Figure 1: Mold drawings

3D Flow and Temperature Analysis of Filling a Plutonium Mold

플루토늄 주형 충전의 3D 유동 및 온도 분석

Authors: Orenstein, Nicholas P. [1]

Publication Date:2013-07-24
Research Org.: Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Sponsoring Org.: DOE/LANL
OSTI Identifier: 1088904
Report Number(s): LA-UR-13-25537
DOE Contract Number: AC52-06NA25396
Resource Type: Technical Report
Country of Publication: United States
Language: English
Subject: Engineering(42); Materials Science(36); Radiation Chemistry, Radiochemistry, & Nuclear Chemistry(38)

Introduction

The plutonium foundry at Los Alamos National Laboratory casts products for various special nuclear applications. However, plutonium’s radioactivity, material properties, and security constraints complicate the ability to perform experimental analysis of mold behavior. The Manufacturing Engineering and Technologies (MET-2) group previously developed a graphite mold to vacuum cast small plutonium disks to be used by the Department of Homeland Security as point sources for radiation sensor testing.

A two-stage pouring basin consisting of a funnel and an angled cavity directs the liquid into a vertical runner. A stack of ten disk castings connect to the runner by horizontal gates. Volumetric flow rates were implemented to limit overflow into the funnel and minimize foundry returns. Models using Flow-3D computational fluid dynamics software are employed here to determine liquid Pu flow paths, optimal pour regimes, temperature changes, and pressure variations.

Setup

Hardcopy drawings provided necessary information to create 3D .stl models for import into Flow-3D (Figs. 1 and 2). The mesh was refined over several iterations to isolate the disk cavities, runner, angled cavity, funnel, and input pour. The final flow and mold-filling simulation utilizes a fine mesh with ~5.5 million total cells. For the temperature study, the mesh contained 1/8 as many cells to reduce computational time and set temperatures to 850 °C for the molten plutonium and 500 °C for the solid graphite mold components (Fig. 3).

Flow-3D solves mass continuity and Navier-Stokes momentum equations over the structured rectangular grid model using finite difference and finite volume numerical algorithms. The solver includes terms in the momentum equation for body and viscous accelerations and uses convective heat transfer.

Simulation settings enabled Flow-3D physics calculations for gravity at 980.665 cm/s 2 in the negative Z direction (top of mold to bottom); viscous, turbulent, incompressible flow using dynamically-computed Renormalized Group Model turbulence calculations and no-slip/partial slip wall shear, and; first order, full energy equation heat transfer.

Mesh boundaries were all set to symmetric boundary conditions except for the Zmin boundary set to outflow and the Zmax boundary set to a volume flow. Vacuum casting conditions and the high reactivity of remaining air molecules with Pu validate the assumption of an initially fluidless void.

Results

The flow follows a unique three-dimensional path. The mold fills upwards with two to three disks receiving fluid in a staggered sequence. Figures 5-9 show how the fluid fills the cavity, and Figure 7 includes the color scale for pressure levels in these four figures. The narrow gate causes a high pressure region which forces the fluid to flow down the cavity centerline.

It proceeds to splash against the far wall and then wrap around the circumference back to the gate (Figs. 5 and 6). Flow in the angled region of the pouring basin cascades over the bottom ledge and attaches to the far wall of the runner, as seen in Figure 7.

This channeling becomes less pronounced as fluid volume levels increase. Finally, two similar but non-uniform depressed regions form about the centerline. These regions fill from their perimeter and bottom until completion (Fig. 8). Such a pattern is counter, for example, to a steady scenario in which a circle of molten Pu encompassing the entire bottom surface rises as a growing cylinder.

Cavity pressure becomes uniform when the cavity is full. Pressure levels build in the rising well section of the runner, where impurities were found to settle in actual casting. Early test simulations optimized the flow as three pours so that the fluid would never overflow to the funnel, the cavities would all fill completely, and small amounts of fluid would remain as foundry returns in the angled cavity.

These rates and durations were translated to the single 2.7s pour at 100 cm 3 per second used here. Figure 9 shows anomalous pressure fluctuations which occurred as the cavities became completely filled. Multiple simulations exhibited a rapid change in pressure from positive to negative and back within the newly-full disk and surrounding, already-full disks.

The time required to completely fill each cavity is plotted in Figure 10. Results show negligible temperature change within the molten Pu during mold filling and, as seen in Figure 11, at fill completion.

Figure 1: Mold drawings
Figure 1: Mold drawings
Figure 2: Mold Assembly
Figure 2: Mold Assembly
Figure 4: Actual mold and cast Pu
Figure 4: Actual mold and cast Pu
Figure 5: Bottom cavity filling
from runner
Figure 5: Bottom cavity filling from runner
Figure 6: Pouring and filling
Figure 6: Pouring and filling
Figure 8: Edge detection of cavity fill geometry. Two similar depressed areas form
about the centerline. Top cavity shown; same pressure scale as other figures
Figure 8: Edge detection of cavity fill geometry. Two similar depressed areas form about the centerline. Top cavity shown; same pressure scale as other figures
Figure 10: Cavity fill times,from first fluid contact with pouring basin, Figure 11:Fluid temperature remains essentially constant
Figure 10: Cavity fill times,from first fluid contact with pouring basin, Figure 11:Fluid temperature remains essentially constant

Conclusions

Non-uniform cavity filling could cause crystal microstructure irregularities during solidification. However, the small temperature changes seen – due to large differences in specific heat between Pu and graphite – over a relatively short time make such problems unlikely in this case.

