhotskiy, A. Verma, G. Garg, M. Tong and E.P. Furlani, Drop-on-Demand 3D Metal Printing, Informatics, Electronics and Microsystems TechConnect Briefs 2017, Vol. 4

102-16   J. Brindha, RA.G. Privita Edwina, P.K. Rajesh and P.Rani, “Influence of rheological properties of protein bio-inks on printability: A simulation and validation study,” Materials Today: Proceedings, vol. 3, no.10, pp. 3285-3295, 2016. doi: 10.1016/j.matpr.2016.10.010

99-16   Ioannis H. Karampelas, Kai Liu, Fatema Alali, and Edward P. Furlani, Plasmonic Nanoframes for Photothermal Energy Conversion, J. Phys. Chem. C, 2016, 120 (13), pp 7256–7264

98-16   Jelena Dinic and Vivek Sharma, Drop formation, pinch-off dynamics and liquid transfer of simple and complex fluidshttp://meetings.aps.org/link/BAPS.2016.MAR.B53.12, APS March Meeting 2016, Volume 61, Number 2, March 14–18, 2016, Baltimore, Maryland

67-16  Vahid Bazargan and Boris Stoeber, Effect of substrate conductivity on the evaporation of small sessile droplets, PHYSICAL REVIEW E 94, 033103 (2016), doi: 10.1103/PhysRevE.94.033103

57-16   Ioannis Karampelas, Computational analysis of pulsed-laser plasmon-enhanced photothermal energy conversion and nanobubble generation in the nanoscale, PhD Dissertation: Department of Chemical and Biological Engineering, University at Buffalo, State University of New York, July 2016

44-16   Takeshi Sawada et al., Prognostic impact of circulating tumor cell detected using a novel fluidic cell microarray chip system in patients with breast cancer, EBioMedicine, Available online 27 July 2016, doi: 10.1016/j.ebiom.2016.07.027.

39-16   Chien-Hsun Wang, Ho-Lin Tsai, Yu-Che Wu and Weng-Sing Hwang, Investigation of molten metal droplet deposition and solidification for 3D printing techniques, IOP Publishing, J. Micromech. Microeng. 26 (2016) 095012 (14pp), doi: 10.1088/0960-1317/26/9/095012, July 8, 2016

30-16   Ioannis H. Karampelas, Kai Liu and Edward P. Furlani, Plasmonic Nanocages as Photothermal Transducers for Nanobubble Cancer Therapy, Nanotech 2016 Conference & Expo, May 22-25, Washington, DC.

29-16   Scott Vader, Zachary Vader, Ioannis H. Karampelas and Edward P. Furlani, Advances in Magnetohydrodynamic Liquid Metal Jet Printing, Nanotech 2016 Conference & Expo, May 22-25, Washington, DC.

02-16  Stephen D. Hoath (Editor), Fundamentals of Inkjet Printing: The Science of Inkjet and Droplets, ISBN: 978-3-527-33785-9, 472 pages, February 2016 (see chapters 2 and 3 for FLOW-3D results)

125-15   J. Berthier, K.A. Brakke, E.P. Furlani, I.H. Karampelas, V. Poher, D. Gosselin, M. Cubinzolles and P. Pouteau, Whole blood spontaneous capillary flow in narrow V-groove microchannels, Sensors and Actuators B: Chemical, 206, pp. 258-267, 2015.

86-15   Yousub Lee and Dave F. Farson, Simulation of transport phenomena and melt pool shape for multiple layer additive manufacturing, J. Laser Appl. 28, 012006 (2016). doi: 10.2351/1.4935711, published online 2015.

77-15   Ho-Lin Tsai, Weng-Sing Hwang, Jhih-Kai Wang, Wen-Chih Peng and Shin-Hau Chen, Fabrication of Microdots Using Piezoelectric Dispensing Technique for Viscous Fluids, Materials 2015, 8(10), 7006-7016. doi: 10.3390/ma8105355

63-15   Scott Vader, Zachary Vader, Ioannis H. Karampelas and Edward P. Furlani, Magnetohydrodynamic Liquid Metal Jet Printing, TechConnect World Innovation Conference & Expo, Washington, D.C., June 14-17, 2015

46-15   Adwaith Gupta, 3D Printing Multi-Material, Single Printhead Simulation, Advanced Qualification of Additive Manufacturing Materials Workshop, July 20 – 21, 2015, Santa Fe, NM

28-15   Yongqiang Li, Mingzhu Hu, Ling Liu, Yin-Yin Su, Li Duan, and Qi Kang, Study of Capillary Driven Flow in an Interior Corner of Rounded Wall Under MicrogravityMicrogravity Science and Technology, June 2015

20-15   Pamela J. Waterman, Diversity in Medical Simulation Applications, Desktop Engineering, May 2015, pp 22-26,

16-15   Saurabh Singh, Ann Junghans, Erik Watkins, Yash Kapoor, Ryan Toomey, and Jaroslaw Majewski, Effects of Fluid Shear Stress on Polyelectrolyte Multilayers by Neutron Scattering Studies, © 2015 American Chemical Society, DOI: 10.1021/acs.langmuir.5b00037, Langmuir 2015, 31, 2870−2878, February 17, 2015

11-15   Cheng-Han Wu and Weng-Sing Hwang, The effect of process condition of the ink-jet printing process on the molten metallic droplet formation through the analysis of fluid propagation direction, Canadian Journal of Physics, 2015. doi: 10.1139/cjp-2014-0259

03-15 Hanchul Cho, Sivasubramanian Somu, Jin Young Lee, Hobin Jeong and Ahmed Busnaina, High-Rate Nanoscale Offset Printing Process Using Directed Assembly and Transfer of Nanomaterials, Adv. Materials, doi: 10.1002/adma.201404769, February 2015

122-14  Albert Chi, Sebastian Curi, Kevin Clayton, David Luciano, Kameron Klauber, Alfredo Alexander-Katz, Sebastián D’hers and Noel M Elman, Rapid Reconstitution Packages (RRPs) implemented by integration of computational fluid dynamics (CFD) and 3D printed microfluidics, Research Gate, doi: 10.1007/s13346-014-0198-7, July 2014

113-14 Cihan Yilmaz, Arif E. Cetin, Georgia Goutzamanidis, Jun Huang, Sivasubramanian Somu, Hatice Altug, Dongguang Wei and Ahmed Busnaina, Three-Dimensional Crystalline and Homogeneous Metallic Nanostructures Using Directed Assembly of Nanoparticles, 10.1021/nn500084g, © 2014 American Chemical Society, April 2014

110-14 Koushik Ponnuru, Jincheng Wu, Preeti Ashok, Emmanuel S. Tzanakakis and Edward P. Furlani, Analysis of Stem Cell Culture Performance in a Microcarrier Bioreactor System, Nanotech, Washington, D.C., June 15-18, 2014

109-14   Ioannis H. Karampelas, Young Hwa Kim and Edward P. Furlani, Numerical Analysis of Laser Induced Photothermal Effects using Colloidal Plasmonic Nanostructures, Nanotech, Washington, D.C., June 15-18, 2014

108-14   Chenxu Liu, Xiaozheng Xue and Edward P. Furlani, Numerical Analysis of Fully-Coupled Particle-Fluid Transport and Free-Flow Magnetophoretic Sorting in Microfluidic Systems, Nanotech, Washington, D.C., June 15-18, 2014

95-14   Cheng-Han Wu, Weng-Sing Hwang, The effect of the echo-time of a bipolar pulse waveform on molten metallic droplet formation by squeeze mode piezoelectric inkjet printing, Accepted November 2014, Microelectronics Reliability (2014) , © 2014 Elsevier Ltd. All rights reserved.

85-14   Sudhir Srivastava, Lattice Boltzmann method for contact line dynamics, ISBN: 978-90-386-3608-5, Copyright © 2014 S. Srivastava

61-14   Chenxu Liu, A Computational Model for Predicting Fully-Coupled Particle-Fluid Dynamics and Self-Assembly for Magnetic Particle Applications, Master’s Thesis: State University of New York at Buffalo, 2014, 75 pages; 1561583, http://gradworks.umi.com/15/61/1561583.html

41-14 Albert Chi, Sebastian Curi, Kevin Clayton, David Luciano, Kameron Klauber, Alfredo Alexander-Katz, Sebastian D’hers, and Noel M. Elman, Rapid Reconstitution Packages (RRPs) implemented by integration of computational fluid dynamics (CFD) and 3D printed microfluidics, Drug Deliv. and Transl. Res., DOI 10.1007/s13346-014-0198-7, # Controlled Release Society 2014. Available for purchase online at SpringerLink.

21-14  Suk-Hee Park, Ung Hyun Koh, Mina Kim, Dong-Yol Yang, Kahp-Yang Suh and Jennifer Hyunjong Shin, Hierarchical multilayer assembly of an ordered nanofibrous scaffold via thermal fusion bonding, Biofabrication 6 (2014) 024107 (10pp), doi:10.1088/1758-5082/6/2/024107, IOP Publishing, 2014. Available for purchase online at IOP.

17-14   Vahid Bazargan, Effect of substrate cooling and droplet shape and composition on the droplet evaporation and the deposition of particles, Ph.D. Thesis: Department of Mechanical Engineering, The University of British Columbia, March 2014, © Vahid Bazargan, 2014

73-13  Oliver G. Harlen, J. Rafael Castrejón-Pita, and Arturo Castrejon-Pita, Asymmetric Detachment from Angled Nozzles Plates in Drop-on Demand Inkjet Printing, NIP & Digital Fabrication Conference, 2013 International Conference on Digital Printing Technologies. Pages 253-549, pp. 277-280(4)

63-13  Fatema Alali, Ioannis H. Karampelas, Young Hwa Kim, and Edward P. Furlani, Photonic and Thermofluidic Analysis of Colloidal Plasmonic Nanorings and Nanotori for Pulsed-Laser Photothermal ApplicationsJ. Phys. Chem. C, Article ASAP, DOI: 10.1021/jp406986y, Copyright © 2013 American Chemical Society, September 2013.

25-13  Sudhir Srivastava, Theo Driessen, Roger Jeurissen, Herma Wijshoff, and Federico Toschi, Lattice Boltzmann Method to Study the Contraction of a Viscous Ligament, International Journal of Modern Physics © World Scientific Publishing Company, May 2013.

11-13  Li-Chieh Hsu, Yong-Jhih Chen, Jia-Huang Liou, Numerical Investigation in the Factors on the Pool Boiling, Applied Mechanics and Materials Vol. 311 (2013) pp 456-461, © (2013) Trans Tech Publications, Switzerland, doi:10.4028/www.scientific.net/AMM.311.456. Available for purchase online at Scientific.Net.

10-13 Pamela J. Waterman, CFD: Shaping the Medical World, Desktop Engineering, April 2013. Full article available online at Desktop Engineering.

90-12 Charles R. Ortloff and Martin Vogel, Spray Cooling Heat Transfer- Test and CFD Analysis, Electronics Cooling, June 2012. Available online at Electronics Cooling.

79-12    Daniel Parsaoran Siregar, Numerical simulation of evaporation and absorption of inkjet printed droplets, Ph.D. Thesis: Technische Universiteit Eindhoven, September 18, 2012, Copyright 2012 by D.P. Siregar, ISBN: 978-90-386-3190-5.

71-12   Jong-hyeon Chang, Kyu-Dong Jung, Eunsung Lee, Minseog Choi, Seungwan Lee, and Woonbae Kim, Varifocal liquid lens based on microelectrofluidic technology, Optics Letters, Vol. 37, Issue 21, pp. 4377-4379 (2012) http://dx.doi.org/10.1364/OL.37.004377

70-12   Jong-hyeon Chang, Kyu-Dong Jung, Eunsung Lee, Minseog Choi, and Seunwan Lee, Microelectrofluidic Iris for Variable ApertureProc. SPIE 8252, MOEMS and Miniaturized Systems XI, 82520O (February 9, 2012); doi:10.1117/12.906587

69-12   Jong-hyeon Chang, Eunsung Lee, Kyu-Dong Jung, Seungwan Lee, Minseog Choi, and  Woonbae Kim, Microelectrofluidic Lens for Variable CurvatureProc. SPIE 8486, Current Developments in Lens Design and Optical Engineering XIII, 84860X (October 11, 2012); doi:10.1117/12.925852.

61-12  Biddut Bhattacharjee, Study of Droplet Splitting in an Electrowetting Based Digital Microfluidic System, Thesis: Doctor of Philosophy in the College of Graduate Studies (Applied Sciences), The University of British Columbia, September 2012, © Biddut Bhattacharjee.

55-12 Hejun Li, Pengyun Wang, Lehua Qi, Hansong Zuo, Songyi Zhong, Xianghui Hou, 3D numerical simulation of successive deposition of uniform molten Al droplets on a moving substrate and experimental validation, Computational Materials Science, Volume 65, December 2012, Pages 291–301. Available for purchase online at SciVerse.

54-12   Edward P. Furlani, Anthony Nunez, Gianmarco Vizzeri, Modeling Fluid Structure-Interactions for Biomechanical Analysis of the Human Eye, Nanotech Conference & Expo, June 18-21, 2012, Santa Clara, CA.

53-12   Xinyun Wu, Richard D. Oleschuk and Natalie M. Cann, Characterization of microstructured fibre emitters in pursuit of improved nano electrospray ionization performance, The Royal Society of Chemistry 2012, http://pubs.rsc.org, DOI: 10.1039/c2an35249d, May 2012

25-12    Edward P. Furlani, Ioannis H. Karampelas and Qian Xie, Analysis of Pulsed Laser Plasmon-assisted Photothermal Heating and Bubble Generation at the Nanoscale, Lab on a Chip, 10.1039/C2LC40495H, Received 01 May 2012, Accepted 07 Jun 2012. First published on the web 13 Jun 2012.

22-12  R.A. Sultanov, D. Guster, Numerical Modeling and Simulations of Pulsatile Human Blood Flow in Different 3D-Geometries, Book chapter #21 in Fluid Dynamics, Computational Modeling and Applications (2012), ISBN: 978-953-51-0052-2, p. 475 [18 pages]. Available online at INTECH.

21-12  Guo-Wei Huang, Tzu-Yi Hung, and Chin-Tai Chen, Design, Simulation, and Verification of Fluidic Light-Guide Chips with Various Geometries of Micro Polymer Channels, NEMS 2012, Kyoto, Japan, March 5-8, 2012. Available for purchase online at IEEE.

103-11   Suk-Hee Park, Development of Three-Dimensional Scaffolds containing Electrospun Nanofibers and their Applications to Tissue Regeneration, Ph.D. Thesis: School of Mechanical, Aersospace and Systems Engineering, Division of Mechanical Engineering, KAIST, 2011.

81-11   Xinyun Wu, Modeling and Characterization of Microfabricated Emitters-In Pursuit of Improved ESI-MS Performance, thesis: Department of Chemistry, Queen’s University, December 2011, Copyright © Xinyun Wu, 2011

79-11  Cong Lu, A Cell Preparation Stage for Automatic Cell Injection, thesis: Graduate Department of Mechanical and Industrial Engineering, University of Toronto, Copyright © Cong Lu, 2011

77-11 Ge Bai, W. Thomas Leach, Computational fluid dynamics (CFD) insights into agitation stress methods in biopharmaceutical development, International Journal of Pharmaceutics, Available online 8 December 2011, ISSN 0378-5173, 10.1016/j.ijpharm.2011.11.044. Available online at SciVerse.

72-11  M.R. Barkhudarov, C.W. Hirt, D. Milano, and G. Wei, Comments on a Comparison of CFD Software for Microfluidic Applications, Flow Science Technical Note #93, FSI-11-TN93, December 2011

45-11  Chang-Wei Kang, Jiak Kwang Tan, Lunsheng Pan, Cheng Yee Low and Ahmed Jaffar, Numerical and experimental investigations of splat geometric characteristics during oblique impact of plasma spraying, Applied Surface Science, In Press, Corrected Proof, Available online 20 July 2011, ISSN 0169-4332, DOI: 10.1016/j.apsusc.2011.06.081. Available to purchase online at SciVers

33-11  Edward P. Furlani, Mark T. Swihart, Natalia Litchinitser, Christopher N. Delametter and Melissa Carter, Modeling Nanoscale Plasmon-assisted Bubble Nucleation and Applications, Nanotech Conference and Expo 2011, Boston, MA, June 13-16, 2011

32-11  Lu, Cong and Mills, James K., Three cell separation design for realizing automatic cell injection, Complex Medical Engineering (CME), 2011 IEEE/ICME, pp: 599 – 603, Harbin, China, 10.1109/ICCME.2011.5876811, June 2011. Available online at IEEEXplore.

25-11 Issam M. Bahadur, James K. Mills, Fluidic vacuum-based biological cell holding device with piezoelectrically induced vibration, Complex Medical Engineering (CME), 2011 IEEE/ICME International Conference on, 22-25 May 2011, pp: 85 – 90, Harbin, China. Available online at: IEEE Xplore.

14-11  Edward P. Furlani, Roshni Biswas, Alexander N. Cartwright and Natalia M. Litchinitser, Antiresonant guiding optofluidic biosensor, doi:10.1016/j.optcom.2011.04.014, Optics Communication, April 2011

05-11 Hyeju Eom and Keun Park, Integrated numerical analysis to evaluate replication characteristics of micro channels in a locally heated mold by selective induction, International Journal of Precision Engineering and Manufacturing, Volume 12, Number 1, 53-60, DOI: 10.1007/s12541-011-0007-x, 2011. Available online at: SpringerLink.

70-10  I.N. Volnov, V.S. Nagornyi, Modeling Processes for Generation of Streams of Monodispersed Fluid Droplets in Electro-inkjet Applications, Science and Technology News, St. Petersburg State Polytechnic University, 4, pp 294-300, 2010. In Russian.