In the actual casting, cooling required approximately ten minutes. This large difference in time scales further reduces the chance for temperature effects in such a superheated scenario. Pouring basin emptying decreases pressure at the gate which extends fill time of the top two cavities.

The bottom cavity takes longer to fill because fluid must first enter the runner and fill the well. Fill times continue linearly until the top two cavities. The anomalous pressure fluctuations may be due to physical attempts by the system to reach equilibrium, but they are more likely due to numerical errors in the Flow3D solver.

Unsuccessful tests were performed to remove them by halving fluid viscosity. The fine mesh reduced, but did not eliminate, the extent of the fluctuations. Future work is planned to study induction and heat transfer in the full Pu furnace system, including quantifying temporal lag of the cavity void temperature to the mold wall temperature during pre-heat and comparing heat flux levels between furnace components during cool-down.

Thanks to Doug Kautz for the opportunity to work with MET-2 and for assigning an interesting unclassified project. Additional thanks to Mike Bange for CFD guidance, insight of the project’s history, and draft review.

Fig. 6 LH2 isotherms at 1020 s.

액체-수소 탱크를 위한 결합된 열역학-유체-역학 솔루션

Coupled thermodynamic-fluid-dynamic solution for a liquid-hydrogen tank

G. D. Grayson

Published Online:23 May 2012 https://doi.org/10.2514/3.26706

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Introduction

ROPELLANT 열 성층화 및 외부 교란에 대한 유체 역학적 반응은 발사체와 우주선 모두에서 중요합니다. 과거에는 결합된 솔루션을 제공할 수 있는 충분한 계산 기술이 부족하여 이러한 문제를 개별적으로 해결했습니다.1

이로 인해 모델링 기술의 불확실성을 허용하기 위해 큰 안전 계수를 가진 시스템이 과도하게 설계되었습니다. 고중력 환경과 저중력 환경 모두에서 작동하도록 설계된 미래 시스템은 기술적으로나 재정적으로 실현 가능하도록 과잉 설계 및 안전 요소가 덜 필요합니다.

이러한 유체 시스템은 열역학 및 유체 역학이 모두 중요한 환경에서 모델의 기능을 광범위하게 검증한 후에만 고충실도 수치 모델을 기반으로 할 수 있습니다. 상용 컴퓨터 코드 FLOW-3D2는 유체 역학 및 열 모델링 모두에서 가능성을 보여주었으며,1 따라서 열역학-유체-역학 엔지니어링 문제에서 결합된 질량, 운동량 및 에너지 방정식을 푸는 데 적합함을 시사합니다.

발사체의 복잡한 액체 가스 시스템에 대한 포괄적인 솔루션을 달성하기 위한 첫 번째 단계로 액체 유체 역학과 열역학을 통합하는 제안된 상단 단계 액체-수소(Lit) 탱크의 간단한 모델이 여기에 제시됩니다. FLOW-3D FLOW-3D 프로그램은 Los Alamos Scientific Laboratory에서 시작되었으며 마커 및 셀 방법에서 파생된 것입니다.3 현재 상태로 가져오기 위해 수년에 걸쳐 광범위한 코드 수정이 이루어졌습니다.2

프로그램은 다음과 같습니다. 일반 Navier-Stokes 방정식을 풀기 위해 수치 근사의 중앙 유한 차분 방법을 사용하는 3차원 유체 역학 솔버입니다. 모멘텀 및 에너지 방정식의 섹션은 특정 응용 프로그램에 따라 활성화 또는 비활성화할 수 있습니다.

코드는 1994년 9월 13일 접수를 인용하기 위해 무액체 표면, 복잡한 용기 기하학, 여러 점성 모델, 표면 장력, 다공성 매체를 통한 흐름 및 응고와 함께 압축성 또는 비압축성 유동 가정을 제공합니다. 1995년 1월 15일에 받은 개정; 1995년 2월 17일 출판 승인.

ROPELLANT thermal stratification and fluid-dynamic response to external disturbances are of concern in both launch vehicles and spacecraft. In the past these problems have been addressed separately for want of sufficient computational technology to provide for coupled solutions.1 This has resulted in overdesigned systems with large safety factors to allow for the uncertainty in modeling techniques. Future systems designed to perform in both highand low-gravity environments will require less overdesign and safety factors to be technically and financially feasible. Such fluid systems can be based on high-fidelity numerical models only after extensive validation of the models’ capabilities in environments where both the thermodynamics and the fluid dynamics are important. The commercial computer code FLOW-3D2 has shown promise in both fluid-dynamic and thermal modeling,1 thus suggesting suitability for solving the coupled mass, momentum, and energy equations in thermodynamic-fluid-dynamic engineering problems. As a first step to achieving a comprehensive solution for complex liquidgas systems in a launch vehicle, a simple model of a proposed upper-stage liquid-hydrogen (Lit) tank incorporating the liquid fluid dynamics and thermodynamics is presented here. FLOW-3D The FLOW-3D program originated at the Los Alamos Scientific Laboratory and is a derivative of the marker-and-cell method.3 Extensive code modifications have been made over the years to bring it to its present state.2 The program is a three-dimensional fluiddynamic solver that uses a central finite-difference method of numerical approximation to solve the general Navier-Stokes equations. Sections of the momentum and energy equations can be enabled or disabled depending on the particular application. The code provides compressible or incompressible flow assumptions with liquid free surfaces, complex container geometries, several viscosity models, surface tension, flow though porous media, and solidification, to cite Received Sept. 13, 1994; revision received Jan. 15, 1995; accepted for publication Feb. 17, 1995. Copyright © 1995 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved. *Engineer/Scientist, Propulsion Analysis and Hydraulics, Space Transportation Division, MS 13-3, 5301 Bolsa Avenue. Member AIAA. a few of the possibilities. Further information on FLOW-3D’s capabilities and details of the numerical algorithms can be found in Ref. 2

Fig. 1 Axial-acceleration history.
Fig. 1 Axial-acceleration history.
Fig. 2 Heat flux histories.
Fig. 2 Heat flux histories.
Fig. 3 LHi isotherms at 50 s.
Fig. 3 LHi isotherms at 50 s.
Fig. 4 LH2 isotherms at 300 s
Fig. 4 LH2 isotherms at 300 s
Fig. 5 LH2 isotherms at 880 s.
Fig. 5 LH2 isotherms at 880 s.
Fig. 6 LH2 isotherms at 1020 s.
Fig. 6 LH2 isotherms at 1020 s.
Fig. 7 Tank-outlet temperature history.
Fig. 7 Tank-outlet temperature history.
Fig. 1. A typical Boiling Water Reactor (BWR) and selected segment of study for simulation

Understanding dry-out mechanism in rod bundles of boiling water reactor

끓는 물 원자로 봉 다발의 건조 메커니즘 이해

Liril D.SilviaDinesh K.ChandrakercSumanaGhoshaArup KDasb
aDepartment of Chemical Engineering, Indian Institute of Technology, Roorkee, India
bDepartment of Mechanical Engineering, Indian Institute of Technology, Roorkee, India
cReactor Engineering Division, Bhabha Atomic Research Centre, Mumbai, India

Abstract

Present work reports numerical understanding of interfacial dynamics during co-flow of vapor and liquid phases of water inside a typical Boiling Water Reactor (BWR), consisting of a nuclear fuel rod bundle assembly of 7 pins in a circular array. Two representative spacings between rods in a circular array are used to carry out the simulation. In literature, flow boiling in a nuclear reactor is dealt with mechanistic models or averaged equations. Hence, in the present study using the Volume of Fluid (VOF) based multiphase model, a detailed numerical understanding of breaking and making in interfaces during flow boiling in BWR is targeted. Our work will portray near realistic vapor bubble and liquid flow dynamics in rod bundle scenario. Constant wall heat flux for fuel rod and uniform velocity of the liquid at the inlet patch is applied as a boundary condition. The saturation properties of water are taken at 30 bar pressure. Flow boiling stages involving bubble nucleation, growth, merging, local dry-out, rewetting with liquid patches, and complete dry-out are illustrated. The dry-out phenomenon with no liquid presence is numerically observed with phase fraction contours at various axial cut-sections. The quantification of the liquid phase fraction at different axial planes is plotted over time, emphasizing the progressive dry-out mechanism. A comparison of liquid-vapor distribution for inner and outer rods reveals that the inner rod’s dry-out occurs sooner than that of the outer rod. The heat transfer coefficient to identify the heat dissipation capacity of each case is also reported.

현재 작업은 원형 배열에 있는 7개의 핀으로 구성된 핵연료봉 다발 어셈블리로 구성된 일반적인 끓는 물 원자로(BWR) 내부의 물의 증기 및 액체상의 동시 흐름 동안 계면 역학에 대한 수치적 이해를 보고합니다.

원형 배열의 막대 사이에 두 개의 대표적인 간격이 시뮬레이션을 수행하는 데 사용됩니다. 문헌에서 원자로의 유동 비등은 기계론적 모델 또는 평균 방정식으로 처리됩니다.

따라서 VOF(Volume of Fluid) 기반 다상 모델을 사용하는 본 연구에서는 BWR에서 유동 비등 동안 계면의 파괴 및 생성에 대한 자세한 수치적 이해를 목표로 합니다.

우리의 작업은 막대 번들 시나리오에서 거의 사실적인 증기 기포 및 액체 흐름 역학을 묘사합니다. 연료봉에 대한 일정한 벽 열유속과 입구 패치에서 액체의 균일한 속도가 경계 조건으로 적용됩니다. 물의 포화 특성은 30bar 압력에서 취합니다.

기포 핵 생성, 성장, 병합, 국소 건조, 액체 패치로 재습윤 및 완전한 건조를 포함하는 유동 비등 단계가 설명됩니다. 액체가 존재하지 않는 건조 현상은 다양한 축 단면에서 위상 분율 윤곽으로 수치적으로 관찰됩니다.

다른 축 평면에서 액상 분율의 정량화는 점진적인 건조 메커니즘을 강조하면서 시간이 지남에 따라 표시됩니다. 내부 막대와 외부 막대의 액-증기 분포를 비교하면 내부 막대의 건조가 외부 막대보다 더 빨리 발생함을 알 수 있습니다. 각 경우의 방열 용량을 식별하기 위한 열 전달 계수도 보고됩니다.