62-10  F. Mobadersani, M. Eskandarzade, S. Azizi and S. Abbasnezhad, Effect of Ambient Pressure on Bubble Growth in Micro-Channel and Its Pumping Effect, ESDA2010-24436, pp. 577-584, doi:10.1115/ESDA2010-24436, ASME 2010 10th Biennial Conference on Engineering Systems Design and Analysis (ESDA2010), Istanbul, Turkey, July 12–14, 2010. Available online at the ASME Digital Library.

58-10 Tsung-Yi Ho, Jun Zeng, and Chakrabarty, K, Digital microfluidic biochips: A vision for functional diversity and more than moore, Computer-Aided Design (ICCAD), 2010 IEEE/ACM International Conference on, DOI: 10.1109/ICCAD.2010.5654199, © IEEE, November 2010. Available online at IEEE Explore.

51-10  Regina Bleul, Marion Ritzi-Lehnert, Julian Höth, Nico Scharpfenecker, Ines Frese, Dominik Düchs, Sabine Brunklaus, Thomas E. Hansen-Hagge, Franz-Josef Meyer-Almes, Klaus S. Drese, Compact, cost-efficient microfluidics-based stopped-flow device, Anal Bioanal Chem, DOI 10.1007/s00216-010-4446-5, Available online at Springer, November 2010

22-10    Krishendu Chakrabarty, Richard B. Fair and Jun Zeng, Design Tools for Digital Microfluidic Biochips Toward Functional Diversification and More than Moore, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Vol. 29, No. 7, July 2010

14-10 E. P. Furlani and M. S. Hanchak, Nonlinear analysis of the deformation and breakup of viscous microjets using the method of lines, International Journal for Numerical Methods in Fluids (2010), © 2010 John Wiley & Sons, Ltd., Published online in Wiley InterScience. DOI: 10.1002/fld.2205

55-09 R.A. Sultanov, and D. Guster, Computer simulations of  pulsatile human blood flow through 3D models of the human aortic arch, vessels of simple geometry and a bifurcated artery, Proceedings of the 31st Annual International Conference of the IEEE EMBS (Engineering in Medicine and Biology Society), Minneapolis, September 2-6, 2009, p.p. 4704-4710.

30-09 Anurag Chandorkar and Shayan Palit, Simulation of Droplet Dynamics and Mixing in Microfluidic Devices using a VOF-Based Method, Sensors & Transducers journal, ISSN 1726-5479 © 2009 by IFSA, Vol.7, Special Issue “MEMS: From Micro Devices to Wireless Systems,” October 2009, pp. 136-149.

13-09 E.P. Furlani, M.C. Carter, Analysis of an Electrostatically Actuated MEMS Drop Ejector, Presented at Nanotech Conference & Expo 2009, Houston, Texas, USA, May 3-7, 2009

12-09 A. Chandorkar, S. Palit, Simulation of Droplet-Based Microfluidics Devices Using a Volume-of-Fluid Approach, Presented at Nanotech Conference & Expo 2009, Houston, Texas, USA, May 3-7, 2009

3-09 Christopher N. Delametter, FLOW-3D Speeds MEMS Inkjet Development, Desktop Engineering, January 2009

42-08  Tien-Li Chang, Jung-Chang Wang, Chun-Chi Chen, Ya-Wei Lee, Ta-Hsin Chou, A non-fluorine mold release agent for Ni stamp in nanoimprint process, Microelectronic Engineering 85 (2008) 1608–1612

26-08 Pamela J. Waterman, First-Pass CFD Analyses – Part 2, Desktop Engineering, November 2008

09-08 M. Ren and H. Wijshoff, Thermal effect on the penetration of an ink droplet onto a porous medium, Proc. Eurotherm2008 MNH, 1 (2008)

04-08 Delametter, Christopher N., MEMS development in less than half the time, Small Times, Online Edition, May 2008

02-08 Renat A. Sultanov, Dennis Guster, Brent Engelbrekt and Richard Blankenbecler, 3D Computer Simulations of Pulsatile Human Blood Flows in Vessels and in the Aortic Arch – Investigation of Non-Newtonian Characteristics of Human Blood, The Journal of Computational Physics, arXiv:0802.2362v1 [physics.comp-ph], February 2008

01-08 Herman Wijshoff, thesis: University of Twente, Structure- and fluid dynamics in piezo inkjet printheads, ISBN 978-90-365-2582-4, Venlo, The Netherlands January 2008.

30-07 A. K. Sen, J. Darabi, and D. R. Knapp, Simulation and parametric study of a novel multi-spray emitter for ESI–MS applications, Microfluidics and Nanofluidics, Volume 3, Number 3, June 2007, pp. 283-298(16)

28-07 Dan Soltman and Vivek Subramanian, Inkjet-Printed Line Morphologies and Temperature Control of the Coffee Ring Effect, Langmuir; 2008; ASAP Web Release Date: 16-Jan-2008; (Research Article) DOI: 10.1021/la7026847

23-07 A K Sen and J Darabi, Droplet ejection performance of a monolithic thermal inkjet print head, Journal of Micromechanical and Microengineering,vol.17, pp.1420-1427 (2007) doi:10.1088/0960-1317/17/8/002; Abstract only.

18-07 Herman Wisjhoff, Better Printheads Via Simulation, Desktop Engineering, October 2007, Vol. 13, Issue 2

17-07 Jos de Jong, Ph.D. Thesis: University of Twente, Air entrapment in piezo inkjet printing, ISBN 978-90-365-2483-4, April 2007

15-07 Krishnendu Chakrabarty and Jun Zeng, (Ed.), Design Automation Methods and Tools for Microfluidics-Based Biochips, Springer, September 2006.

14-07 Fei Su and Jun Zeng, Computer-aided design and test for digital microfluidics, IEEE Design & Test of Computers, 24(1), 2007, 60-70.

13-07 Jun Zeng, Modeling and simulation of electrified droplets and its application to computer-aided design of digital microfluidics, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 25(2), 2006, 224-233.

12-07 Krishnendu Chakrabarty and Jun Zeng, (2005), Automated top-down design for microfluidic biochips, ACM Journal on Emerging Technologies in Computing Systems, 1(3), 2005, 186–223.

01-07 Wijshoff, Herman, Drop formation mechanisms in piezo-acoustic inkjet, NSTI-Nanotech 2007, ISBN 1420061844 Vol. 3, 2007)

23-06 John J. Uebbing, Stephan Hengstler, Dale Schroeder, Shalini Venkatesh, and Rick Haven, Heat and Fluid Flow in an Optical Switch Bubble, Journal of Microelectromechanical Systems, Vol. 15, No. 6, December 2006

21-06 Wijshoff, Herman, Manipulating Drop Formation in Piezo Acoustic Inkjet, Proc. IS&T’s NIP22, 79 (2006)

20-06 J. de Jong, H. Reinten, M. van den Berg, H. Wijshoff, M. Versluis, G. de Bruin, A. Prosperetti and D. Lohse, Air entrapment in piezo-driven inkjet printheads, J. Acoust. Soc. Am. 120(3), 1257 (2006)

11-06 A. K. Sen, J. Darabi, D. R. Knapp and J. Liu, Modeling and Characterization of a Carbon Fiber Emitter for Electrospray Ionization, 1 MEMS and Microsystems Laboratory, Department of Mechanical Engineering, University of South Carolina, 300 Main Street, Columbia, SC 29208, USA, 2 Department of Pharmacology, Medical University of South Carolina, Charleston, SC

5-06 E. P. Furlani, B. G. Price, G. Hawkins, and A. G. Lopez, Thermally Induced Marangoni Instability of Liquid Microjets with Application to Continuous Inkjet Printing, Proceedings of NSTI Nanotech Conference 2006, Vol. 2, pp 534-537.

28-05 O B Fawehinmi, P H Gaskell, P K Jimack, N Kapur, and H M Thompson, A combined experimental and computational fluid dynamics analysis of the dynamics of drop formation, May 2005. DOI: 10.1243/095440605X31788

5-05 E. P. Furlani, Thermal Modulation and Instability of Newtonian Liquid Microjets, presented at Nanotech 2005, Anaheim, CA, May 8-12, 2005.

1-05 C.W. Hirt, Electro-Hydrodynamics of Semi-Conductive Fluids: With Application to Electro-Spraying, Flow Science Technical Note #70, FSI-05-TN70

19-04 G. F. Yao, Modeling of Electroosmosis Without Resolving Physics Inside a Electric Double Layer, Flow Science Technical Note (FSI-04-TN69)

12-04 Jun Zeng and Tom Korsmeyer, Principles of Droplet Electrohydrodynamics for Lab-on-a-Chip, Lab. Chip. Journal, 2004, 4(4), 265-277

9-04 Constantine N. Anagnostopoulos, James M. Chwalek, Christopher N. Delametter, Gilbert A. Hawkins, David L. Jeanmaire, John A. Lebens, Ali Lopez, and David P. Trauernicht, Micro-Jet Nozzle Array for Precise Droplet Metering and Steering Having Increased Droplet Deflection, Proceedings of the 12th International Conference on Solid State Sensors, Actuators and Microsystems, sponsored by IEEE, Boston, June 8-12, 2003, pp. 368-71

8-04 Christopher N. Delametter, David P. Trauernicht, James M. Chwalek, Novel Microfluidic Jet Deflection – Significant Modeling Challenge with Great Application Potential, Technical Proceedings of the 2002 International Conference on Modeling and Simulation of Microsystems sponsored by NSTI, San Juan, Puerto Rico, April 21-25, 2002, pp. 44-47

6-04 D. Vadillo*, G. Desie**, A Soucemarianadin*, Spreading Behavior of Single and Multiple Drops, *Laboratoire des Ecoulements Geophysiques et Industriels (LEGI), and **AGFA-Gevaert Group N.V., XXI ICTAM, 15-21 August 2004, Warsaw, Poland

2-04 Herman Wijshoff, Free Surface Flow and Acousto-Elastic Interaction in Piezo Inkjet, Nanotech 2004, sponsored by the Nano Science & Technology Institute, Boston, MA, March 2004

30-03 D Souders, I Khan and GF Yao, Alessandro Incognito, and Matteo Corrado, A Numerical Model for Simulation of Combined Electroosmotic and Pressure Driven Flow in Microdevices, 7th International Symposium on Fluid Control, Measurement and Visualization

27-03 Jun Zeng, Daniel Sobek and Tom Korsmeyer, Electro-Hydrodynamic Modeling of Electrospray Ionization – CAD for a µFluidic Device-Mass Spectrometer Interface, Agilent Technologies Inc, paper presented at Transducers 2003, June 03 Boston (note: Reference #10 is to FLOW-3D)

17-03 John Uebbing, Switching Fiber-optic Circuits with Microscopic Bubbles, Sensors Magazine, May 2003, Vol 20, No 5, p 36-42

16-03 CFD Speeds Development of MEMS-based Printing Technology, MicroNano Magazine, June 2003, Vol 8, No 6, p 16

3-03 Simulation Speeds Design of Microfluidic Medical Devices, R&D Magazine, March 2003, pp 18-19

1-03 Simulations Help Microscopic Bubbles Switch Fiber-Optic Circuits, Agilent Technologies, Fiberoptic Product News, January 2003, pp 22-23

27-02 Feng, James Q., A General Fluid Dynamic Analysis of Drop Ejection in Drop-on-Demand Ink Jet Devices, Journal of Imaging Science and Technology®, Volume 46, Number 5, September/October 2002

1-02 Feixia Pan, Joel Kubby, and Jingkuang Chen, Numerical Simulation of Fluid Structure Interaction in a MEMS Diaphragm Drop Ejector, Xerox Wilson Research Center, Institute of Physics Publishing, Journal of Micromechanics and Microengineering, 12 (2002), PII: SO960-1317(02)27439-2, pp. 70-76

48-01   Rainer Gruber, Radial Mass Transfer Enhancement in Bubble-Train Flow, PhD thesis in Engineering Sciences, Rheinisch- Westf alischen Technische Hochschule Aachen, December 2001.

34-01 Furlani, E.P., Delametter, C.N., Chwalek, J.M., and Trauernicht, D., Surface Tension Induced Instability of Viscous Liquid Jets, Fourth International Conference on Modeling and Simulation of Microsystems, April 2001

12-01 C. N. Delametter, Eastman Kodak Company, Micro Resolution, Mechanical Engineering, Col 123/No 7, July 2001, pp 70-72

11-01 C. N. Delametter, Eastman Kodak Company, Surface Tension Induced Instability of Viscous Liquid Jets, Technical Proceeding of the Fourth International Conference on Modeling and Simulation of Microsystems, April 2001

9-01 Aman Khan, Unipath Limited Research and Development, Effects of Reynolds Number on Surface Rolling in Small Drops, PVP-Col 431, Emerging Technologies for Fluids, Structures and Fluids, Structures and Fluid Structure Interaction — 2001

2-00 Narayan V. Deshpande, Significance of Inertance and Resistance in Fluidics of Thermal Ink-Jet Transducers, Journal of Imaging Science and Technology, Volume 40, Number 5, Sept./Oct. 1996, pp.457-461

4-98 D. Deitz, Connecting the Dots with CFD, Mechanical Engineering Magazine, pp. 90-91, March 1998

14-94 M. P. O’Hare, N. V. Deshpande, and D. J. Drake, Drop Generation Processes in TIJ Printheads, Xerox Corporation, Adv. Imaging Business Unit, IS&T’s Tenth International Congress on Advances in Non-Impact Printing, Tech. 1994

14-92 Asai, A.,Three-Dimensional Calculation of Bubble Growth and Drop Ejection in a Bubble Jet Printer, Journal of Fluids Engineering Vol. 114 December 1992:638-641

Aerospace Bibliography

아래는 항공 우주 분야에 대한 기술 문서 모음입니다.
이 모든 논문은 FLOW-3D  결과를 포함하고 있습니다. FLOW-3D를 사용하여 항공 우주 산업을 위한 응용 프로그램을 성공적으로 시뮬레이션  하는 방법에 대해 자세히 알아보십시오.

Aerospace Bibliography

Below is a collection of technical papers in our Aerospace Bibliography. All of these papers feature FLOW-3D results. Learn more about how  FLOW-3D can be used to successfully simulate applications for the Aerospace Industry.

08-20   Li Yong-Qiang, Dong Jun-Yan and Rui Wei, Numerical simulation for capillary driven flow in capsule-type vane tank with clearances under microgravity, Microgravity Science and Technology, 2020. doi.org/10.1007/s12217-019-09773-z

107-19   Martin Konopka, Extension of a standard flow solver for simulating phase change in cryogenic tanks, Journal of Thermophysics and Heat Transfer, 33.3, 2019. doi.org/10.2514/1.T5546

79-19   Baotang Zhuang, Yong Li, Jintao Liu, and Wei Rui, Numerical simulation of fluid transport along parallel vanes for vane type propellant tanks, Microgravity Science and Technology, pp. 1-10, 2019. doi:10.1007/s12217-019-09746-2

54-19     Robert E. Manning, Ian Ballinger, Manoj Bhatia, and Mack Dowdy, Design of the Europa Clipper propellant management device, AIAA Propulsion and Energy 2019 Forum, Indianapolis, Indiana, August 19-22, 2019. doi:10.2514/6.2019-3858

48-19     Lei Wang, Tian Yan, Jiaojiao Wang, Shixuan Ye, Yanzhong Li, Rui Zhuan, and Bin Wang, CFD investigation on thermodynamic characteristics in liquid hydrogen tank during successive varied-gravity conditions, Cryogenics, Vol. 103, 2019. doi:10.1016/j.cryogenics.2019.102973

01-18   Martin Konopka, Extension of a Standard Flow Solver for Simulating Phase Change in Cryogenic Tanks, 018 AIAA Aerospace Sciences Meeting, AIAA SciTech Forum, (AIAA 2018-1818), https://doi.org/10.2514/6.2018-1818

69-16   Philipp Behruzi and Francesco De Rose, Coupling sloshing, GNC and rigid body motions during ballistic flight phases, Propulsion and Energy Forum, 52nd AIAA/SAE/ASEE Joint Propulsion Conference, July 25-27, 2016, Salt Lake City, UT.

55-16   Martin Konopka, Peter Noeding, Jörg Klatte, Philipp Behruzi, Jens Gerstmann, Anton Stark, Nicolas Darkow, Analysis of LN2 Filling, Draining, Stratification and Sloshing Experiments, 46th AIAA Fluid Dynamics Conference, Washington, D.C.

95-15   D Frank, Control of fluid mass center in the Gravity Probe B space mission Dewar, © 2015 IOP Publishing Ltd, Classical and Quantum Gravity, Volume 32, Number 22, November 17, 2015

58-15   Diana Gaulke and Michael E. Dreyer, CFD Simulation of Capillary Transport of Liquid Between Parallel Perforated Plates using FLOW-3D, Microgravity Science and Technology, August 2015

55-15   Sebastian Schmitt and Michael E. Dreyer, Free Surface Oscillations of Liquid Hydrogen in Microgravity Conditions, Cryogenics, doi:10.1016/j.cryogenics.2015.07.004, July 26, 2015

53-15   Jeffrey Moder and Kevin Breisacher, Preliminary Simulations of Ullage Dynamics in Microgravity during Jet Mixing Portion of the Tank Pressure Control Experiments, 51st AIAA/SAE/ASEE Joint Propulsion Conference, 2015

52-15   Philipp Behruzi, Diana Gaulke, Joerg Klatte, Nicolas Fries, Development of the MPCV ESM propellant tanks, 51st AIAA/SAE/ASEE Joint Propulsion Conference, 2015

51-15   Grant O. Musgrove and Shane B. Coogan, Validation and Rules-of-Thumb for Computational Predictions of Liquid Slosh Dynamics, 51st AIAA/SAE/ASEE Joint Propulsion Conference, 2015

23-15   Eckart Fuhrmann, Michael Dreyer, Steffen Basting, and Eberhard Bänsch, Free surface deformation and heat transfer by thermocapillary convection, Heat and Mass Transfer, June 2015, © SpringerLink

09-15   Zhicheng Zhou and Hua Huang, Constraint Surface Model for Large Amplitude Sloshing of the spacecraft with Multiple Tanks, Acta Astronautica, http://dx.doi.org/10.1016/j.actaastro.2015.02.023

43-14   C. Ludwig and M.E. Dreyer, Investigations on thermodynamic phenomena of the active-pressurization process of a cryogenic propellant tankCryogenics (2014), doi: http://dx.doi.org/10.1016/j.cryogenics.2014.05.005.

40-14   M. Berci, S. Mascetti; A. Incognito, P. H. Gaskell, and V. V. Toropov, Dynamic Response of Typical Section Using Variable-Fidelity Fluid Dynamics and Gust-Modeling Approaches—With Correction Methods, Journal of Aerospace Engineering, © ASCE, ISSN 0893-1321/04014026(20), May 2014.

22-14  M. Lazzarin, M. Biolo, A. Bettella, M. Manente, R. DaForno, and D. Pavarin, EUCLID satellite: Sloshing model development through computational fluid dynamics, Aerospace Science and Technology, JID:AESCTE AID:3040 /FLA, Available online 12 April 2014.

75-13   Carina Ludwig and Michael Dreyer, Analyses of Cryogenic Propellant Tank Pressurization based upon Experiments and Numerical Simulations, 5TH EUROPEAN CONFERENCE FOR AERONAUTICS AND SPACE SCIENCES (EUCASS), Munich, Germany, 1-5 July 2013

49-13 Damien Theureau, Astrium; Jean Mignot, French Space Agency (CNES); Sebastien Tanguy, Fluid Mechanics Institute of Toulouse (IMFT), Integration of low g sloshing models with spacecraft attitude control simulators, Chapter DOI: 10.2514/6.2013-4961, August 2013.

44-13  Philipp Behruzi, Jörg Klatte and Gaston Netter, Passive Phase Separation in Cryogenic Upper Stage Tanks, 49th AIAA/ASME/SAE/ASEE Joint Propulsion Conference, July 14 – 17, 2013, San Jose, CA.

43-13  Philipp Behruzi, Jörg Klatte, Nicolas Fries, Andreas Schütte, Burkhard Schmitz and Horst Köhler, Cryogenic Propellant Management Sounding Rocket Experiments on TEXUS 48, 49th AIAA/ASME/SAE/ASEE Joint Propulsion Conference, July 14 – 17, 2013, San Jose, CA.

113-12  M. Lazzarin, M. Biolo, A. Bettella, and R. Da Forno, EUCLID Mission: Theoretical Sloshing Model and CFD Comparison, 48th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 30 July – 01 August 2012, Atlanta, Georgia

34-12  N. Fries , P. Behruzi, T. Arndt, M. Winter, G. Netter, U. Renner, Modelling of fluid motion in spacecraft propellant tanks – Sloshing, Space Propulsion 2012 conference, 7th-10th May 2012, Bordeaux

55-11   P. Behruzi, F. de Rose, P. Netzlaf, H. Strauch, Ballistic Phase Management for Cryogenic Upper Stages, DGLR Conference, Bremen, Germany, 2011

11-11 Philipp Behruzi, Hans Strauch, and Francesco de Rose, Coasting Phase Propellant Management for Upper Stages, 38th COSPAR Scientific Assembly, 18-15 July 2010, Bremen, Germany. PowerPoint presentation.

73-10    Amber Bakkum, Kimberly Schultz, Jonathan Braun, Kevin M Crosby, Stephanie Finnvik, Isa Fritz, Bradley Frye, Cecilia Grove, Katelyn Hartstern, Samantha Kreppel and Emily Schiavone, Investigation of Propellant Sloshing and Zero Gravity Equilibrium for the Orion Service Module Propellant Tanks, Wisconsin Space Conference, Yingst, R. A., & Wisconsin Space Grant Consortium. (2010). Dawn of a new age: 20th Annual Wisconsin Space Conference, August 19-20, 2010. Green Bay, Wis: Wisconsin Space Grant Consortium; University of Wisconsin-Green Bay.

35-10   Kevin Breisacher and Jeffrey Moder, Computational Fluid Dynamics (CFD) Simulations of Jet Mixing in Tanks of Different Scales, NASA/TM—2010-216749

21-10 Berci M., Mascetti S., Incognito A., Gaskell P.H., Toropov V.V., Gust Response of a Typical Section Via CFD and Analytical Solutions, V European Conference on Computational Fluid Dynamics, ECCOMAS CFD 2010, Lisbon, Portugal, 14-17 June 2010 (A companion PowerPoint presentation in pdf format is available upon request)

49-08   Jens Gerstmann, Michael Dreyer, et al., Dependency of the apparent contact angle on nonisothermal conditions, PHYSICS OF FLUIDS 20, 042101 (2008)

35-07 N. Fries, K. Odic and M. Dreyer, Wicking of Perfectly Wetting Liquids into a Metallic Mesh, Proceedings of the 2nd International Conference on Porous Media and its Applications in Science and Engineering, ICPM2, Kauai, Hawaii, USA, June 17-21, 2007

08-07 Gary Grayson, Alfredo Lopez, Frank Chandler, Leon Hastings, Ali Hedayat, and James Brethour, CFD Modeling of Helium Pressurant Effects on Cryogenic Tank Pressure Rise Rates in Normal Gravity, 43rd AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit, © 2007 by The Boeing Company. Published by the American Institute of Aeronautics and Astronautics, Inc. with permission. AIAA 2007-5524, 8 – 11 July 2007

34-06 Phillipp Behruzi, Mark Michaelis and Gaël Khimeche, Behavior of the Cryogenic Propellant Tanks during the First Flight of the Ariane 5 ESC-A Upper Stage, 42nd AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 9-12 July 2006, Sacramento, California, © 2006 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

12-06 G. D. Grayson, A. Lopez, F. O. Chandler, L. J. Hastings, S. P. Tucker, Cryogenic Tank Modeling for the Saturn AS-203 Experiment, AIAA 2006-5258, presented at the 42nd AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit, July 9-12, 2006, Sacramento, CA.

29-02 O. Bayle, V. L’Hullier, M. Ganet, P. Delpy, J.L. Francart and D. Paris, Influence of the ATV Propellant Sloshing on the GNC Performance, AIAA Guidance, Navigation, and Control Conference and Exhibit, Monterey, California, 5-8 August 2002, © 2002 by EADS Launch Vehicles

42-01 C. Figus and L. Ounougha, Correlations between Neutral Buoyancy Tests and CFD, Spacecraft Propulsion, Third International Conference held 10-13 October, 2000 at Cannes, France. European Space Agency ESASP-465, 2001, p.547

24-01 Hiroshi Nishino, Shujiro Sawai, & Katsumi Furukawa, Prediction of Sloshing Dynamics in Spinning Spherical Tanks, Mitsubishi Heavy Industry, The Institute of Space and Astronautical Science 9th Workshop on Astrodynamics and Flight Mechanics (1999)

5-96 D. J. Frank, Dynamics of Superfluid Helium in Low-Gravity: A Progress Report, Advanced Technology Center, Lockheed Martin Missiles & Space, Palo Alto, CA 94304, USA, To be published in Proceedings of 1996 NASA/JPL Microgravity Low Temperature Physics Workshop, April 1996

7-95 G. D. Grayson, Coupled Thermodynamic-Fluid-Dynamic Solution for a Liquid Hydrogen Tank, Journal of Spacecraft and Rockets, Vol. 32, No. 5, September-October 1995

5-94 G. Ross, Dynamics of Superfluid Helium in Low Gravity, dissertation submitted to Dept. Mech. Engrg. and Committee on Graduate Studies of Stanford University for Ph.D. degree, July 1994

9-93 N. H. Hughes, Numerical Stability Problem Encountered Modeling Large Liquid Mass in Micro Gravity, The Boeing Company, presented at the AAS/AIAA Astrodynamics Specialist Conference, Victoria, B.C., Canada, August 16-19, 1993

8-93 G. D. Grayson and J. Navickas, Interaction Between Fluid-Dynamic and Thermodynamic Phenomena in a Cryogenic Upper Stage, McDonnell Douglas, AIAA-93-2753, presented at the AIAA 28th Thermophysics Conference, Orlando, FL, July 6-9, 1993

7-93 G. Grayson and E. DiStefano, Propellant Acquisition for Single Stage Rocket Technology, McDonnell Douglas, AIAA-93-2283, presented at the AIAA/SAE/ASME/ASEE 29th Joint Propulsion Conference and Exhibit, Monterey, CA, June 28-30, 1993

6-93 Y. Letourneur and J. Sicilian, Propellant Reorientation Effects on the Attitude of the Main Cryotechnic Stage of Ariane V, Aerospatiale, Les Mureaux and Flow Science Inc, presented at the AIAA/SAE/ASME/ASEE 29th Joint Propulsion Conference and Exhibit, Monterey, CA, June 28-30, 1993

4-92 J. M. Sicilian, Evaluation of Space Vehicle Dynamics Including Fluid Slosh and Applied Forces, Flow Science report (FSI-92-47-01), August 1992

9-91 G. P. Sasmal, J. I. Hochstein, M. C. Wendl, Washington University and T. L. Hardy, NASA Lewis Research Center, Computational Modeling of the Pressurization Process in a NASP Vehicle Propellant Tank Experimental Simulation, (AIAA 91-2407), AIAA/SAE/ASME/ASEE 27th Joint Propulsion Conference, Sacramento, CA, June 24-26, 1991

8-91 M. F. Fisher, G. R. Schmidt, and J. J. Martin,  Analysis of Cryogenic Propellant Behavior in Microgravity and Low Thrust Environments, NASA-Marshall Space Flight Center, AIAA/SAE/ASME/ASEE 27th Joint Propulsion Conference, Sacramento, CA, June 24-26, 1991

15-90 T. L. Hardy and T. M. Tomasik, Prediction of the Ullage Gas Thermal Stratification in a NASP Vehicle Propellant Tank Experimental Simulation Using FLOW-3D, NASA Technical Memorandum 103217, NASA-Lewis Research Center, Cleveland, OH, July 1990

6-90 J. Navickas, McDonnell Douglas Space Systems Co., Huntington Beach, CA and P.Y. Cheng, McDonnell Douglas Aircraft Co., St. Louis, MO, Effect of Propellant Sloshing on the Design of Space Vehicle Propellant Storage Systems, presented at the 26th AIAA/SAE/ASME/ASEE Joint Propulsion Conference, Orlando World Center, Orlando, FL, July 16-18, 1990

1-90 S. M. Dominick and J. R. Tegart, Fluid Dynamics and Thermodynamics of a Low Gravity Liquid Tank Filling Method, AIAA 28th Aerospace Sciences Meeting, AAIA-90-0509, Reno, NV, January 1990.

9-89 S. Lin and D. K. Warinner, FLOW-3D Analysis of Pressure Responses in an Enclosed Launching System, presented at the Symposium on Computational Experiments, PVP ASME Conference, Honolulu, HI, July 22-27, 1989

3-89 C. W. Hirt, Flow in a Solid-Propellant Rocket Chamber, Flow Science Technical Note #17, March 1989 (FSI-89-TN17)

1-89 J. Navickas, E. C. Cady, and J. L. Ditter, Suspension of Solid Particles in the Aerospace Plane’s Slush Hydrogen Tanks, McDonnell Douglas Astronautics Co. report, Huntington Beach, CA, 1988, presented at the Symposium on Computational Experiments, PVP ASME Conference, Honolulu, HI, July 22-27, 1989

11-88 J. Navickas, Prediction of a Liquid Tank Thermal Stratification by a Finite Difference Computing Method, presented to AIAA/ASEE/ASME/SAE 24th Joint Propulsion Conference, Boston, MA, 11-14 July 1988

10-88 J. Navickas, Space-Based System Disturbances Caused by On-Board Fluid Motion During System Maneuvers, presented to 1st National Fluid Dynamics Congress, Cincinnati, OH, July 24-28, 1988

9-88 J. Navickas, E. C. Cady, and T. L. Flaska, Modeling of Solid-Liquid Circulation in the National Aerospace Plane’s Slush Hydrogen Tanks, Advanced Propulsion, Advanced Technology Center, McDonnell Douglas Astronautics Co., Huntington Beach, CA, May 24, 1988

3-88 J. M. Sicilian and C. W. Hirt, Nozzle/Case Joint Analysis with CFD Analysis Using the FLOW-3D Program, in Redesigned Solid Rocket Motor Circumferential Flow Technical Interchange Meeting Final Report, NASA-TWR-17788, February 1988

11-87 C. W. Hirt, A Perspective on NASA-VOF3D vs. FLOW-3D, Flow Science report, December 1987 (FSI-87-00-3)

8-87 J. M. Sicilian, Fluid Slosh in a Rotating and Accelerating Tank, Flow Science report, Sept. 1987 (FSI-87-37-1)

5-87 J. J. Der and C.L. Stevens, Liquid Propellant Tank Ullage Bubble Deformation and Breakup in Low Gravity Reorientation, AIAA/SAE/ASME/ASEE 23rd Joint Propulsion Conference, San Diego, Calif., June 1987 (AIAA-87-2021)

3-87 J. Navickas and J. Ditter, Effect of the Propellant Storage Tank Geometric Configuration on the Resultant Disturbing Forces and Moments during Low-Gravity Maneuvers, McDonnell Douglas Astronautics report, MDAC H2589, April 1987, presented at 1987 ASME Winter Annual Meeting

1-87 J. J. Der and C. L. Stevens, Low-Gravity Bubble Reorientation in Liquid Propellant Tanks, AIAA 25th Aerospace Sciences Meeting, Reno, Nevada, January 12-15, 1987 (AIAA-87-0622)

7-86 J. Navickas, C. R. Cross, and D. D. Van Winkle, Propellant Tank Forces Resulting from Fluid Motion in a Low-Gravity Field, ASME Symposium in Microgravity Fluid Mechanics, Winter Annual Meeting, Anaheim, CA, December 7-12, 1986

6-86 J. Navickas and C. R. Cross, Some Typical Applications of the HYDR3D CodeFLOW-3D Experience Conference, Redondo Beach, California, November 6-7, 1986

5-86 R. E. Martin, Effects of Transient Propellant Dynamics on Deployment of Large Liquid Stages in Zero-Gravity with Application to Shuttle-Centaur, 37th Annual Astronautical Congress, Innsbruck, Austria, Oct. 3-10, 1986 (IAF-86-119), Acta Astronautical Vol. 15, No. 6/7, pp. 331-340, 1987

4-86 C. W. Hirt, FLOW-3D Test Problems for Two-Fluid Sloshing, Flow Science report, July 1986 (FSI-86-31-1)

6-85 John I. Hochstein, Computational Prediction of Propellant Motion During Separation of a Centaur G-Prime Vehicle from the Shuttle, NASA report, Washington University, St. Louis, MO, December 1985 (WU/CFDL-85/1)

4-85 T. W. Eastes, Y. M. Chang, C. W. Hirt, and J. M. Sicilian, Zero-Gravity Slosh Analysis, ASME Winter Annual Meeting, Miami, Florida, November 1985

3-84 J. M. Sicilian and C. W. Hirt, Numerical Simulation of Propellant Sloshing for Spacecraft, ASME Winter Annual Meeting, New Orleans, LA, December 9-14, 1984

Coating Bibliography

아래는 코팅 참고 문헌의 기술 문서 모음입니다. 
이 모든 논문은 FLOW-3D  결과를 포함하고 있습니다. FLOW-3D를 사용하여 코팅 공정을 성공적으로 시뮬레이션  하는 방법에 대해 자세히 알아보십시오.

Coating Bibliography

Below is a collection of technical papers in our Coating Bibliography. All of these papers feature FLOW-3D results. Learn more about how FLOW-3D can be used to successfully simulate coating processes.

50-19     Peng Yi, Delong Jia, Xianghua Zhan, Pengun Xu, and Javad Mostaghimi, Coating solidification mechanism during plasma-sprayed filling the laser textured grooves, International Journal of Heat and Mass Transfer, Vol. 142, 2019. doi:10.1016/j.ijheatmasstransfer.2019.118451

01-19   Jelena Dinic and Vivek Sharma, Computational analysis of self-similar capillary-driven thinning and pinch-off dynamics during dripping using the volume-of-fluid method, Physics of Fluids, Vol. 31, 2019. doi: 10.1063/1.5061715

85-18   Zia Jang, Oliver Litfin and Antonio Delgado, A semi-analytical approach for prediction of volume flow rate in nip-fed reverse roll coating process, Proceedings in Applied Mathematics and Mechanics, Vol. 18, no. 1, Special Issue: 89th Annual Meeting of the International Association of Applied Mathematics and Mechanics, 2018. doi: 10.1002/pamm.201800317

80-14   Hiroaki Koyama, Kazuhiro Fukada, Yoshitaka Murakami, Satoshi Inoue, and Tatsuya Shimoda, Investigation of Roll-to-Sheet Imprinting for the Fabrication of Thin-film Transistor Electrodes, IEICE TRAN, ELECTRON, VOL.E97-C, NO.11, November 2014

46-14   Isabell Vogeler, Andreas Olbers, Bettina Willinger and Antonio Delgado, Numerical investigation of the onset of air entrainment in forward roll coating, 17th International Coating Science and Technology Symposium September 7-10, 2014 San Diego, CA, USA

17-12  Chi-Feng Lin, Bo-Kai Wang, Carlos Tiu and Ta-Jo Liu, On the Pinning of Downstream Meniscus for Slot Die Coating, Advances in Polymer Technology, Vol. 00, No. 0, 1-9 (2012) © 2012 Wiley Periodicals, Inc. Available online at Wiley.