Fig. 1. A typical Boiling Water Reactor (BWR) and selected segment of study for simulation
Fig. 1. A typical Boiling Water Reactor (BWR) and selected segment of study for simulation
Fig. 2. (a-c) dimensions and mesh configuration for G = 6 mm; (d-f) dimensions and mesh configuration for G = 0.6 mm
Fig. 2. (a-c) dimensions and mesh configuration for G = 6 mm; (d-f) dimensions and mesh configuration for G = 0.6 mm
Fig. 3. Simulating the effect of spacer (a) Spacer configuration around rod bundle (b) Mesh structure in spacer zone (c) Distribution of vapor bubbles in a rod bundle with spacer (d) Liquid phase fraction comparison for geometry with and without spacer (e,f,g) Wall temperature comparison for geometry with and without spacer; WS: With Spacer, WOS: Without Spacer; Temperature in the y-axis is in (f) and (g) is same as (e).
Fig. 3. Simulating the effect of spacer (a) Spacer configuration around rod bundle (b) Mesh structure in spacer zone (c) Distribution of vapor bubbles in a rod bundle with spacer (d) Liquid phase fraction comparison for geometry with and without spacer (e,f,g) Wall temperature comparison for geometry with and without spacer; WS: With Spacer, WOS: Without Spacer; Temperature in the y-axis is in (f) and (g) is same as (e).
Fig. 4. Validation of the present numerical model with crossflow boiling over a heated cylindrical rod [40]
Fig. 4. Validation of the present numerical model with crossflow boiling over a heated cylindrical rod [40]
Fig. 5. Grid-Independent study in terms of vapor volume in 1/4th of computational domain
Fig. 5. Grid-Independent study in terms of vapor volume in 1/4th of computational domain
Fig. 6. Interface contour for G = 6 mm; ul = 1.2 m/s; q˙ w = 396 kW/m2; they are showing nucleation, growth, merging, and pseudo-steady-state condition.
Fig. 6. Interface contour for G = 6 mm; ul = 1.2 m/s; q˙ w = 396 kW/m2; they are showing nucleation, growth, merging, and pseudo-steady-state condition.
Fig. 7. Interface contours for G = 0.6 mm; ul = 1.2 m/s; q˙ w = 396 kW/m2; It shows dry-out at pseudo-steady-state near the exit
Fig. 7. Interface contours for G = 0.6 mm; ul = 1.2 m/s; q˙ w = 396 kW/m2; It shows dry-out at pseudo-steady-state near the exit
Fig. 8. Vapor-liquid distribution across various distant cross-sections (Black color indicates liquid; Gray color indicates vapor); Magnification factor: 1 × (for a and b), 1.5 × (for c and d)
Fig. 8. Vapor-liquid distribution across various distant cross-sections (Black color indicates liquid; Gray color indicates vapor); Magnification factor: 1 × (for a and b), 1.5 × (for c and d)
Fig. 21. Two-phase flow mixture velocity (u¯z); for G = 6 mm, r = 5 means location at inner heated wall and r = 25 means location at outer adiabatic wall; for G = 0.66 mm, r = 5 means location at inner heated wall and r = 16.6 mm means location at outer adiabatic wall.
Fig. 21. Two-phase flow mixture velocity (u¯z); for G = 6 mm, r = 5 means location at inner heated wall and r = 25 means location at outer adiabatic wall; for G = 0.66 mm, r = 5 means location at inner heated wall and r = 16.6 mm means location at outer adiabatic wall.

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Figure 6: Fluid firing of test model

버블 제트 마이크로 액추에이터에서 기포 성장 및 액체 흐름의 수치 시뮬레이션

Numerical analysis of liquid flow characteristics according to the design parameters of a bubble jet microactuator

마이크로 액추에이터 챔버 및 노즐 내부의 유체 역학의 수치 모델이 제공됩니다. 모델에는 저장소로부터의 잉크 흐름, 기포 형성 및 성장, 노즐을 통한 배출, 리필 프로세스의 역학이 포함됩니다. 고 테이퍼 노즐은 전체 액추에이터 성능 설계에 매우 중요한 매개 변수 중 하나이기 때문에 노즐 두께, 직경 및 테이퍼 각도의 변화에 ​​따른 효과를 시뮬레이션하고 일부 결과를 실험 결과와 비교합니다.

얇고 테이퍼형 노즐을 통한 잉크 방울 배출이 보다 안정적이고 빠르고 견고하다는 것이 확인되었습니다.

키워드: Numerical smulation, Micro actuator; Bubble growth, Drop ejection, Volume of fluid

Figure 1: The commercial thermal micro actuator
Figure 1: The commercial thermal micro actuator
Table 1: Prediction results of the effects of nozzle thickness and diameter change
Table 1: Prediction results of the effects of nozzle thickness and diameter change
Figure 2: Designed polyimide nozzles
Figure 2: Designed polyimide nozzles
Figure 3: SEM photograph of one nozzle
Figure 3: SEM photograph of one nozzle
Figure 5: Geometry of test model
Figure 5: Geometry of test model
Figure 6: Fluid firing of test model
Figure 6: Fluid firing of test model

Conclusions

수치 시뮬레이션은 마이크로 버블 증가 및 낙하 방출 현상의 예측에 성공적으로 적용됩니다. 노즐 두께의 변화 결과와 비교했을 때, 우리는 얇은 노즐이 더 빠른 방울을 만든다는 것을 발견했습니다. 또한 노즐 직경이 증가하면 방울 부피가 증가할 수 있습니다. 이 수치 시뮬레이션에서는 노즐 직경의 20%를 증가시키면 방울 부피는 49.3% 증가하고 노즐 두께의 20%를 감소시키면 방울 속도는 약 8.5% 증가합니다. 노즐 테이퍼 각도 변경의 예측 결과에 따르면, 테이퍼형 노즐이 더 빠른 속도로 거의 동일한 유체량을 보인다는 결론을 내렸습니다. 방울 속도만이 방울 배출의 품질을 향상시킬 수 있는 유일한 요인은 아니지만, 방울이 빠르면 일반적으로 위성이 줄어들고, 물에 젖지 않는 상태가 개선되며, 정렬 효과가 좋아지며, 직선 방출이 가능합니다.