01-11  Reid Chesterfield, Andrew Johnson, Charlie Lang, Matthew Stainer, and Jonathan Ziebarth, Solution-Coating Technology for AMOLED Displays, Information Display Magazine, 1/11 0362-0972/01/2011-024 © SID 2011.

61-09 Yi-Rong Chang, Chi-Feng Lin and Ta-Jo Liu, Start-up of slot die coating, Polymer Engineering and Science, Vol. 49, pp. 1158-1167, 2009. doi:10.1002/pen.21360

26-06  James M. Brethour, 3-D transient simulation of viscoelastic coating flows, 13th International Coating Science and Technology Symposium, September 2006, Denver, Colorado

19-06  Ivosevic, M., Cairncross, R. A., and Knight, R., 3D Predictions of Thermally Sprayed Polymer Splats Modeling Particle Acceleration, Heating and Deformation on Impact with a Flat Substrate, Int. J. of Heat and Mass Transfer, 49, pp. 3285 – 3297, 2006

9-06  M. Ivosevic, R. A. Cairncross, R. Knight, T. E. Twardowski, V. Gupta, Drexel University, Philadelphia, PA; J. A. Baldoni, Duke University, Durham, NC, Effect of Substrate Roughness on Splatting Behavior of HVOF Sprayed Polymer Particles Modeling and Experiments, International Thermal Spray Conference, Seattle, WA, May 2006.

26-05  Ivosevic, M., Cairncross, R. A., Knight, R., Impact Modeling of Thermally Sprayed Polymer Particles, Proc. International Thermal Spray Conference [ITSC-2005], Eds., DVS/IIW/ASM-TSS, Basel, Switzerland, May 2005.

11-05  Brethour, J., Simulation of Viscoelastic Coating Flows with a Volume-of-fluid Technique, in Proceedings of the 6th European Coating Symposium, Bradford, UK, 2005

1-05 C.W. Hirt, Electro-Hydrodynamics of Semi-Conductive Fluids: With Application to Electro-Spraying, Flow Science Technical Note #70, FSI-05-TN70

38-04 K.H. Ho and Y.Y. Zhao, Modelling thermal development of liquid metal flow on rotating disc in centrifugal atomisation, Materials Science and Engineering, A365, pp. 336-340, 2004. doi:10.1016/j.msea.2003.09.044

30-04  M. Ivosevic, R.A. Cairncross, and R. Knight, Impact Modeling of HVOF Sprayed Polymer Particles, Presented at the 12th International Coating Science and Technology Symposium, Rochester, New York, September 23-25, 2004

29-04  J.M. Brethour and C.W. Hirt, Stains Arising from Dried Liquid Drops, Presented at the 12th International Coating Science and Technology Symposium, Rochester, New York, September 23-25, 2004

20-03  James Brethour, Filling and Emptying of Gravure Cells–A CFD Analysis, Convertech Pacific October 2002, Vol. 10, No 4, p 34-37

4-03   M. Toivakka, Numerical Investigation of Droplet Impact Spreading in Spray Coating of Paper, In Proceedings of 2003 TAPPI 8th Advanced Coating Fundamentals Symposium, TAPPI Press, Atlanta, 2003

28-02  J.M. Brethour and H. Benkreira, Filling and Emptying of Gravure Cells—Experiment and CFD Comparison, 11th International Coating Science and Technology Symposium, September 23-25, 2002, Minneapolis, Minnesota

22-02  Hirt, C.W., and Brethour, J.M., Contact Line on Rough Surfaces with Application to Air Entrainment, Presented at the 11th International Coating Science and Technology Symposium, September 23-25, 2002, Minneapolis, Minnesota. Unpublished.

17-01  J. M. Brethour, C. W. Hirt, Moving Contact Lines on Rough Surfaces, 4th European Coating Symposium, 2001, Belgium

16-01  J. M. Brethour, Filling and Emptying of Gravure Cells–-A CFD Analysis, proceedings of the 4th European Coating Symposium 2001, October 1-4, 2001, Brussels, Belgium

26-00 Ronald H. Miller and Gary S. Strumolo, A Self-Consistent Transient Paint Simulation, Proceedings of IMEC2000: 2000 ASME International Mechanical Engineering Congress and Exposition, November 2000, Orlando, Florida

6-99  C. W. Hirt, Direct Computation of Dynamic Contact Angles and Contact Lines, ECC99 Coating Conference, Erlangen, Germany (FSI-99-00-2), Sept. 1999

7-98 J. E. Richardson and Y. Becker, Three-Dimensional Simulation of Slot Coating Edge Effects, Flow Science Inc, and Polaroid Corporation, presented at the 9th International Coating Science and Technology Symposium, Newark, DE, May 18-20, 1998

6-98  C. W. Hirt and E. Choinski, Simulation of the Wet-Start Process in Slot Coating, Flow Science Inc, and Polaroid Corporation, presented at the 9th International Coating Science and Technology Symposium, Newark, DE, May 18-20, 1998

3-97  C. W. Hirt and J. E. Richardson of Flow Science Inc, and K.S. Chen, Sandia National Laboratory, Simulation of Transient and Three-Dimensional Coating Flows Using a Volume-of-Fluid Technique, presented at the 50th Annual Conference of the Society for Imaging and Science Technology, Boston, MA 18-23 May 1997

2-96 C. W. Hirt, K. S. Chen, Simulation of Slide-Coating Flows Using a Fixed Grid and a Volume-of-Fluid Front-Tracking Technique, presented a the 8th International Coating Process Science & Technology Symposium, February 25-29, 1996, New Orleans, LA

Coastal & Maritime Bibliography

다음은 연안 및 해양 분야의 기술 문서 모음입니다.
이 모든 논문은 FLOW-3D  결과를 포함하고 있습니다. FLOW-3D를 사용하여 연안 및 해양 시설물을 성공적으로 시뮬레이션 하는 방법에 대해 자세히 알아보십시오.

Coastal & Maritime Bibliography

Below is a collection of technical papers in our Coastal & Maritime Bibliography. All of these papers feature FLOW-3D results. Learn more about how FLOW-3D can be used to successfully simulate Coastal & Maritime applications.

51-20       Yupeng Ren, Xingbei Xu, Guohui Xu, Zhiqin Liu, Measurement and calculation of particle trajectory of liquefied soil under wave action, Applied Ocean Research, 101; 102202, 2020. doi.org/10.1016/j.apor.2020.102202

50-20       C.C. Battiston, F.A. Bombardelli, E.B.C. Schettini, M.G. Marques, Mean flow and turbulence statistics through a sluice gate in a navigation lock system: A numerical study, European Journal of Mechanics – B/Fluids, 84; pp.155-163, 2020. doi.org/10.1016/j.euromechflu.2020.06.003

49-20     Ahmad Fitriadhy, Nur Amira Adam, Nurul Aqilah Mansor, Mohammad Fadhli Ahmad, Ahmad Jusoh, Noraieni Hj. Mokhtar, Mohd Sofiyan Sulaiman, CFD investigation into the effect of heave plate on vertical motion responses of a floating jetty, CFD Letters, 12.5; pp. 24-35, 2020. doi.org/10.37934/cfdl.12.5.2435

40-20       P. April Le Quéré, I. Nistor, A. Mohammadian, Numerical modeling of tsunami-induced scouring around a square column: Performance assessment of FLOW-3D and Delft3D, Journal of Coastal Research (preprint), 2020. doi.org/10.2112/JCOASTRES-D-19-00181

38-20       Sahameddin Mahmoudi Kurdistani, Giuseppe Roberto Tomasicchio, Daniele Conte, Stefano Mascetti, Sensitivity analysis of existing exponential empirical formulas for pore pressure distribution inside breakwater core using numerical modeling, Italian Journal of Engineering Geology and Environment, 1; pp. 65-71, 2020. doi.org/10.4408/IJEGE.2020-01.S-08

36-20       Mohammadamin Torabi, Bruce Savage, Efficiency improvement of a novel submerged oscillating water column (SOWC) energy harvester, Proceedings, World Environmental and Water Resources Congress (Cancelled), Henderson, Nevada, May 17–21, 2020. doi.org/10.1061/9780784482940.003

32-20       Adriano Henrique Tognato, Modelagem CFD da interação entre hidrodinâmica costeira e quebra-mar submerso: estudo de caso da Ponta da Praia em Santos, SP (CFD modeling of interaction between sea waves and submerged breakwater at Ponta de Praia – Santos, SP: a case study, Thesis, Universidad Estadual de Campinas, Campinas, Brazil, 2020.

29-20   Ana Gomes, José L. S. Pinho, Tiago Valente, José S. Antunes do Carmo and Arkal V. Hegde, Performance assessment of a semi-circular breakwater through CFD modelling, Journal of Marine Science and Engineering, 8.3, art. no. 226, 2020. doi.org/10.3390/jmse8030226

23-20  Qi Yang, Peng Yu, Yifan Liu, Hongjun Liu, Peng Zhang and Quandi Wang, Scour characteristics of an offshore umbrella suction anchor foundation under the combined actions of waves and currents, Ocean Engineering, 202, art. no. 106701, 2020. doi.org/10.1016/j.oceaneng.2019.106701

04-20  Bingchen Liang, Shengtao Du, Xinying Pan and Libang Zhang, Local scour for vertical piles in steady currents: review of mechanisms, influencing factors and empirical equations, Journal of Marine Science and Engineering, 8.1, art. no. 4, 2020. doi.org/10.3390/jmse8010004

104-19   A. Fitriadhy, S.F. Abdullah, M. Hairil, M.F. Ahmad and A. Jusoh, Optimized modelling on lateral separation of twin pontoon-net floating breakwater, Journal of Mechanical Engineering and Sciences, 13.4, pp. 5764-5779, 2019. doi.org/10.15282/jmes.13.4.2019.04.0460

103-19  Ahmad Fitriadhy, Nurul Aqilah Mansor, Nur Adlina Aldin and Adi Maimun, CFD analysis on course stability of an asymmetrical bridle towline model of a towed ship, CFD Letters, 11.12, pp. 43-52, 2019.

90-19   Eric P. Lemont and Karthik Ramaswamy, Computational fluid dynamics in coastal engineering: Verification of a breakwater design in the Torres Strait, Proceedings, pp. 762-768, Australian Coasts and Ports 2019 Conference, Hobart, Australia, September 10-13, 2019.

86-19   Mohammed Arab Fatiha, Benoît Augier, François Deniset, Pascal Casari, and Jacques André Astolfi, Morphing hydrofoil model driven by compliant composite structure and internal pressure, Journal of Marine Science and Engineering, 7:423, 2019. doi.org/10.3390/jmse7120423

83-19   Cong-Uy Nguyen, So-Young Lee, Thanh-Canh Huynh, Heon-Tae Kim, and Jeong-Tae Kim, Vibration characteristics of offshore wind turbine tower with gravity-based foundation under wave excitation, Smart Structures and Systems, 23:5, pp. 405-420, 2019. doi.org/10.12989/sss.2019.23.5.405

68-19   B.W. Lee and C. Lee, Development of an equation for ship wave crests in a current in whole water depths, Proceedings, 10th International Conference on Asian and Pacific Coasts (APAC 2019), Hanoi, Vietnam, September 25-28, 2019; pp. 207-212, 2019. doi.org/10.1007/978-981-15-0291-0_29

62-19   Byeong Wook Lee and Changhoon Lee, Equation for ship wave crests in the entire range of water depths, Coastal Engineering, 153:103542, 2019. doi.org/10.1016/j.coastaleng.2019.103542

23-19     Mariano Buccino, Mohammad Daliri, Fabio Dentale, Angela Di Leo, and Mario Calabrese, CFD experiments on a low crested sloping top caisson breakwater, Part 1: Nature of loadings and global stability, Ocean Engineering, Vol. 182, pp. 259-282, 2019. doi.org/10.1016/j.oceaneng.2019.04.017

21-19     Mahsa Ghazian Arabi, Deniz Velioglu Sogut, Ali Khosronejad, Ahmet C. Yalciner, and Ali Farhadzadeh, A numerical and experimental study of local hydrodynamics due to interactions between a solitary wave and an impervious structure, Coastal Engineering, Vol. 147, pp. 43-62, 2019. doi.org/10.1016/j.coastaleng.2019.02.004

15-19     Chencong Liao, Jinjian Chen, and Yizhou Zhang, Accumulation of pore water pressure in a homogeneous sandy seabed around a rocking mono-pile subjected to wave loads, Vol. 173, pp. 810-822, 2019. doi.org/10.1016/j.oceaneng.2018.12.072

09-19     Yaoyong Chen, Guoxu Niu, and Yuliang Ma, Study on hydrodynamics of a new comb-type floating breakwater fixed on the water surface, 2018 International Symposium on Architecture Research Frontiers and Ecological Environment (ARFEE 2018), Wuhan, China, December 14-16, 2018, E3S Web of Conferences Vol. 79, Art. No. 02003, 2019. doi.org/10.1051/e3sconf/20197902003

08-19     Hongda Shi, Zhi Han, and Chenyu Zhao, Numerical study on the optimization design of the conical bottom heaving buoy convertor, Ocean Engineering, Vol. 173, pp. 235-243, 2019. doi.org/10.1016/j.oceaneng.2018.12.061

06-19   S. Hemavathi, R. Manjula and N. Ponmani, Numerical modelling and experimental investigation on the effect of wave attenuation due to coastal vegetation, Proceedings of the Fourth International Conference in Ocean Engineering (ICOE2018), Vol. 2, pp. 99-110, 2019. doi.org/10.1007/978-981-13-3134-3_9

87-18   Muhammad Syazwan Bazli, Omar Yaakob and Kang Hooi Siang, Validation study of u-oscillating water column device using computational fluid dynamic (CFD) simulation, 11thInternational Conference on Marine Technology, Kuala Lumpur, Malaysia, August 13-14, 2018.

86-18   Nur Adlina Aldin, Ahmad Fitriadhy, Nurul Aqilah Mansor, and Adi Maimun, CFD analysis on unsteady yaw motion characteristic of a towed ship, 11th International Conference on Marine Technology, Kuala Lumpur, Malaysia, August 13-14, 2018.

78-18 A.A. Abo Zaid, W.E. Mahmod, A.S. Koraim, E.M. Heikal and H.E. Fath, Wave interaction of partially immersed semicircular breakwater suspended on piles using FLOW-3D, CSME Conference Proceedings, Toronto, Canada, May 27-30, 2018.

73-18   Jian Zhou and Subhas K. Venayagamoorthy, Near-field mean flow dynamics of a cylindrical canopy patch suspended in deep water, Journal of Fluid Mechanics, Vol. 858, pp. 634-655, 2018. doi.org/10.1017/jfm.2018.775

69-18   Keisuke Yoshida, Shiro Maeno, Tomihiro Iiboshi and Daisuke Araki, Estimation of hydrodynamic forces acting on concrete blocks of toe protection works for coastal dikes by tsunami overflows, Applied Ocean Research, Vol. 80, pp. 181-196, 2018. doi.org/10.1016/j.apor.2018.09.001

68-18   Zegao Yin, Yanxu Wang and Xiaoyu Yang, Regular wave run-up attenuation on a slope by emergent rigid vegetation, Journal of Coastal Research (in-press), 2018. doi.org/10.2112/JCOASTRES-D-17-00200.1

65-18   Dagui Tong, Chencong Liao, Jinjian Chen and Qi Zhang, Numerical simulation of a sandy seabed response to water surface waves propagating on current, Journal of Marine Science and Engineering, Vol. 6, No. 3, 2018. doi.org/10.3390/jmse6030088

61-18   Manuel Gerardo Verduzco-Zapata, Aramis Olivos-Ortiz, Marco Liñán-Cabello, Christian Ortega-Ortiz, Marco Galicia-Pérez, Chris Matthews, and Omar Cervantes-Rosas, Development of a Desalination System Driven by Low Energy Ocean Surface Waves, Journal of Coastal Research: Special Issue 85 – Proceedings of the 15th International Coastal Symposium, pp. 1321 – 1325, 2018. doi.org/10.2112/SI85-265.1

37-18   Songsen Xu, Chunshuo Jiao, Meng Ning and Sheng Dong, Analysis of Buoyancy Module Auxiliary Installation Technology Based on Numerical Simulation, Journal of Ocean University of China, vol. 17, no. 2, pp. 267-280, 2018. doi.org/10.1007/s11802-018-3305-4

36-18   Deniz Velioglu Sogut and Ahmet Cevdet Yalciner, Performance comparison of NAMI DANCE and FLOW-3D® models in tsunami propagation, inundation and currents using NTHMP benchmark problems, Pure and Applied Geophysics, pp. 1-39, 2018. doi.org/10.1007/s00024-018-1907-9

26-18   Mohammad Sarfaraz and Ali Pak, Numerical investigation of the stability of armour units in low-crested breakwaters using combined SPH–Polyhedral DEM method, Journal of Fluids and Structures, vol. 81, pp. 14-35, 2018. doi.org/10.1016/j.jfluidstructs.2018.04.016

25-18   Yen-Lung Chen and Shih-Chun Hsiao, Numerical modeling of a buoyant round jet under regular waves, Ocean Engineering, vol. 161, pp. 154-167, 2018. doi.org/10.1016/j.oceaneng.2018.04.093

13-18   Yizhou Zhang, Chencong Liao, Jinjian Chen, Dagui Tong, and Jianhua Wang, Numerical analysis of interaction between seabed and mono-pile subjected to dynamic wave loadings considering the pile rocking effect, Ocean Engineering, Volume 155, 1 May 2018, Pages 173-188, doi.org/10.1016/j.oceaneng.2018.02.041

11-18  Ching-Piao Tsai, Chun-Han Ko and Ying-Chi Chen, Investigation on Performance of a Modified Breakwater-Integrated OWC Wave Energy Converter, Open Access Sustainability 2018, 10(3), 643; doi:10.3390/su10030643, © Società Italiana di Fisica and Springer-Verlag GmbH Germany, part of Springer Nature 2018.

58-17   Jian Zhou, Claudia Cenedese, Tim Williams and Megan Ball, On the propagation of gravity currents over and through a submerged array of circular cylinders, Journal of Fluid Mechanics, Vol. 831, pp. 394-417, 2017. doi.org/10.1017/jfm.2017.604

56-17   Yu-Shu Kuo, Chih-Yin Chung, Shih-Chun Hsiao and Yu-Kai Wang, Hydrodynamic characteristics of Oscillating Water Column caisson breakwaters, Renewable Energy, vol. 103, pp. 439-447, 2017. doi.org/10.1016/j.renene.2016.11.028

47-17   Jae-Nam Cho, Chang-Geun Song, Kyu-Nam Hwang and Seung-Oh Lee, Experimental assessment of suspended sediment concentration changed by solitary wave, Journal of Marine Science and Technology, Vol. 25, No. 6, pp. 649-655 (2017) 649 DOI: 10.6119/JMST-017-1226-04

45-17   Muhammad Aldhiansyah Rifqi Fauzi, Haryo Dwito Armono, Mahmud Mustain and Aniendhita Rizki Amalia, Comparison Study of Various Type Artificial Reef Performance in Reducing Wave Height, Regional Conference in Civil Engineering (RCCE) 430 The Third International Conference on Civil Engineering Research (ICCER) August 1st-2nd 2017, Surabaya – Indonesia.

44-17   Fabio Dentale, Ferdinando Reale, Angela Di Leo, and Eugenio Pugliese Carratelli, A CFD approach to rubble mound breakwater design, International Journal of Naval Architecture and Ocean Engineering, Available online 30 December 2017.

39-17   Milad Rashidinasab and Mehdi Behdarvandi Askar, Modeling the Pressure Distribution and the Changes of Water Level around the Offshore Platforms Exposed to Waves, Using the Numerical Model of FLOW-3D, Computational Water, Energy, and Environmental Engineering, 2017, 6, 97-106, http://www.scirp.org/journal/cweee, ISSN Online: 2168-1570, ISSN Print: 2168-1562

30-17   Omid Nourani and Mehdi Behdarvandi Askar, Comparison of the Effect of Tetrapod Block and Armor X block on Reducing Wave Overtopping in Breakwaters, Open Journal of Marine Science, 2017, 7, 472-484 http://www.scirp.org/journal/ojms ISSN Online: 2161-7392.

29-17   J.A. Vasquez, Modelling the generation and propagation of landslide generated waves, Leadership in Sustainable Infrastructure, Annual Conference – Vancouver, May 31 – June 3, 2017

28-17   Manuel G. Verduzco-Zapata, Francisco J. Ocampo-Torres, Chris Matthews, Aramis Olivos-Ortiz, Diego E. and Galván-Pozos, Development of a Wave Powered Desalination Device Numerical Modelling, Proceedings of the 12th European Wave and Tidal Energy Conference 27th Aug -1st Sept 2017, Cork, Ireland

20-17   Chu-Kuan Lin, Jaw-Guei Lin, Ya-Lan Chen, Chin-Shen Chang, Seabed Change and Soil Resistance Assessment of Jack up Foundation, Proceedings of the Twenty-seventh (2017) International Ocean and Polar Engineering Conference, San Francisco, CA, USA, June 25-30, 2017, Copyright © 2017 by the International Society of Offshore and Polar Engineers (ISOPE), ISBN 978-1-880653-97-5; ISSN 1098-6189.

19-17   Velioğlu Deniz, Advanced Two- and Three-Dimensional Tsunami – Models Benchmarking and Validation, Ph.D Thesis:, Middle East Technical University, June 2017

18-17   Farrokh Mahnamfar and Abdüsselam Altunkaynak, Comparison of numerical and experimental analyses for optimizing the geometry of OWC systems, Ocean Engineering 130 (2017) 10–24.

07-17   Jonas Čerka, Rima Mickevičienė, Žydrūnas Ašmontas, Lukas Norkevičius, Tomas Žapnickas, Vasilij Djačkov and Peilin Zhou, Optimization of the research vessel hull form by using numerical simulation, Ocean Engineering 139 (2017) 33–38

05-17   Liang, B.; Ma, S.; Pan, X., and Lee, D.Y., Numerical modelling of wave run-up with interaction between wave and dolosse breakwater, In: Lee, J.L.; Griffiths, T.; Lotan, A.; Suh, K.-S., and Lee, J. (eds.), 2017, The 2nd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 79, pp. 294-298. Coconut Creek (Florida), ISSN 0749-0208.

02-17   A. Yazid Maliki, M. Azlan Musa, Ahmad M.F., Zamri I., Omar Y., Comparison of numerical and experimental results for overtopping discharge of the OBREC wave energy converter, Journal of Engineering Science and Technology, In Press, © School of Engineering, Taylor’s University

01-17   Tanvir Sayeed, Bruce Colbourne, David Molyneux, Ayhan Akinturk, Experimental and numerical investigation of wave forces on partially submerged bodies in close proximity to a fixed structure, Ocean Engineering, Volume 132, Pages 70–91, March 2017

101-16 Xin Li, Liang-yu Xu, Jian-Min Yang, Study of fluid resonance between two side-by-side floating barges, Journal of Hydrodynamics, vol. B-28, no. 5, pp. 767-777, 2016. doi.org/10.1016/S1001-6058(16)60679-0

81-16   Loretta Gnavi, Deep water challenges: development of depositional models to support geohazard assessment for submarine facilities, Ph.D. Thesis: Politecnico di Torino, May 2016

80-16   Mohammed Ibrahim, Hany Ahmed, Mostafa Abd Alall and A.S. Koraim, Proposing and investigating the efficiency of vertical perforated breakwater, International Journal of Scientific & Engineering Research, Volume 7, Issue 3, March 2016, ISSN 2229-5518

72-16   Yen-Lung Chen and Shih-Chun Hsiao, Generation of 3D water waves using mass source wavemaker applied to Navier–Stokes model, Coastal Engineering 109 (2016) 76–95.

64-16   Jae Nam Cho, Dong Hyun Kim and Seung Oh Lee, Experimental Study of Shape and Pressure Characteristics of Solitary Wave generated by Sluice Gate for Various Conditions, Journal of the Korean Society of Safety, Vol. 31, No. 2, pp. 70-75, April 2016, Copyright @ 2016 by The Korean Society of Safety (pISSN 1738-3803, eISSN 2383-9953) All right reserved. http://dx.doi.org/10.14346/JKOSOS.2016.31.2.70

56-16   Ali A. Babajani, Mohammad Jafari and Parinaz Hafezi Sefat, Numerical investigation of distance effect between two Searasers for hydrodynamic performance, Alexandria Engineering Journal, June 2016.

53-16   Hwang-Ki Lee, Byeong-Kuk Kim, Jongkyu Kim and Hyeon-Ju Kim, OTEC thermal dispersion in coastal waters of Tarawa, Kiribati, OCEANS 2016 – Shanghai, April 2016, 10.1109/OCEANSAP.2016.7485548, © IEEE.

50-16   Mohsin A. R. Irkal, S. Nallayarasu and S. K. Bhattacharyya, CFD simulation of roll damping characteristics of a ship midsection with bilge keel, Proceedings of the ASME 2016 35th International Conference on Ocean, Offshore and Arctic Engineering, OMAE2016, June 19-24, 2016, Busan, South Korea

49-16   Bill Baird, Seth Logan, Wim Van Der Molen, Trevor Elliot and Don Zimmer, Thoughts on the future of physical models in coastal engineering, Proceedings of the 6th International Conference on the Application of Physical Modelling in Coastal and Port Engineering and Science (Coastlab16) Ottawa, Canada, May 10-13, 2016 Copyright ©: Creative Commons CC BY-NC-ND 4.0

47-16   KH Kim et. al, Numerical analysis on the effects of shoal on the ship wave, Applied Engineering, Materials and Mechanics: Proceedings of the 2016 International Conference on Applied Engineering, Materials and Mechanics (ICAEMM 2016)

17-16  Nan-Jing Wu, Shih-Chun Hsiao, Hsin-Hung Chen, and Ray-Yeng Yang, The study on solitary waves generated by a piston-type wave maker, Ocean Engineering, 117(2016)114–129

13-16   Maryam Deilami-Tarifi, Mehdi Behdarvandi-Askar, Vahid Chegini, and Sadegh Haghighi-Pou, Modeling of the Changes in Flow Velocity on Seawalls under Different Conditions Using FLOW-3DSoftware, Open Journal of Marine Science, 2016, 6, 317-322, Published Online April 2016 in SciRes.

01-16   Mohsin A.R. Irkal, S. Nallayarasu, and S.K. Bhattacharyya, CFD approach to roll damping of ship with bilge keel with experimental validation, Applied Ocean Research, Volume 55, February 2016, Pages 1–17

121-15   Josh Carter, Scott Fenical, Craig Hunter and Joshua Todd, CFD modeling for the analysis of living shoreline structure performance, Coastal Structures and Solutions to Coastal Disasters Joint Conference, Boston, MA, Sept. 9-11, 2015. © 2017 by the American Society of Civil Engineers. doi.org/10.1061/9780784480304.047

114-15   Jisheng Zhang, Peng Gao, Jinhai Zheng, Xiuguang Wu, Yuxuan Peng and Tiantian Zhang, Current-induced seabed scour around a pile-supported horizontal-axis tidal stream turbine, Journal of Marine Science and Technology, Vol. 23, No. 6, pp. 929-936 (2015) 929, DOI: 10.6119/JMST-015-0610-11

108-15  Tiecheng Wang, Tao Meng, and Hailong Zha, Analysis of Tsunami Effect and Structural Response, ISSN 1330-3651 (Print), ISSN 1848-6339 (Online), DOI: 10.17559/TV-20150122115308

107-15   Jie Chen, Changbo Jiang, Wu Yang, Guizhen Xiao, Laboratory study on protection of tsunami-induced scour by offshore breakwaters, Natural Hazards, 2015, 1-19

85-15   Majid A. Bhinder, M.T. Rahmati, C.G. Mingham and G.A. Aggidis, Numerical hydrodynamic modelling of a pitching wave energy converter, European Journal of Computational Mechanics, Volume 24, Issue 4, 2015, DOI: 10.1080/17797179.2015.1096228

65-15   Giancarlo Alfonsi, Numerical Simulations of Wave-Induced Flow Fields around Large-Diameter Surface-Piercing Vertical Circular CylinderComputation 20153(3), 386-426; doi:10.3390/computation3030386

61-15   Bingchen Liang, Duo Li, Xinying Pan and Guangxin Jiang, Numerical Study of Local Scour of Pipeline under Combined Wave and Current Conditions, Proceedings of the Twenty-fifth (2015) International Ocean and Polar Engineering Conference Kona, Big Island, Hawaii, USA, June 21-26, 2015 Copyright © 2015 by the International Society of Offshore and Polar Engineers (ISOPE) ISBN 978-1-880653-89-0; ISSN 1098-6189.

60-15   Chun-Han Ko, Ching-Piao Tsai, Ying-Chi Chen, and Tri-Octaviani Sihombing, Numerical Simulations of Wave and Flow Variations between Submerged Breakwaters and Slope Seawall, Proceedings of the Twenty-fifth (2015) International Ocean and Polar Engineering Conference Kona, Big Island, Hawaii, USA, June 21-26, 2015 Copyright © 2015 by the International Society of Offshore and Polar Engineers (ISOPE) ISBN 978-1-880653-89-0; ISSN 1098-6189.

57-15   Giacomo Viccione and Settimio Ferlisi, A numerical investigation of the interaction between debris flows and defense barriers, Advances in Environmental and Geological Science and Engineering, ISBN: 978-1-61804-314-6, 2015

56-15   Vittorio Bovolin, Eugenio Pugliese Carratelli and Giacomo Viccione, A numerical study of liquid impact on inclined surfaces, Advances in Environmental and Geological Science and Engineering, ISBN: 978-1-61804-314-6, 2015

49-15   Fabio Dentale, Giovanna Donnarumma, Eugenio Pugliese Carratelli, and Ferdinando Reale, A numerical method to analyze the interaction between sea waves and rubble mound emerged breakwaters, WSEAS TRANSACTIONS on FLUID MECHANICS, E-ISSN: 2224-347X, Volume 10, 2015

45-15   Diego Vicinanza, Daniela Salerno, Fabio Dentale and Mariano Buccino, Structural Response of Seawave Slot-cone Generator (SSG) from Random Wave CFD Simulations, Proceedings of the Twenty-fifth (2015) International Ocean and Polar Engineering Conference, Kona, Big Island, Hawaii, USA, June 21-26, 2015, Copyright © 2015 by the International Society of Offshore and Polar Engineers (ISOPE), ISBN 978-1-880653-89-0; ISSN 1098-6189

38-15   Yen-Lung Chen, Shih-Chun Hsiao, Yu-Cheng Hou, Han-Lun Wu and Yuan Chieh Wu, Numerical Simulation of a Neutrally Buoyant Round Jet in a Wave Environment, E-proceedings of the 36th IAHR World Congress, 28 June – 3 July, 2015, The Hague, the Netherlands

34-15   Dieter Vanneste and Peter Troch, 2D numerical simulation of large-scale physical model tests of wave interaction with a rubble-mound breakwater, Coastal Engineering, Volume 103, September 2015, Pages 22–41.

29-15   Masanobu Toyoda, Hiroki Kusumoto, and Kazuo Watanabe, Intrinsically Safe Cryogenic Cargo Containment System of IHI-SPB LNG Tank, IHI Engineering Review, Vol. 47, No. 2, 2015.

24-15   Xixi Pan, Shiming Wang, and Yongcheng Liang, Three-dimensional simulation of floating wave power device, International Power, Electronics and Materials Engineering Conference (IPEMEC 2015)

05-15   M. A. Bhinder, A. Babarit, L. Gentaz, and P. Ferrant, Potential Time Domain Model with Viscous Correction and CFD Analysis of a Generic Surging Floating Wave Energy Converter, (2015), doi: http://dx.doi.org/10.1016/j.ijome.2015.01.005

137-14   A. Najafi-Jilani, M. Zakiri Niri and Nader Naderi, Simulating three dimensional wave run-up over breakwaters covered by antifer units, Int. J. Nav. Archit. Ocean Eng. (2014) 6:297~306

128-14   Dong Chule Kim, Byung Ho Choi, Kyeong Ok Kim and Efim Pelinovsky, Extreme tsunami runup simulation at Babi Island due to 1992 Flores tsunami and Okushiri due to 1993 Hokkido tsunami, Geophysical Research Abstracts, Vol. 16, EGU2014-1341, 2014, EGU General Assembly 2014, © Author(s) 2013. CC Attribution 3.0 License.

123-14   Irkal Mohsin A.R., S. Nallayarasu and S.K. Bhattacharyya, Experimental and CFD Simulation of Roll Motion of Ship with Bilge Keel, International Conference on Computational and Experimental Marine Hydrodynamics MARHY 2014 3-4 December 2014, Chennai, India.

101-14  Dieter Vanneste, Corrado Altomare, Tomohiro Suzuki, Peter Troch and Toon Verwaest, Comparison of Numerical Models for Wave Overtopping and Impact on a Sea Wall, Coastal Engineering 2014

91-14   Fabio Dentale, Giovanna Donnarumma, and Eugenio Pugliese Carratelli, Numerical wave interaction with tetrapods breakwater, Int. J. Nav. Archit. Ocean Eng. (2014) 6:0~0, http://dx.doi.org/10.2478/IJNAOE-2013-0214, ⓒSNAK, 2014, pISSN: 2092-6782, eISSN: 2092-6790

87-14   Philipp Behruzi, Simulation of breaking wave impacts on a flat wall, The 15th International Workshop on Trends In Numerical and Physical Modeling for Industrial Multiphase Flows, Cargèse, Corsica, October 13th–17th, 2014

86-14   Chuan Sim and Sung-uk Choi, Three-Dimensional Scour at Submarine Pipelines under Indefinite Boundary Conditions, 2014

83-14   Hongda Shi, Dong Wang, Jinghui Song, and Zhe Ma, Systematic Design of a Heaving Buoy Wave Energy Device, 5th International Conference on Ocean Energy, 4th November, Halifax, 2014

71-14   Hadi Sabziyan, Hassan Ghassemi, Farhood Azarsina, and Saeid Kazemi, Effect of Mooring Lines Pattern in a Semi-submersible Platform at Surge and Sway Movements, Journal of Ocean Research, 2014, Vol. 2, No. 1, 17-22 Available online at http://pubs.sciepub.com/jor/2/1/4 © Science and Education Publishing DOI:10.12691/jor-2-1-4

56-14   Fernandez-Montblanc, T., Izquierdo, A., and Bethencourt, M., Modelling the oceanographic conditions during storm following the Battle of Trafalgar, Encuentro de la Oceanografıa Fısica Espanola 2014

52-14   Fabio Dentale, Giovanna Donnarumma, and Eugenio Pugliese Carratelli, A new numerical approach to the study of the interaction between wave motion and roubble mound breakwaters, Latest Trends in Engineering Mechanics, Structures, Engineering Geology, ISBN: 978-960-474-376-6

49-14   H. Ahmed and A. Schlenkhoff, Numerical Investigation of Wave Interaction with Double Vertical Slotted Walls, World Academy of Science, Engineering and Technology, International Journal of Environmental, Ecological, Geological and Mining Engineering Vol:8 No:8, 2014

32-14  Richard Keough, Victoria Mullaley, Hilary Sinclair, and Greg Walsh, Design, Fabrication and Testing of a Water Current Energy Device, Memorial University of Newfoundland, Faculty of Engineering and Applied Science, Mechanical Design Project II – ENGI 8926, April 2014

25-14    Paulius Rapalis, Vytautas Smailys, Vygintas Daukšys, Nadežda Zamiatina, and Vasilij Djačkov, Vandens  – Duju Silumos Mainai Gaz-Lifto Tipo Skruberyje,Technologijos mokslo darbai Vakarų Lietuvoje, Vol 9 > Rapalis. Available for download at http://journals.ku.lt/index.php/TMD/article/view/259.