References

SHOWING 1-9 OF 9 REFERENCESThree-Dimensional Calculation of Bubble Growth and Drop Ejection in a Bubble Jet Printer

SaveAlertResearch FeedBubble Dynamics in Boiling Under High Heat Flux Pulse Heating

SaveAlertResearch FeedLBM simulation on friction and mass flow analysis in a rough microchannel

SaveAlertResearch FeedAnalysis on the performance and internal flow of a tubular type hydro turbine for vessel cooling system

SaveAlertResearch FeedAn Introduction to Microelectromechanical Systems Engineering

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SaveAlertResearch FeedInkjet technology and product development strategies

  • Carlsbad: Torrey Pines Research, pp. 115-117, 2000.
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Particle tolerant architecture

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Drop Generation Process in TIJ Printheads

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레이저 용접 수치해석 (FLOW-3D WELD)

FLOW-3D WELD Products

레이저 용접 수치해석 (FLOW-3D WELD)

FLOW-3D@ WELD는 레이저 용접 공정에 대한 정확한 시뮬레이션 기능을 제공하여 최적화된 공정을 개발하게 합니다. 더 나은 공정 제어를 통해 기공, 열 영향 영역을 최소화하고 미세 구조 변화를 제어할 수 있습니다.

레이저 용접 프로세스를 정확하게 시뮬레이션하기 위해 FLOW-3D@ WELD는 레이저 열원, 레이저-재료 상호 작용, 유체 흐름, 열 전달, 표면 장력, 응고, 다중 레이저 반사 및 위상 변화와 같은 모든 관련 물리 모델을 제공합니다.

Laser Welding

최근에는 뛰어난 생산성과 속도, 낮은 열 입력이 결합되어 기존의 용접 프로세스를 대체하는 레이저 용접 프로세스가 주목 받고 있습니다. 레이저 용접이 제공하는 장점은 용접강도가 좋고, 열 영향 부위가 작으며, 정밀도가 낮고 변형이 적으며, 강철, 알루미늄, 티타늄 및 이종 금속을 포함한 광범위한 금속 및 합금을 용접 할 수 있는 기능이 있습니다.

FLOW-3D@는 레이저 용접 공정에 대한 강력한 통찰력을 제공하고 궁극적으로 프로세스 최적화를 달성하는 데 도움이 됩니다.

보다 나은 프로세스 제어를 통해 기공을 최소화할 수 있습니다. 열 영향부위 및 미세조직을 제어가 가능합니다. FLOW-3D는 자유표면 추적 알고리즘을 통해 매우 복잡한 용접 POOL 시뮬레이션을 해석하는데 매우 적합합니다.

용접 모듈은 레이저 소스에 의해 생성된 Heat flux, 용융 금속에 대한 증발압력, shield gas 효과, 용융 풀의 반동압력 및 다중 레이저 반사와 같은 물리적 모델을 FLOW-3D에 적용하기 위해 개발되었습니다. 키홀 용접과 같은 현실적인 프로세스 시뮬레이션을 위해서는 모든 관련 물리적 현상을 적용하는 것이 중요합니다.

FLOW-3D는 레이저 용접의 conduction and keyhole 방식을 시뮬레이션 할 수 있습니다. 전 세계의 연구원들은 FLOW-3D를 사용하여 용접역학을 분석하고, 공정 매개 변수를 최적화하여 기공을 최소화하며, 레이저 용접공정에서의 dendrite 결정 성장 양상을 예측합니다.

Shallow penetration weld (top left); deep penetration weld with shield gas effects (top right); deep penetration weld with shield gas and evaporation pressure (bottom left); and deep penetration weld with shield gas, evaporation pressure and multiple laser reflections effects (bottom right).

Full Penetration Laser Welding Experiments

한국 카이스트와 독일 BAM은 16K kW레이저를 사용하여 10mm강판에 완전 침투 레이저 용접 실험을 수행하였습니다. CCD카메라의 도움을 받아 완전 용입 레이저 용접으로 형성된 상단 및 하단 용융풀 거동을 확인할 수 있었습니다. 그들은 또한 FLOW-3D 로 용접 공정 해석으로 해석과 실험결과의 경향이 일치하는 것을 알 수 있었습니다.

Experimental setup with CCD cameras observing the top and bottom molten pools
Schematic of computation domain in FLOW-3D

 

Simulation results at the top show melt pool lengths of 8mm and 15mm, whereas experiments indicated melt pool lengths of 7mm and 13mm

Laser Welding Porosity Case Study

General Motors, Michigan, 중국의 상하이 대학교는 용접 공정 변수, 즉 keyhole 용접에서 기공의 발생에 대해 용접 속도 및 용접 각도와 같은 공정 매개 변수가 미치는 영향을 알아보기 위해 협력하여 연구를 진행하였습니다.

레이저 용접된 Al 접합부 단면의 기공을 분석합니다. Keyhole이 유도 된 기공들은 유동 역학으로 인해 발생되고 균열을 일으킬 수 있습니다. 최적화 공정의 매개변수는 이러한 종류의 기공을 완화할 수 있습니다. FLOW-3D를 사용하여 연구원들은 증발 및 반동 압력, 용융풀, 온도에 따른 표면장력 및 Keyhole내의 다중 레이저 반사, 프레넬 흡수를 포함한 모든 중요한 물리적 현상을 설명했습니다.

연구진은 시뮬레이션 모델을 기반으로 Keyhole 용접에서 생성된 기공들의 주요 원인으로 불안정한 Keyhole을 규정하였습니다. 아래 이미지에서 볼 수 있듯이 뒤쪽 용융 풀의 과도한 재순환은 뒤쪽 용융 풀이 앞쪽 용융 풀 경계를 무너뜨리며 기공들을 생성시킵니다. 갇힌 공간이 증가하는 응고 전면에 의해 갇혔을때 기공들이 발생되었습니다.