92-13   Matteo Tirindelli, Scott Fenical and Vladimir Shepsis, State-of-the-Art Methods for Extreme Wave Loading on Bridges and Coastal Highways, Seventh National Seismic Conference on Bridges and Highways (7NSC), May 20-22, 2013, Oakland, CA

89-13 Worakanok Thanyamanta, Don Bass and David Molyneux, Prediction of sloshing effects using a coupled non-linear seakeeping and CFD code, Proceedings of the ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering, OMAE2013, June 9-14, 2013, Nantes, France. Available for purchase online at ASME.

83-13   B.W. Lee and C. Lee, Development of Wave Power Generation Device with Resonance Channels, Proceedings of the 7th International Conference on Asian and Pacific Coasts (APAC 2013) Bali, Indonesia, September 24-26, 2013

68-13   Fabio Dentale, Giovanna Donnarumma, and Eugenio Pugliese Carratelli, Rubble Mound Breakwater Run-Up, Reflection and Overtopping by Numerical 3D Simulation, ICE Conference, September 2013, Edinburgh (UK).

66-13  Peter Arnold, Validation of FLOW-3D against Experimental Data for an Axi-Symmetric Point Absorber WEC, © wavebob™, 2013

62-13 Yanan Li, Junwei Zhou, Dazheng Wang and Yonggang Cui, Resistance and Strength Analysis of Three Hulls with ifferent Knuckles, Advanced Materials Research Vols. 779-780 (2013) pp 615-618, © (2013) Trans Tech Publications, Switzerland, doi:10.4028/www.scientific.net/AMR.779-780.615.

61-13  M.R. Soliman, Satoru Ushijima, Nobu Miyagi and Tetsuay Sumi, Density Current Simulation Using Two-Dimensional High Resolution Model, Annuals of Disas. Prev. Res. Inst., Kyoto Univ., No 56 B, 2013.

59-13  Guang Wei Liu, Qing He Zhang, and Jin Feng Zhang, Wave Forces on the Composite Bucket Foundation of Offshore Wind Turbines, Applied Mechanics and Materials, 405-408, 1420, September 2013. Available for purchase online at Scientific.net.

50-13  Joel Darnell and Vladimir Shepsis, Pontoon Launch Analysis, Design and Performance, Ports 2013, © ASCE 2013. Available for purchase online at ASCE.

45-13 Min-chi Li, Numerical Simulation of Wave Overtopping Rate at Sloping Seawalls with Different Configurations of Wave Dissipators, Master’s Thesis: Department of Marine Environment and Engineering, National Sun Yat-Sen University. Abstract only available here: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0701113-144919.

22-13  Nahidul Khan, Jonathan Smith, and Michael Hinchey, Models with all the right curves, © Journal of Ocean Technology, The Journal of Ocean Technology, Vol. 8, No. 1, 2013.

20-13  Efim Pelinovsky, Dong-Chul Kim, Kyeong-Ok Kim and Byung-Ho Choi, Three-dimensional simulation of extreme runup heights during the 2004 Indonesian and 2011 Japanese tsunamis, EGU General Assembly 2013, held 7-12 April, 2013 in Vienna, Austria, id. EGU2013-1760. Online at: http://adsabs.harvard.edu/abs/2013EGUGA..15.1760P.

18-13 Dazheng Wang, Fei Ma, and Lei Mei, Optimization of a 17m Catamaran based on the Resistance Performance, Advanced Materials Research Vols. 690-693, pp 3414-3418, © Trans Tech Publications, Switzerland, doi:10.4028/www.scientific.net/AMR.690-693.3414, May 2013.

16-13  Dong Chule Kim, Kyeong Ok Kim, Efim Pelinovsky, Ira Didenkulova, and Byung Ho Choi, Three-dimensional tsunami runup simulation for the port of Koborinai on the Sanriku coast of Japan, Journal of Coastal Research, Special Issue No. 65, 2013.

15-13  Dong Chule Kim, Kyeong Ok Kim, Byung Ho Choi, Kyung Hwan Kim, and Efin Pelinovsky, Three –dimensional runup simulation of the 2004 Ocean tsunami at the Lhok Nga twin peaks, Journal of Coastal Research, Special Issue No. 65, 2013.

14-13  Jae-Seol Shim, Jinah Kim, Dong-Shul Kim, Kiyoung Heo, Kideok Do, and Sun-Jung Park, Storm surge inundation simulations comparing three-dimensional with two-dimensional models based on Typhoon Maemi over Masan Bay of South Korea, Journal of Coastal Research, Special Issue No. 65, 2013.

115-12  Worakanok Thanyamanta and David Molyneux, Prediction of Stabilizing Moments and Effects of U-Tube Anti-Roll Tank Geometry Using CFD, ASME 2012 31st International Conference on Ocean, Offshore and Arctic Engineering, Volume 5: Ocean Engineering; CFD and VIV, Rio de Janeiro, Brazil, July 1–6, 2012, ISBN: 978-0-7918-4492-2, Copyright © 2012 by ASME

114-12   Dane Kristopher Behrens, The Russian River Estuary: Inlet Morphology, Management, and Estuarine Scalar Field Response, Ph.D. Thesis: Civil and Environmental Engineering, UC Davis, © 2012 by Dane Kristopher Behrens. All Rights Reserved.

111-12  James E. Beget, Zygmunt Kowalik, Juan Horrillo, Fahad Mohammed, Brian C. McFall, and Gyeong-Bo Kim, NEeSR-CR Tsunami Generation by Landslides Integrating Laboratory Scale Experiments, Numerical Models and Natural Scale Applications, George E. Brown, Jr. Network for Earthquake Engineering Simulation Research, July 2012, Boston, MA.

110-12   Gyeong-Bo Kim, Numerical Simulation of Three-Dimensional Tsunami Generation by Subaerial Landslides, M.S. Thesis: Texas A&M University, Copyright 2012 Gyeong-Bo Kim, December 2012

109-12 D. Vanneste, Experimental and Numerical study of Wave-Induced Porous Flow in Rubble-Mound Breakwaters, Ph.D. thesis (Chapters 5 and 6), Faculty of Engineering and Architecture, Ghent University, Ghent (Belgium), 2012.

104-12 Junwoo Choi, Kab Keun Kwon, and Sung Bum Yoon, Tsunami Inundation Simulation of a Built-up Area using Equivalent Resistance Coefficient, Coastal Engineering Journal, Vol. 54, No. 2 (2012) 1250015 (25 pages), © World Scientific Publishing Company and Japan Society of Civil Engineers, DOI: 10.1142/S0578563412500155

94-12 Parviz Ghadimi, Abbas Dashtimanesh, Mohammad Farsi, and Saeed Najafi, Investigation of free surface flow generated by a planing flat plate using smoothed particle hydrodynamics method and FLOW-3D simulations, Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, December 7, 2012 1475090212465235. Available for purchase online at sage journals.

92-12    Panayotis Prinos, Maria Tsakiri, and Dimitris Souliotis, A Numerical Simulation of the WOS and the Wave Propagation along a Coastal Dike, Coastal Engineering 2012.

88-12  Nahidul Khan and Michael Hinchey, Adaptive Backstepping Control of Marine Current Energy Conversion System, PKP Open Conference Systems, IEEE Newfoundland and Labrador Section, 2012.

72-12   F. Dentale, G. Donnarumma, and E. Pugliese Carratelli, Wave Run Up and Reflection on Tridimensional Virtual, Journal of Hydrogeology & Hydrologic Engineering, 2012, 1:1, http://dx.doi.org/10.4172/jhhe.1000102.

64-12  Anders Wedel Nielsen, Xiaofeng Liu, B. Mutlu Sumer, Jørgen Fredsøe, Flow and bed shear stresses in scour protections around a pile in a current, Coastal Engineering, Volume 72, February 2013, Pages 20–38.

56-12  Giancarlo Alfonsi, Agostino Lauria, Leonardo Primavera, Flow structures around large-diameter circular cylinder, Journal of Flow Visualization and Image Processing, 2012. DOI:10.1615/JFlowVisImageProc.2012005088.

51-12  Chun-Ho Chen, Study on the Application of FLOW-3D for Wave Energy Dissipation by a Porous Structure, Master’s Thesis: Department of Marine Environment and Engineering, National Sun Yat-sen University, July 2012. In Chinese.

37-12  Yu-Ren Chen, Numerical Modeling on Internal Solitary Wave propagation over an obstacle using FLOW-3D, Master’s Thesis: Department of Marine Environment and Engineering, National Sun Yat-sen University June 2012. In Chinese.

26-12  D.C. Lo Numerical simulation of hydrodynamic interaction produced during the overtaking and the head-on encounter process of two ships, Engineering Computations: International Journal for Computer-Aided Engineering and Software, Vol. 29 No. 1, 2012. pp. 83-10, Emerald Group Publishing Limited, www.emeraldinsight.com/0264-4401.htm.

14-12  Bahaa Elsharnouby, Akram Soliman, Mohamed Elnaggar, and Mohamed Elshahat, Study of environment friendly porous suspended breakwater for the Egyptian Northwestern Coast, Ocean Engineering 48 (2012) 47-58. Available for purchase online at Science Direct.

11-12  Sang-Ho Oh, Young Min Oh, Ji-Young Kim, Keum-Seok Kang, A case study on the design of condenser effluent outlet of thermal power plant to reduce foam emitted to surrounding seacoast, Ocean Engineering, Volume 47, June 2012, Pages 58–64. Available for purchase online at SciVerse.

101-11 Tsunami – A Growing Disaster, edited by Mohammad Mokhtari, ISBN 978-953-307-431-3, 232 pages, Publisher: InTech, Chapters published December 16, 2011 under CC BY 3.0 license, DOI: 10.5772/922. Available for download at Intech.

100-11 Kwang-Oh Ko, Jun-Woo Choi, Sung-Bum Yoon, and Chang-Beom Park, Internal Wave Generation in FLOW-3D Model, Proceedings of the Twenty-first (2011) International Offshore and Polar Engineering Conference, Maui, Hawaii, USA, June 19-24, 2011, Copyright © 2011 by the International Society of Offshore and Polar Engineers (ISOPE), ISBN 978-1-880653-96-8 (Set); ISSN 1098-6189 (Set); www.isope.org

95-11  S. Brizzolara, L. Savio, M. Viviani, Y. Chen, P. Temarel, N. Couty, S. Hoflack, L. Diebold, N. Moirod and A. Souto Iglesias, Comparison of experimental and numerical sloshing loads in partially filled tanks, Ships and Offshore StructuresVol. 6, Nos. 1–2, 2011, 15–43. Available for purchase online at Francis & Taylor.

85-11 Andrew Eoghan Maguire, Hydrodynamics, control and numerical modelling of absorbing wavemakers, thesis: The University of Edinburgh, 2011.

74-11  Jonathan Smith, Nahidul Khan and Michael Hinchey, CFD Simulation of AUV Depth Control, Paper presented at NECEC 2011, St. John’s, Newfoundland and Labrador, Canada. Abstract available online.

70-11  G. Kim, S.-H. Oh, K.S. Lee, I.S. Han, J.W. Chae, and S.-J Ahn, Numerical Investigation on Water Discharge Capability of Sluice Caisson of Tidal Power Plant, Proceedings of the Sixth International Conference on Asian and Pacific Coasts (APAC 2011), December 14-16, 2011, Hong Kong, China.

69-11  G. Alfonsi, A. Lauria, and L. Primavera, Wave-Field Flow Structures Developing Around Large-Diameter Vertical Circular Cylinder, Proceedings of the Sixth International Conference on Asian and Pacific Coasts (APAC 2011), December 14-16, 2011, Hong Kong, China.

68-11    C. Lee, B.W. Lee, Y.J. Kim, and K.O. Ko, Ship Wave Crests in Intermediate-Depth Water, Proceedings of the Sixth International Conference on Asian and Pacific Coasts (APAC 2011), December 14-16, 2011, Hong Kong, China.

63-11   Worakanok Thanyamanta, Paul Herrington, and David Molyneux, Wave patterns, wave induced forces and moments for a gravity based structure predicted using CFD, Proceedings of the ASME 2011, 30th International Conference on Ocean, Offshore and Arctic Engineering, OMAE2011, Rotterdam, The Netherlands, June 19-24, 2011.

61-11  Jun Jin and Bo Meng, Computation of wave loads on the superstructures of coastal highway bridges, Ocean Engineering, available online October 19, 2011, ISSN 0029-8018, 10.1016/j.oceaneng.2011.09.029. Available for purchase at Science Direct.

36-11    Nadir Yilmaz, Geoffrey E. Trapp, Scott M. Gagan, Timothy R. Emmerich, CFD Supported Examination of Buoy Design for Wave Energy Conversion, IGEC-VI-2011-173, pp: 537-541

28-11  Rodolfo Bolaños, Laurent O. Amoudry and Ken Doyle, Effects of Instrumented Bottom Tripods on Process Measurements, Journal of Atmospheric and Oceanic Technology, June 2011, Vol. 28, No. 6: pp. 827-837. Available online at: AMS Journals Online.

81-10    Ashwin Lohithakshan Parambath, Impact of Tsunamis on Near Shore Wind Power Units, M.S. Thesis: Texas A&M University, Copyright 2010 Ashwin Lohithakshan Parambath December 2010.

80-10    Juan J. Horrillo, Amanda L. Wood, Charles Williams, Ashwin Parambath, and Gyeong-Bo Kim, Construction of Tsunami Inundation Maps in the Gulf of Mexico, Report to the National Tsunami Hazard Mitigation Program, December 2010.

69-10    George A Aggidis and Clive Mingham, A Joint Numerical and Experimental Study of a Surging Point Absorbing Wave Energy Converter (WRASPA), Joule Centre Research Grant Joint Final Report (Lancaster University and Macnhester Metropolitan University), Joule Grant No: JIRP306/02, 2010

67-10  Kazuhiko Terashima, Ryuji Ito, Yoshiyuki Noda, Yoji Masui and Takahiro Iwasa, Innovative Integrated Simulator for Agile Control Design on Shipboard Crane Considering Ship and Load Sway, 2010 IEEE International Conference on Control Applications, Part of 2010 IEEE Multi-Conference on Systems and Control, Yokohama, Japan, September 8-10, 2010

66-10  Shan-Hwei Ou, Tai-Wen Hsu, Jian-Feng Lin, Jian-Wu Lai, Shih-Hsiang Lin, Chen-Chen Chang, Yuan-Jyh Lan, Experimental and Numerical Studies on Wave Transformation over Artificial Reefs, Proceedings of the International Conference on Coastal Engineering, No 32 (2010), Shanghai, China, 2010.

65-10 Tai-Wen Hsu, Jian-Wu Lai, Yuan-Jyh Lan, Experimental and Numerical Studies on Wave Propagation over Coarse Grained Sloping Beach, Proceedings of the International Conference on Coastal Engineering, No 32 (2010), Shanghai, China, 2010.

26-10 R. Marcer, C. Berhault, C. de Jouëtte, N. Moirod and L. Shen, Validation of CFD Codes for Slamming, V European Conference on Computational Fluid Dynamics, ECCOMAS CFD 2010, J.C.F. Pereira and A. Sequeira (Eds), Lisbon, Portugal, 14-17 June 2010

25-10 J.M. Zhan, Z. Dong, W. Jiang, and Y.S. Li, Numerical Simulation of wave transformation and runup incorporating porous media wave absorber and turbulence models, Ocean Engineering (2010), doi: 10.1016/j.oceaneng.2010.06.005. Available for purchase at Science Direct.

17-10 F. Dentale, S.D. Russo, E. Pugliese Carratelli, S. Mascetti, A New Numerical Approach to Study the Wave Motion with Breakwaters and the Armor Stability, Marine Technology Reporter, May 2010

01-10 F. Dentale, S.D. Russo, E. Pugliese Carratelli, Innovative Numerical Simulation to Study the Fluid withing Rubble Mound Breakwaters and the Armour Stability, 17th Armourstone Wallingford Armourstone Meeting, Wallingford, UK, February 2010.

52-09  Mark Reed, Øistein Johansen, Frode Leirvik, and Bård Brørs, Numerical Algorithm to Compute the Effects of Breaking Waves on Surface Oil Spilled at Sea, Final Report, Second revision, SINTEF, October 2009.

49-09  Anna Pellicioli, Indagine Numerica Sulla Resistenza Idrodinamica Di Uno Scafo In Presenza Di Superficie Libera, thesis: Univerista Degli Studi Di Bergamo, 2008/2009. In Italian. Available upon request.

46-09 Carlos Guedes Soares, P.K. Das, Analysis and Design of Marine Structures, CRC Press; 1 Har/Cdr edition (March 2, 2009), 0415549345

32-09 M.A. Binder, C.G. Mingham, D.M. Causon, M.T. Rahmati, G.A. Aggidis, R.V. Chaplin, Numerical Modelling of a Surging Point Absorber Wave Energy Converter, 8th European Wave and Tidal Energy Conference EWTEC 2009, Uppsala, Sweden, 7-10 September 2009

28-09 D. C. Lo, Dong-Taur Su and Jan-Ming Chen (2009), Application of Computational Fluid Dynamics Simulations to the Analysis of Bank Effects in Restricted Waters, Journal of Navigation, 62, pp 477-491, doi:10.1017/S037346330900527X; Purchase the article online (clicking on this link will take you to the Cambridge Journals website).

26-09 Fabio Dentale, E. Pugliese Carratelli, S.D. Russo, and Stefano Mascetti, Advanced Numerical Simulations on the Interaction between Waves and Rubble Mound Breakwaters, Journal of the Engineering Association for Offshore and Marine in Italy, (translation from the Italian)

25-09 F. Dentale, B. Messina, E. Pugliese Carratelli, S. Mascetti, Studio numerico avanzato sul moto di filtrazione in ambito marittimo, A & C, Analisi e Calcolo, Giugno 2009 (in Italian)

22-09 M.A. Bhinder, C.G. Mingham, D.M. Causon, M.T. Rahmati, G.A. Aggidis and R.V. Chaplin, A Joint Numerical And Experimental Study Of a Surging Point Absorbing Wave Energy Converter (WRASPA)2, Proceedings of the ASME 28th International Conference on Ocean, Offshore and Arctic Engineering, OMAE2009-79392, Honolulu, Hawaii, May 31-June 5, 2009

8-09 Basu, D., S. Green, K. Das, R. Janetzke, and J. Stamatakos, Numerical Simulation of Surface Waves Generated by a Subaerial Landslide at Lituya Bay, 28th International Conference on Ocean, Offshore and Arctic Engineering, May 31–June 5, 2009, Honolulu, Hawaii

17-09 Das, K., R. Janetzke, D. Basu, S. Green, and J. Stamatakos, Numerical Simulations of Tsunami Wave Generation by Submarine and Aerial Landslides Using RANS and SPH Models, 28th International Conference on Ocean, Offshore and Arctic Engineering, May 31–June 5, 2009, Honolulu, Hawaii

16-09 Basu, D., S. Green, K. Das, R. Janetzke, and J. Stamatakos, Navier-Stokes Simulations of Surface Waves Generated by Submarine Landslides Effect of Slide Geometry and Turbulence, 2009 Society of Petroleum Engineering Americas E&P Environmental & Safety Conference, March 23–25, 2009, San Antonio, Texas.

48-08    Osamu Kiyomiya1 and Kazuya Kuroki, Flap Gate to Prevent Urban Area from Tsunami, The 14th World Conference on Earthquake Engineering, October 12-17, 2008, Beijing, China

43-08  Eldina Fatimah, Ahmad Khairi Abd. Wahab, and Hadibah Ismail, Numerical modeling approach of an artificial mangrove root system (ArMs) submerged breakwater as wetland habitat protector, COPEDEC VII, Dubai UAE, 2008.

40-08 Giacomo Viccione, Fabio Dentale, and Vittorio Bovolin, Simulation of Wave Impact Pressure on Vertical Structures with the SPH Method, 3rd ERCOFTAC SPHERIC workshop on SPH applications, Laussanne, Switzerland, June 4-6, 2008.

39-08 Kang, Young-Seung, Kim, Pyeong-Joong, Hyun, Sang-Kwon and Sung, Ha-Keun, Numerical Simulation of Ship-induced Wave Using FLOW-3D, Journal of Korean Society of Coastal and Ocean Engineers / v.20, no.3, 2008, pp.255-267, ISSN: 1976-8192, http://ksci.kisti.re.kr/search/article/articleView.ksci?articleBean.artSeq=HOHODK_2008_v20n3_255

35-08 B.W. Nam, S.H. Shin, K.Y. Hong, S.W. Hong, Numerical Simulation of Wave Flow over the Spiral-Reef Overtopping Device, Proceedings of the Eighth (2008) ISOPE Pacific/Asia Offshore Mechanics Symposium, Bangkok, Thailand, November 10-14, 2008, © 2008 by The International Society of Offshore and Polar Engineers, ISBN 978-1-880653-52-4

34-08 B. H. Choi, E. Pelinovsky, D.C. Kim, I. Didenkulova and S.-B. Woo, Two and three-dimensional computation of solitary wave runup on non-plane beach, Nonlin. Processes Geophys., 15, 489-502, 2008, www.nonlin-processes-geophys.net/15/489/2008 (c) Author(s) 2008.

23-08 Barb Schmitz, Tecplot, Nastran & FLOW-3D Win the Race, Desktop Engineering’s Elements of Analysis, September 2008

38-07 Choi, B.-H., Kim, D. C., Pelinovsky, E., and Woo, S. B., Three-dimensional simulation of tsunami run-up around conical island, Coast. Eng., Vol. 54, Issue 8, 618-629, 2007.

33-07 Mirela Zalar, Sime Malenica, Zoran Mravak, Nicolas Moirod, Some Aspects of Direct Calculation Methods for the Assessment of LNG Tank Structure Under Sloshing Impacts, La Asociación Española del Gas (sedigas) Spain 2007

20-07 Oceanic Consulting Corporation, Berthing Studies for LNG Carriers in the Calcasieu River Waterway, Making Waves: Newsletter of Oceanic Consulting Corporation, Winter 2007

10-07 Gildas Colleter, Breaking wave uplift and overtopping on a horizontal deck using physical and numerical modeling, Coasts and Ports 2007 Conference in Melbourne, Australia

18-06 Brizzolara, Stefano and Rizzuto, Enrico, Wind Heeling Moments on Very Large Ships. Some Insights through CFD Results, Proceedings on the 9th International Conference on Stability of Ships and Ocean Vehicles, Rio de Janeiro, September 25, 2006

16-06 Ransau, Samuel R, and Hansen, Ernst W.M., Numerical Simulations of Sloshing in Rectangular Tanks, Proceedings of OMAE2006, 25th International Conference on Offshore Mechanics and Arctic Engineering, Hamburg, Germany, June 4-9, 2006

15-06 Ema Muk-Pavic, Shin Chin and Don Spencer, Validation of the CFD code FLOW-3D for the free surface flow around the ships’; hulls, 14th Annual Conference of the CFD Society of Canada, Kingston, Canada, July 16-18, 2006

3-06 Hansen, E.W.M. and Geir J. Rørtveit, Numerical Simulation of Fluid Mechanisms and Separation Behaviour in Offshore Gravity Separators, Chapter 16 in Emulsions and Emulsion Stability, 2nd Edition, edited by Johan Sjøblom, Taylor & Francis, 2006

24-05 Hansen E.W., Separation Offshore Survey – Design-Redesign of Gravity Separators, Exploration & Production: The Oil & Gas Review 2005 – Issue 2

8-05 T. Kristiansen, R. Baarholm, C.T. Stansberg, G. Rortveit and E.W.M. Hansen, Kinematics in a Diffracted Wave Field Particle Image Velocimetry (PIV) and Numerical Models, Presented at the 24th International Conference on Offshore Mechanics and Arctic Engineering, OMAE 67176, Halkidiki, Greece, June 12-17, 2005

7-05 C.T. Stansberg, R. Baarholm, T. Kristiansen, E.W.M. Hansen and G. Rortveit, Extreme Wave Amplification and Impact Loads on Offshore Structures, presented at the 2005 Offshore Technology Conference, Houston, TX, May 2-5, 2005

16-04 Carl Trygve Stansberg, Kjetil Berget, Oyvind Hellan, Ole A. Hermundstad, Jan R. Hoff and Trygve Kristiansen and Ernst Hansen, Prediction of Green Sea Loads on FPSO in Random Seas, presented at the 14th International Offshore and Polar Engineering Conference (ISOPE 2004), Toulon, France, May 2004

15-04 Š. Malenica, M. Zalar, J.M. Orozco, B. LeGallo & X.B. Chen, Linear and Non-Linear Effects of Sloshing on Ship Motions, 23rd International Conference on Offshore Mechanics and Artic Engineering, OMAE 2004, Vancouver, June 2004

11-04 Don Bass, David Molyneux, Kevin McTaggart, Simulating Wave Action in the Well Deck of Landing Platform Dock Ships Using Computational Fluid Dynamics

37-03  Sreenivasa C Chopakatla, A CFD Model for Wave Transformations and Breaking in the Surf Zone, thesis: Master of Science, The Ohio State Univeristy, 2003.

29-02   O. Bayle, V. L’Hullier, M. Ganet, P. Delpy, J.L. Francart and D. Paris, Influence of the ATV Propellant Sloshing on the GNC Performance, AIAA Guidance, Navigation, and Control Conference and Exhibit, Monterey, California, 5-8 August 2002, © 2002 by EADS Launch Vehicles

25-02 Y. Kim, Numerical Analysis of Sloshing Problem, American Bureau of Shipping, Research Dept, Houston, TX

10-02 Peter Chang III & Xiongjun Wu, Entrainment Correlations Based on a Fuel-Water Stratified Shear Flow, Proceedings of FEDSM2002, 2002 ASME Fluids Engineering Decision Summer Meeting, July 14-18, 2002, Montreal, Quebec, Canada

37-01 Ismail B. Celik, Allen E. Badeau Jr., Andrew Burt and Sherif Kandil, A Single Fluid Transport Model For Computation of Stratified Immiscible Liquid-Liquid Flows, Mechanical and Aerospace Engineering Department, West Virginia University, Proceedings of the XXIX IAHR Congress, September 2001. Beijing, China

14-01 Charles Ortloff, CTC/United Defense, Computer Simulation Analyzed Typhoon Damage to FPSOs, Marine News, April 30, 2001, pp. 22-23

8-01 Charles Ortloff, Computer Simulations Analyze Wave Damage to Offloading Vessels, Marine News, April 30, 2001, pp. 22-23

25-00 Faltinsen, O.A. and Rognebakke, O.F., Sloshing in Rectangular Tanks and Interaction with Ship Motions-Sloshing, Int. Conf. on Ship and Shipping Research NAV, Venice, Italy, 2000.

20-97   C.R. Ortloff, Numerical Test Tank Simulation of Ocean Engineering Problems by Computational Fluid Dynamics, Offshore Technology Conference Paper 8269B, Houston, TX, 1997

19-97   C.R. Ortloff and M. Krafft, Numerical Test Tanks-Computer Simulation-Test Verification of Major Ocean Engineering Problems for the Off-Shore Oil Industry, OTC 8269A, Offshore Technology Conference, Copyright 1997, Houston, Texas, May 1997

9-94 P. A. Chang, C-W Lin, CD-NSWC, Hydrodynamic Analysis of Oil Outflow from Double Hull Tankers, The Advanced Double-Hull Technical Symposium, Gaithersburg, MD, October 25-26, 1994.

8-90 C. W. Hirt, Computational Modeling of Cavitation, Flow Science report, July 1990, presented at the 2nd International Symposium on Performance Enhancement for Marine Applications, Newport, RI, October 14-16, 1990

10-87 H. W. Meldner, USA’s Revolutionary Appendages and CFD, CORDTRAN Corp. Report presented at AIAA and SNAME 17th Annual International Symposium on Sailing, Stanford University, Palo Alto, CA, Oct. 31-Nov. 1, 1987

3-85 C. W. Hirt and J. M. Sicilian, A Porosity Technique for the Definition of Obstacles in Rectangular Cell Meshes, Fourth International Conference on Ship Hydrodynamics, Washington, DC, September 1985

난류 모델링

본 자료는 국내 사용자들의 편의를 위해 원문 번역을 해서 제공하기 때문에 일부 오역이 있을 수 있어서 원문과 함께 수록합니다. 자료를 이용하실 때 참고하시기 바랍니다.

Turbulence Modeling

The majority of flows in nature are turbulent. This raises the question, is it necessary to represent turbulence in computational models of flow processes? Unfortunately, there is no simple answer to this question, and the modeler must exercise some engineering judgment. The following remarks cover some things to consider when faced with this question.

난류 모델링

자연에서의 흐름은 대부분은 난류입니다. 이것은 유동의 수치해석 모델에서 난류를 표현할 필요가 있는가? 에 대한 의문이 생깁니다.  불행히도이 질문에 대한 답은 모델링을 할 경우 엔지니어가 공학적인 판단을 내려야합니다.  다음에 이 질문에 직면했을 때 고려해야 할  몇 가지를 설명합니다.

Definitions and Orders of Magnitude

The possibility that turbulence may occur is generally measured by the flow Reynolds number:

난류가 발생할 가능성은 일반적으로 흐름의 레이놀즈 수에 의해 측정됩니다.

where ρ is fluid density and μ is the dynamic viscosity of the fluid. The parameters L and U are a characteristic length and speed for the flow. Obviously, the choice of L and U are somewhat arbitrary, and there may not be single values that characterize all the important features of an entire flow field. The important point to remember is that Re is meant to measure the relative importance of fluid inertia to viscous forces. When viscous forces are negligible the Reynolds number is large.

여기서 ρ는 유체 밀도이고 μ는 유체의 동적 점도입니다. 매개 변수 L과 U는 흐름의 특성 길이와 속도입니다. 분명히 L과 U의 선택은 다소 임의적이며, 전체 유동장의 모든 중요한 특징을 특징 짓는 단일 값이 없을 수도 있습니다. 기억해야 할 중요한 점은 Re가 점성력에 대한 유체 관성의 상대적 중요성을 측정한다는 것입니다. 점성력을 무시할 수있는 경우 레이놀즈 수가 큽니다.

A good choice for L and U is usually one that characterizes the region showing the strongest shear flow, that is, where viscous forces would be expected to have the most influence.

L과 U에 대한 좋은 선택은 일반적으로 가장 강한 전단 흐름을 나타내는 영역, 즉 점성 힘이 가장 큰 영향을 미칠 것으로 예상되는 영역을 특징 짓는 것입니다.

Roughly speaking, a Reynolds number well above 1000 is probably turbulent, while a Reynolds number below 100 is not. The actual value of a critical Reynolds number that separates laminar and turbulent flow can vary widely depending on the nature of the surfaces bounding the flow and the magnitude of perturbations in the flow.

대략적으로 말하면, 1000을 훨씬 넘는 레이놀즈 수는 아마도 난류 일 수 있지만 100 미만의 레이놀즈 수는 그렇지 않습니다. 층류와 난류를 분리하는 임계 레이놀즈 수의 실제 값은 유동을 경계하는 표면의 특성과 유동의 섭동의 크기에 따라 크게 달라질 수 있습니다.

In a fully turbulent flow a range of scales exist for fluctuating velocities that are often characterized as collections of different eddy structures. If L is a characteristic macroscopic length scale and l is the diameter of the smallest turbulent eddies, defined as the scale on which viscous effects are dominant, then the ratio of these scales can be shown to be of order L/l≈Re3/4. This relation follows from the assumption that, in steady-state, the smallest eddies must dissipate turbulent energy by converting it into heat.

완전 난류 흐름에서는 다양한 와류 구조의 집합으로 특징 지어지는 변동 속도에 대해 다양한 스케일이 존재합니다. L이 거시적 길이 특성 척도이고, l을 점성 효과가 우세한 척도로 정의되는 가장 작은 난류 소용돌이의 직경인 경우, 이러한 척도의 비율은L/l≈Re3/4 정도인 것으로 표시 될 수 있습니다.  이 관계는 정상 상태에서 가장 작은 소용돌이가 난류 에너지를 열로 변환하여 발산해야한다는 가정에서 비롯됩니다.

Turbulence Models

From the above relation for the range of scales it is easy to see that even for a modest Reynolds number, say Re=104, the range spans three orders of magnitude, L/l=103. In this case, the number of control volumes needed to resolve all the eddies in a three-dimensional computation would be greater than 109. Numbers of this size are well beyond current computational capabilities. For this reason, considerable effort has been devoted to the construction of approximate models for turbulence.

난류 모델

스케일의 범위에 대한 위의 관계를 보면 적당한 레이놀즈 수 (예 : Re = 10 4 )에서도 범위가 세 자릿수인 L/l=103에 걸쳐 있음을 쉽게 알 수 있습니다. 이 경우 3 차원 계산에서 모든 소용돌이를 해결하는데 필요한 제어 볼륨의 수는 109보다 커집니다.이 크기의 수는 현재 계산 능력을 훨씬 뛰어 넘습니다. 이러한 이유로 난류에 대한 대략적인 모델을 구성하는 데 상당한 노력을 기울였습니다.

We cannot describe turbulence modeling in any detail in this short article. Instead, we will simply make some basic observations about the types of models available. Be forewarned, however, that no models exist for general use. Every model must be employed with discretion and its results cautiously treated.

이 짧은 기사에서는 난류 모델링에 대해 구체적으로 설명 할 수 없습니다.  대신 사용 가능한 모델의 유형에 대한 몇 가지 기본적인 설명만 합니다.  그러므로 일반 모델은 존재하지 않는 것을 미리 양해 바랍니다.  어떤 모델도 신중하게 선택하고 결과를 주의 깊게 처리해야 합니다.

The original turbulence modeler was Osborne Reynolds. Anyone interested in this subject should read his groundbreaking work (Phil. Trans. Royal Soc. London, Series A, Vol.186, p.123, 1895). Reynolds’s insights and approach were both fundamental and practical.

난류를 처음으로 모델링 한 인물은 Osborne Reynolds 입니다.  이 건에 관심이있는 분은 Reynolds 의 획기적인 저서 (Phil. Trans. Royal Soc. London, Series A, Vol.186, p.123,1895)를 참조하십시오.  Reynolds 의 통찰력과 접근 방식은 기본이며 동시에 실용적인 것입니다.

The Pseudo-Fluid Approximation

In a fully turbulent flow it is sometimes possible to define an effective turbulent viscosity, μeff, that roughly approximates the turbulent mixing processes contributing to a diffusion of momentum (and other properties). Thinking of a turbulent flow as a pseudo-fluid having increased viscosity leads to the observation that the effective Reynolds number for a turbulent flow is generally less than 100:

의사 유체 근사

완전 난류 흐름에서는 운동량 (및 기타 특성)의 확산에 기여하는 난류 혼합 공정에 대략적으로 근접하는 효과적인 난류 점도 μ eff를 정의 할 수 있습니다. 난류 흐름을 점도가 증가 된 유사 유체로 생각하면 난류 흐름에 대한 유효 레이놀즈 수가 일반적으로 100 미만이라는 관찰이 가능합니다.