Distribution of porosity in longitudinal welding sections as seen in simulations (top) and experiments (bottom)

용접 속도가 빠를수록 더 큰 keyhole이 생성되며 이로 인해, 보다 안정적인 keyhole이 생성됩니다. 연구진은 FLOW-3D를 사용하여 용접 속도와 용접 경사각으로 기공들의 생성을 완화시킬 수 있었습니다.


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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 레이저분야 활용

FLOW-3D 레이저 용접분야 활용

FLOW-3D는 유체의 유동 및 열전달 수치 해석 소프트웨어이며, 자유표면(자유수면)을 가진 유체의 흐름을 정확하게 예측한다. FLOW-3D는 수 많은 물리적 유동 현상에 대한 시뮬레이션 모델을 제공하여, 설계 및 운영 단계에서 엔지니어가 쉽고 정확하게 판단할 수 있도록 해주기 때문에 수리, 주조, 기계, 항공, 용접, 적층 공정, 금속 3D 프린팅 등 여러 분야에서 사용되는 소프트웨어이다. 이번 호에서는 FLOW-3D의 다양한 활용 분야 중에서 레이저 용접 분야(Weld 모듈이 연계된 FLOW-3D Weld를 사용)에 대해 자세히 알아보고자 한다.

레이저 용접은 레이저 광선의 출력을 응용한 용접 방법을 말한다. 레이저 용접의 장점은 용접 강도가 좋고, 열 영향 부위가 작으며, 정밀도가 높고 변형이 적으며 강철, 알루미늄, 티타늄 및 이종 금속을 포함한 광범위한 금속 및 합금을 용접할 수 있다는 것이다.
FLOW-3D Weld는 이러한 레이저 용접 공정에 대해 정확한 결과를 얻게 해 주며, 엔지니어가 레이저 프로세스를 최적화하는데 도움을 준다. FLOW-3D Weld는 레이저 소스에 의해 생성된 Heat flux, 용융 금속에 대한 증발 압력, shield gas 효과, 다중 레이저 반사 등과 같은 물리적 모델을 적용하여 Conduction 용접, Keyhole 용접, Porosity, 용융풀 거동 등을 분석할 수 있다.
이번 호에서는 레이저 용접 프로세스 및 결과물을 최적화하기 위해 필요한 물리적 설정과 대표적인 레이저 용접 해석 예제를 설명하고자 한다.

레이저 광원

1. 레이저 광원
레이저 용접을 하는데 있어 레이저 광원의 설정이 필요하다. FLOW-3D Weld에서 사용되는 레이저 광원은 원통형과 원추형으로 설정할 수 있으며, <그림 1>과 같이 Heat flux를 일정한 상태 또는 가우시안 분포(Gaussian distribution)  형태로 나타낼 수 있다.

레이저 광원의 형태를 원추형으로, 가우시안 분포를 가지도록 Heat flux를 설정하면 <그림 2>와 같이 광원이 원추형으로 나타나며, 반경 거리에 따른 Heat flux의 에너지 밀도 차이도 확인할 수 있다.

그리고, <그림 3>과 같이 레이저 광원의 위치 좌표와 속도 벡터를 설정하면, 레이저의 위치에 대한 광원의 움직임 설정이 가능하다.

기사 상세 내용은 PDF로 제공됩니다.

다운로드[2M] : [201906_FLOW3D_레이저용접]

작성자 | 양정호_에스티아이C&D 솔루션사업부 대리, 조애령_에스티아이C&D 솔루션 사업부 차장
이메일 | flow3d@stikorea.co.kr
홈페이지 | www.flow3d.co.kr

출처 : CAD&Graphics 2019년 06월호

레이저 용접 수치해석(FLOW WELD)

Laser Welding

뛰어난 생산성과 속도, 낮은 열 입력이 결합되어 기존의 용접 프로세스를 대체하는 레이저 용접 프로세스가 있습니다. 레이저 용접이 제공하는 장점은 용접강도가 좋고, 열 영향 부위가 작으며, 정밀도가 높고 변형이 적으며 강철, 알루미늄, 티타늄 및 이종 금속을 포함한 광범위한 금속 및 합금을 용접 할 수 있는 기능이 있습니다.

FLOW-3D는 레이저 용접 공정에 대한 강력한 통찰력을 제공하고 궁극적으로 프로세스 최적화를 달성하는 데 도움이 됩니다. 보다 나은 프로세스 제어를 통해 다공성을 최소화할 수 있습니다. 열 영향부위 및 마이크로-구조를 제어합니다. FLOW-3D는 자유표면 추적 알고리즘으로 인해 매우 복잡한 용접 풀 시뮬레이션을 해석하는데 적합합니다. 용접의 추가 모듈은 레이저 소스에 의해 생성된 Heat flux, 용융 금속에 대한 증발압력, shield gas효과, 용융 풀의 반동압력 및 다중 레이저반사와 같은 물리적 모델을 FLOW-3D에 통합하기 위해 개발되었습니다. Keyhole 용접과 같은 현실적인 프로세스 시뮬레이션을 위해서는 모든 관련 물리적 현상을 포착하는 것이 중요합니다.

FLOW-3D는 레이저 용접의 conduction and keyhole 방식을 시뮬레이션 할 수 있습니다. 전 세계의 연구원들은 FLOW-3D를 사용하여 용접역학을 분석하고, 공정 매개 변수를 최적화하여 다공성을 최소화하며, 레이저 용접공정의 수지결정 성장을 예측합니다.

Shallow penetration weld (top left); deep penetration weld with shield gas effects (top right); deep penetration weld with shield gas and evaporation pressure (bottom left); and deep penetration weld with shield gas, evaporation pressure and multiple laser reflections effects (bottom right).

Full Penetration Laser Welding Experiments

한국 카이스트와 독일 BAM은 16KW레이저를 사용하여 10mm강판에 완전 침투 레이저 용접 실험을 수행하였습니다. CCD카메라의 도움을 받아 완전 용입 레이저 용접으로 형성된 상단 및 하단 용융지 역학을 포착할 수 있었습니다. 그들은 또한 FLOW-3D공정을 시뮬레이션하여 해석과 실험결과가 경향이 일치하는 것을 나타내었습니다.

Experimental setup with CCD cameras observing the top and bottom molten pools
 
Simulation results at the top show melt pool lengths of 8mm and 15mm, whereas experiments indicated melt pool lengths of 7mm and 13mm
 
 
 
 
Schematic of computation domain in FLOW-3D

 

Laser Welding Porosity Case Study

General Motors, Michigan, 중국의 상하이 대학교는 공정변수, 즉 keyhole 용접에서 다공성 발생 에 대해 용접속도 및 용접각도와 같은 공정 매개 변수가 미치는 영향을 이해하기 위해 협력하여 연구를 진행하였습니다.

 
레이저 용접된 Al 접합부 단면의 다공성을 용접합니다. Keyhole 유도 된 다공성은 유동 역학으로 인해 발생되고 균열을 일으킬 수 있습니다. 최적화 공정의 매개변수는 이러한 종류의 다공성을 완화할 수 있습니다. FLOW-3D를 사용하여 연구원들은 증발 및 반동 압력, 용융풀, 온도에 따른 표면장력 및 Keyhole내의 다중 레이저 반사, 프레넬 흡수를 포함한 모든 중요한 물리적 현상을 설명했습니다.

연구진은 시뮬레이션 모델을 기반으로 Keyhole용접에서 유도된 다공성의 주요 원인으로 불안정한Keyhole을 규정하였습니다. 아래 이미지에서 볼 수 있듯이 뒤쪽 용융 풀의 과도한 재순환은 뒤쪽 용융 풀이 앞쪽 용융 풀 경계를 무너뜨리며 다공성을 초래시킵니다. 갇힌 공간이 증가하는 응고 전면에 의해 포착되었을 때 다공성이 유도되었습니다.

용접 속도가 빠를수록 더 큰 keyhole이 생성되며 이로 인해보다 안정적인 keyhole이 구성됩니다. 연구진은 FLOW-3D를 사용하여 높은 용접 속도와 큰 용접 경사각으로 다공성을 완화시킬 수 있다고 예측했습니다.

 
 
Distribution of porosity in longitudinal welding sections as seen in simulations (top) and experiments (bottom)

용접분야 활용

Conduction 용접

하이브리드 레이저 용접

깊은 용접 레이저용접

레이저 적층 공법

TIG 용접

이종소재 레이저 용접

Increasing Productivity by Reducing Ejection Times

Increasing Productivity by Reducing Ejection Times

This article was contributed by Eugene Moore of Hellebusch Tool & Die

시뮬레이션 소프트웨어는 설계자와 엔지니어가 주조 공정의 세부 사항을 이해하고 경쟁사보다 저렴한 비용으로 고품질 부품을 일관성 있게 제작할 수 있게 해주는 유용한 도구입니다. 고압 다이캐스팅에서 시뮬레이션 소프트웨어는 주조 내로 금속을 공급하고 난류로 인한 공기 유입을 방지하기 위해 샷 슬리브 팁의 타이밍을 개선하고 오버 플로우에 대한 가장 효과적인 위치를 식별하는 더 나은 게이팅 시스템을 설계하는 데 사용됩니다. 이 기사에서는 프로세스 시간을 단축하기 위해 부품을 다이에서 배출하기 전에 시간을 줄이는 방법을 살펴 보겠습니다.

비스킷은 주조 과정에서 고형화 된 마지막 장소이기 때문에 우리의 노력에 집중할 수 있는 자연스러운 곳이며 따라서 부품을 언제 꺼낼 수 있는지를 결정합니다. 따라서 비스킷의 응고 시간을 줄일 수 있다면 전반적인 공정 시간을 줄일 수 있습니다. 이를 수행하는 한 가지 방법은 유체와 접촉하는 영역의 양을 늘려 샷팁을 통해 금속에서 더 많은 열을 제거하는 것입니다. 이 경우 정확하게 적용할 수는 없지만, 아래에 표시된 정상상태 대류 방정식을 사용하면 이 접근법의 기초가 가장 쉽게 표시됩니다.

이 방정식에서 열 흐름은 대류 열 전달 계수이고, 금속 팁과 샷 팁 온도의 차이이며, 금속과 접촉하는 샷 팁의 표면적입니다. 그림 1에서 볼 수 있듯이 오늘날 시장에서 볼 수 있는 다양한 형태의 플런저 팁이 금속과 접촉하는 표면적을 증가시키도록 설계되었습니다.

Figure 1: Plunger tips varying in size and surface area [1]

비스킷에서 제거된 열을 증가시키는 또 다른 방법은 비스켓에서 샷 팁과 금속 사이의 온도 차이를 조절하는 것입니다. 이는 그림 2 에서처럼 냉각 선을 팁에 추가하여 수행됩니다. 이 접근법의 단점은 피스톤 어셈블리에 상당한 복잡성을 추가한다는 것입니다.