This observation is particularly useful because it suggests a simple way to approximate some turbulent flows. In particular, when the details of the turbulence are not important, but the general mixing behavior associated with the turbulence is, it is often possible to use an effective turbulent (eddy) viscosity in place of the molecular viscosity. The effective viscosity can often be expressed as

이 관찰 결과는 몇 가지 난류를 근사하는 간단한 방법을 제시하고 있기 때문에 특히 유용합니다.  특히 난류 대한 자세한 내용은 중요하지 난류와 관련된 일반적인 혼합 거동이 중요한 경우에는 분자 점성 대신 사용 난류 (소용돌이) 점성을 사용할 수있는 경우가 있습니다.  유효 점성은 다음의 식으로 나타낼 수 있습니다.

where α is a number between 0.02 and 0.04. This expression works well for the turbulence associated with plane and cylindrical jets entering a stagnant fluid. The effective Reynolds number associated with this model is Re=1/α, a number between 25 and 50.

α는 0.02에서 0.04 사이의 숫자입니다.  이 수식은 정체 유체에 들어가는 평면 제트 및 원통형 분류 관련 난류에 대하여 효과가 있습니다.  이 모델에 대한 사용 레이놀즈 수는 Re = 1 / α 25에서 50 사이의 숫자입니다.

While this model is often adequate for predicting the gross features of a turbulent flow, it may not be suitable for predicting local details. For example, it would predict a parabolic flow (i.e., laminar) profile in a pipe instead of the measured logarithmic profile.

이 모델은 종종 난류의 전반적인 특징을 예측하는데는 적합하지만, 로컬 세부 사항을 예측하는 데는 적합하지 않을 수 있습니다.  예를 들어, 측정된 대수 프로필 대신 파이프의 포물선 흐름 (층류 등)의 프로파일을 예측합니다.

Local Viscosity Model

The next level of complexity beyond a constant eddy viscosity is to compute an effective viscosity that is a function of local conditions. This is the basis of Prandtl’s mixing-length hypothesis where it is assumed that the viscosity is proportional to the local rate of shear. The proportionality constant has the dimensions of a length squared. The square root of this constant is referred to as the “mixing length.”

This model offers an improvement over a simple constant viscosity. For example, it predicts the logarithmic velocity profile in a pipe. However, it is not used much because it doesn’t account for important transport effects.

국소 점성 모델

일정한 소용돌이 점성보다 복잡한 것은 국소적 조건의 함수인 유효 점성을 계산하는 것입니다.  이것은 점성이 국소적 전단 속도에 비례한다고 가정된다는 프란틀 혼합 길이 가설(Prandtl’s mixing-length hypothesis )의 기초가됩니다.  비례 상수의 차원은 길이의 제곱입니다.  이 상수의 제곱근은 “혼합 장”이라고합니다.

이 모델은 간단한 일정한 점성 개선을 제공합니다.  예를 들어, 파이프의 대수 속도 프로파일을 예측할 수 있습니다.  그러나 중요한 수송 효과를 지원하지 않기 때문에 그다지 많이 사용되지 않습니다.

Turbulence Transport Models

For practical engineering purposes the most successful computational models have two or more transport equations. A minimum of two equations is desirable because it takes two quantities to characterize the length and time scales of turbulent processes. The use of transport equations to describe these variables allows turbulence creation and destruction processes to have localized rates. For instance, a region of strong shear at the corners of a building may generate strong eddies, while little turbulence is generated in the building’s wake region. The strong mixing observed in the wakes of buildings (or automobiles and airplanes) is caused by the advection of upstream generated eddies into the wake. Without transport mechanisms, turbulence would have to instantly adjust to local conditions, implying unrealistically large creation and destruction rates.

난류 수송 모델

실용 공학의 목적인 가장 뛰어난 수치 모델에는 2 개 이상의 수송 방정식이 있습니다.  난류 과정의 길이와 시간의 스케일을 특징으로는 2 개 분량이 필요하므로 최소한 2 개의 방정식이있는 것이 바람직 할 것입니다.  수송 방정식을 사용하여 이러한 변수를 표현하면 난류의 생성 속도와 파괴율을 국소적으로 할 수 있습니다.  예를 들어, 건물의 모서리의 전단력이 강한 영역에서 강력한 소용돌이가 생성 된 건축물의 후류 영역에서 난류는 거의 생성되지 않습니다.  건축물 (또는 자동차 나 비행기)의 후류에서 관찰되는 강력한 혼합은 상류에서 생성된 소용돌이 후류의 이류에 의해 발생합니다.  수송 메커니즘이 없는 경우, 난류는 국소적 조건에 즉시 적응해야하므로 생성 속도와 파괴율이 비현실적인 크기입니다.

Nearly all transport models invoke one or more gradient assumptions in which a correlation between two fluctuating quantities is approximated by an expression proportional to the gradient of one of the terms. This captures the diffusion-like character of turbulent mixing associated with many small eddy structures, but such approximations can lead to errors when there is significant transport by large eddy structures.

거의 모든 수송 모델에서 하나 이상의 경사 가정을 이루어 두 변동하는 양의 상관 관계가 하나의 항 기울기에 비례하는 식으로 근사됩니다.  이를 통해 다수의 작은 소용돌이 구조와 관련된 난류 혼합 확산적인 특징을 파악할 수 있지만, 큰 소용돌이 구조에 의해 상당한 전송이 존재하는 경우, 이러한 근사 오류가 발생할 수 있습니다.

Large Eddy Simulation

Most models of turbulence are designed to approximate a smoothed out or time-averaged effect of turbulence. An exception is the Large Eddy Simulation model (or Subgrid Scale model). The idea behind this model is that computations should be directly capable of modeling all the fluctuating details of a turbulent flow except for those too small to be resolved by the grid. The unresolved eddies are then treated by approximating their effect using a local eddy viscosity. Generally, this eddy viscosity is made proportional to the local grid size and some measure of the local flow velocity, such as the magnitude of the rate of strain.

Large Eddy 시뮬레이션

난류의 대부분의 모델은 매끄럽게 또는 시간 평균된 난류의 효과를 근사하도록 설계되어 있습니다.  예외는 큰 에디 시뮬레이션 모델 (또는 서브 그리드 스케일 모델)입니다.  이 모델의 배경에는 너무 작은 격자에 의해 해결할 수 없는 것을 제외하고는 난류의 모든 변동 내용은 계산에 의해 직접 모델링 할 수 있어야 한다는 생각이 있습니다.  미해결 소용돌이는 로컬 점성을 사용하여 효과를 근사하여 처리됩니다.  일반적으로이 소용돌이 점성은 국소적인 격자 크기 및 어떤 국소적인 흐름의 속도 측정 (변형 속도의 크기 등)에 비례합니다.

대부분의 난류 모델은 난류의 평활화 또는 시간 평균 효과에 근접하도록 설계되었습니다. 예외는 Large Eddy Simulation 모델 (또는 Subgrid Scale 모델)입니다. 이 모델의 이면에있는 아이디어는 계산이 격자에 의해 해결 되기에는 너무 작은 것을 제외하고, 난류 흐름의 모든 변동 세부 사항을 직접 모델링 할 수 있어야 한다는 것입니다. 해결되지 않은 소용돌이는 로컬 소용돌이 점도를 사용하여 효과를 근사화하여 처리됩니다. 일반적으로, 이 와류 점도는 로컬 격자 크기와 변형률의 크기와 같은 로컬 유속 측정치에 비례하여 만들어집니다.

Such an approach might be expected to give good results if the unresolved scales are small enough, for example, in the viscous sub-range. Unfortunately, this is still an uncomfortably small size. When these models are used with a minimum scale size that is above the viscous sub-range, they are then referred to as Coherent Structure Capturing models.

이러한 접근 방식은 미해결 스케일이 충분히 작은 경우, 예를 들어 점성이 작은 영역에 있는 경우에 좋은 결과를 얻을 수 있을 것으로 기대됩니다.  불행히도 아직은 여전히 불편한 작은 크기 입니다.  이러한 모델을 점성 작은 영역보다 높은 최소 스케일 사이즈로 사용하는 경우는 CSC (Coherent Structure Capturing) 모델이라고합니다.

The advantage of these more realistic models is that they provide information not only about the average effects of turbulence but also about the magnitude of fluctuations. But, this advantage is also a disadvantage, because averages must actually be computed over many fluctuations, and some means must be provided to introduce meaningful fluctuations at the start of a computation and at boundaries where flow enters the computational region.

이보다 현실적인 모델의 장점은 난류의 평균 효과에 대한 정보뿐만 아니라 변동의 크기에 대한 정보도 제공 될 것입니다.  그러나 이와같은 장점은 단점도 있습니다.  평균적으로 실제로 다수의 변동에 대해 계산해야 하며, 계산의 시작 및 흐름이 계산 영역에 들어가는 경계에서 상당한 변화를 도입하기위한 수단을 제공 할 필요가 있기 때문입니다.

Turbulence from an Engineering Perspective

We have seen that it is probably not reasonable to attempt to compute all the details of a turbulent flow. Furthermore, from the perspective of most applications, it’s not likely that we would be interested in the local details of individual fluctuations. The question then is how should we deal with turbulence, when should we employ a turbulence model, and how complex should that model be?

공학적 관점에서의 난류

지금까지 난류의 모든 세부 사항을 계산하려고하는 것은 아마도 합리적이지 않다는 것을 확인했습니다.  또한 많은 적용례의 관점에서 개별 변동의 국소적인 세부 사항이 관심의 대상이 될 수는 없을 것입니다.  거기서 생기는 의문은 난류를 어떻게 처리해야 할지 난류 모델을 언제 선택할지 그 모델이 얼마나 복잡할지에 있다는 것입니다.

Experimental observations suggest that many flows become independent of Reynolds number once a certain minimum value is exceeded. If this were not so, wind tunnels, wave tanks, and other experimental tools would not be as useful as they are. One of the principal effects of a Reynolds number change is to relocate flow separation points. In laboratory experiments this fact sometimes requires the use of trip wires or other devices to induce separation at desired locations. A similar treatment may be used in a numerical simulation.

실험적 관찰에 따르면 특정 최소값이 초과되면 많은 흐름이 레이놀즈 수와 무관하게됩니다. 그렇지 않다면 풍동, 파도 탱크 및 기타 실험 도구는 그다지 유용하지 않을 것입니다. 레이놀즈 수 변경의 주요 효과 중 하나는 흐름 분리 지점을 재배치하는 것입니다. 실험실 실험에서이 사실은 때때로 원하는 위치에서 분리를 유도하기 위해 트립 와이어 또는 기타 장치를 사용해야합니다. 유사한 처리가 수치 시뮬레이션에서 사용될 수 있습니다.

Most often a simulation is done to determine the dominant flow patterns that develop in some specified situation. These patterns consist of the mean flow and the largest eddy structures containing the majority of the kinetic energy of the flow. The details of how this energy is removed from the larger eddies and dissipated into heat by the smallest eddies may not be important. In such cases the dissipation mechanisms inherent in numerical methods may alone be sufficient to produce reasonable results. In other cases it is possible to supply additional dissipation with a simple turbulence model such as a constant eddy viscosity or a mixing length assumption.

대부분의 경우 특정 상황에서 발생하는 지배적 인 흐름 패턴을 결정하기 위해 시뮬레이션이 수행됩니다. 이러한 패턴은 평균 흐름과 흐름의 대부분의 운동 에너지를 포함하는 가장 큰 소용돌이 구조로 구성됩니다. 이 에너지가 더 큰 소용돌이에서 제거되고 가장 작은 소용돌이에 의해 열로 소산되는 방법에 대한 세부 사항은 중요하지 않을 수 있습니다. 그러한 경우 수치 적 방법에 내재 된 소산 메커니즘만으로도 합리적인 결과를 얻을 수 있습니다. 다른 경우에는 일정한 소용돌이 점도 또는 혼합 길이 가정과 같은 간단한 난류 모델을 사용하여 추가 소산을 제공 할 수 있습니다.

Turbulence transport equations require more CPU resources and should only be used when there are strong, localized sources of turbulence and when that turbulence is likely to be advected into other important regions of the flow.  When there is reason to seriously question the results of a computation, it is always desirable to seek experimental confirmation.

An excellent introduction to fluid turbulence can be found in the book Elementary Mechanics of Fluids by Hunter Rouse, Dover Publications, Inc., New York (1978).

난류 전송 방정식은 더 많은 CPU 리소스를 필요로하며 강력하고 국부 화 된 난기류 소스가 있고 그 난류가 흐름의 다른 중요한 영역으로 전파 될 가능성이있는 경우에만 사용해야합니다. 계산 결과에 매우 의문이 생길 경우는 실험에 의해 확인하는 것이 좋습니다.

유체 난류에 대한 훌륭한 소개는 Hunter Rouse, Dover Publications, Inc., New York (1978)의 책 Elementary Mechanics of Fluids에서 찾을 수 있습니다.

주조 분야

Metal Casting

주조제품, 금형의 설계 과정에서 FLOW-3D의 사용은 회사의 수익성 개선에 직접적인 영향을 줍니다.
(주)에스티아이씨앤디에서는  FLOW-3D를 통해 해결한 수많은 경험과 전문 지식을 엔지니어와 설계자에게 제공합니다.
품질 및 생산성 문제는 빠른 시간 안에 시뮬레이션을 통해 예측하므로써 낮은 비용으로 해결 될 수 있습니다. FLOW-3D는 특별히 주조해석의 정확성향상을 위한 다양한 설계 물리 모델들을 포함하고 있습니다.
이 모델에는 lost foam 주조, Non-newtonian 유체 및 금형의 다이싸이클링 해석에 대한 알고리즘등을 포함하고 있습니다.
시뮬레이션의 정확성과 주조 제품의 품질을 향상시키고자 한다면, FLOW-3D는 여러분들의 이러한 요구를 충족시키는 제품입니다.

Ladle Pour Simulation by Nemak Poland Sp. z o.o.

수자원 분야

실제 지형을 적용하여 3차원 shallow water hybrid model을 이용한 댐 붕괴 시뮬레이션

FLOW-3D는 자유표면 흐름이 있는 수치해석 알고리듬에 의해 유동의 표면이 시공간적으로 변하는 모사를 위한 이상적인 도구라고 할 수 있습니다. 자유 표면은 물과 공기 같은 높은 비율의 밀도 변화를 가지는 유체들 사이의 특정한 경계을 일컫습니다. 자유 표면 흐름을 모델링하는 것은 일반적인 유동방정식과 난류 모델이 결합 된 고급 알고리즘을 필요로 합니다. 이 기능은 FLOW-3D로 하여금 침수 구조에 의해 형성된 방수, 수력 점프 및 수면 변화의 흐름의 궤적을 포착 할 수 있습니다.   Downloads

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주조분야
  • Gravity Pour 중력 주조
  • High Pressure Die Casting 고압 다이캐스팅
  • Tilt Casting 경동 주조
  • Centrifugal Casting 원심 주조
  • Investment Casting 정밀 주조
  • Vacuum Casting 진공 주조
  • Continuous Casting 연속 주조
  • Lost Foam Casting 소실 모형 주조
  • Fill and Defects Tracking 용탕 주입 및 결함 추적
  • Solidification and Shrinkage 응고 및 수축 해석
  • Thermal Stress Evolution and Deformation 열응력 및 변형 해석
물 및 환경 응용 분야
  • Wastewater Treatment and Recovery 폐수 처리 및 복구
  • Pump Stations 펌프장
  • Dams, Weirs, Spillways 댐, 위어, 여수로
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  • Inundation & Flooding 침수 및 범람
  • Open Channel Flow 개수로 흐름
  • Sediment and Scour 퇴적 및 세굴(쇄굴)
  • Plumes, Hydraulic Zones of Influence 기둥, 수리 영향 구역
  • Coastal and Critical Infrastructure Wave Run-Up 연안 및 핵심 인프라 웨이브 런업

에너지 분야
  • Fuel/cargo sloshing in oceangoing containers 해양 컨테이너 용 연료 /화물 슬로싱
  • Offshore platform wave effects 근해 플랫폼 파 영향
  • Separation devices undergoing 6 DOF motion 6 자유도 운동을하는 분리 장치
  • Wave energy converters 파동 에너지 변환기
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  • Opto-Microfluidics 광 마이크로 유체
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  • Fuel Cells 연료 전지들
용접 제조
  • Laser Welding 레이저 용접
  • Laser Metal Deposition 레이저 금속 증착
  • Additive Manufacturing 첨가제 제조
  • Multi-Layer Build 다중 레이어 빌드
  • Polymer 3D Printing 폴리머 3D 프린팅
코팅 분야
  • Curtain Coating 커튼 코팅
  • Dip Coating 딥 코팅
  • Gravure Printing 그라비아 코팅
  • Roll Coating 롤 코팅
  • Slide Coating 슬라이드 코팅
  • Slot Coating 슬롯 코팅
  • Contact Insights 접촉면 분석
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  • Breakwater Structures 방파제 구조물
  • Offshore Structures 항만 연안 구조물
  • Ship Hydrodynamics 선박 유체 역학
  • Sloshing & Slamming 슬로싱 & 슬래 밍
  • Tsunamis 쓰나미 해석
생명공학 분야
  • Active Mixing 액티브 믹싱
  • Chemical Reactions 화학 반응
  • Dissolution 용해
  • Drug Delivery 약물 전달
  • Drug Particles 마약 입자
  • Microdispensers 마이크로 디스펜서
  • Passive Mixing 패시브 믹싱
  • Piezo Driven Pumps 피에조 구동 펌프
자동차 분야
  • Fuel Tanks 연료 탱크
  • Early Fuel Shut-Off 초기 연료 차단
  • Gear Interaction 기어 상호 작용
  • Filters 필터
  • Degas Bottles 병의 가스제거
우주 항공 분야
  • Sloshing Dynamics 슬로싱 동역학
  • Electric Charge Distribution 전기 충전 배분
  • PMDs PMD