Figure 2: Cooling within plunger tip [2]

New design

이 기사에서 FLOW-3D Cast를 사용하여 새로운 플런저 팁 디자인을 분석하고 수정되지 않은 표준 원통형 팁과 비교했습니다. 그림 3에서와 같이 끝 부분에 별 모양의 컷 아웃이 있는 원통형 팁으로 구성된 수정된 팁은 수정되지 않은 샷 팁보다 20 % 더 많은 표면적을 갖습니다. 팁은 분석을 위해 물로 냉각되지 않습니다.

Figure 3: Shape of the modified tip to give 20% increase in area

 

Analysis

각 샷 팁 디자인에 대해 충진 (샷 팁 모션 포함) 및 응고 (플로우 미포함) 시뮬레이션을 실행했습니다. 모든 다른 매개 변수는 사례간에 동일합니다. 주요 관심사는 두 가지입니다. 즉, 충전 중 흐름 패턴과 전반적인 응고 시간입니다. 샷 팁 디자인이 파동 및 공기 유입을 유발하는 경우 팁 또는 샷 슬리브 프로파일을 다시 설계해야 하기 때문에 충진 중 흐름 패턴이 중요합니다.

첫 번째 비교는 그림 4에 표시된 샷 슬리브의 흐름 패턴입니다. 이 그림은 수정 된 팁이 있거나 없는 샷 슬리브 중 유체의 이미지를 보여 주며 팁의 모양이 샷 슬리브에 영향을 주지 않는 것으로 나타났습니다. 흐름 패턴. 샷 프로파일에 거의 영향을 주지 않기 때문에 응고에 집중할 수 있습니다.

Figure 4: Flow patterns in the shot sleeves from both tips.

 

두 번째 비교는 응고 시간입니다. 그림 5는 시간의 함수로서 팁의 평균 온도, 시간의 함수로서 금속으로부터 팁으로의 열 유속 및 추출시의 액체 금속의 온도 프로파일을 비교합니다

Figure 5: The above time plots show the average temperature in tip on the upper left hand corner and the heat flux from the metal to the tip in the upper right hand corner. The images below this show the metal temperature within the biscuit of the two castings.

그림 5에서 볼 수 있듯이, 그래프는 금속에서 더 많은 열을 추출했기 때문에 수정 된 팁의 평균 온도가 더 높음을 보여줍니다. 이것은 또한 열 유속 플롯에 표시됩니다. 그래프 아래의 이미지는 비스킷과 탄환의 경계면에서 액체금속을 보여줍니다. 데이터는 수정된 팁을 사용하여 열 제거가 12.7 % 증가한 것을 보여줍니다.

Conclusions

샷 팁 디자인은 주조 부품의 응고 시간에 눈에 띄는 영향을 미칩니다. 시뮬레이션 소프트웨어는 효과를 분석하고 이 지식을 사용하여 프로세스 매개변수를 최적화하는 방법을 제공합니다.

 

References
[1] http://www.metalminotti.it/copper-alloys-semi-and-finished-products/plunger-tips-for-die-casting/
[2] http://www.castool.com/product/plunger-rod

Learn more about the versatility and power of modeling metal casting processes with FLOW-3D Cast >

[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.

 

General Applications Bibliography

다음은 일반 응용 분야의 기술 문서 모음입니다.
이 모든 논문은 FLOW-3D  결과를 포함하고 있습니다. 복잡한 다중 물리와 관련된 문제를 성공적으로 시뮬레이션하기 위해 FLOW-3D를 사용 하는 방법에 대해 자세히 알아보십시오.

Below is a collection of technical papers in our General Applications Bibliography. All of these papers feature FLOW-3D results. Learn more about how FLOW-3D can be used to successfully simulate problems that involve complex multiphysics.

2023년 3월 10일 Upate

20-23   Giampiero Sciortino, Valentina Lombardi, Pietro Prestininzi, Modelling of cantilever-based flow energy harvesters featuring C-shaped vibration inducers: The role of the fluid/beam interaction, Applied Sciences, 13.1; 416, 2023. doi.org/10.3390/app13010416

134-22   Guozheng Ma, Shuying Chen, Haidou Wang, Impact spread behavior of flying droplets and properties of splats, Micro Process and Quality Control of Plasma Spraying, pp. 87-202, 2022. doi.org/10.1007/978-981-19-2742-3_3

111-22   Chia-Lin Chiu, Chia-Ming Fan, Chia-Ren Chu, Numerical analysis of two spheres falling side by side, Physics of Fluids, 34; 072112, 2022. doi.org/10.1063/5.0096534

58-21   Ruizhe Liu, Haidong Zhao, Experimental study and numerical simulation of infiltration of AlSi12 alloys into Si porous preforms with micro-computed tomography inspection characteristics, Journal of the Ceramic Society of Japan, 129.6; pp. 315-322, 2021. doi.org/10.2109/jcersj2.21018

56-20   Nils Steinau, CFD modeling of ascending Strombolian gas slugs through a constricted volcanic conduit considering a non-linear rheology, Thesis, Universität Hamburg, Hamburg, Germany, 2020.

30-20   Bita Bayatsarmadi, Mike Horne, Theo Rodopoulos and Dayalan Gunasegaram, Intensifying diffusion-limited reactions by using static mixer electrodes in a novel electrochemical flow cell, Journal of The Electrochemical Society, 167.6, 2020. doi.org/10.1149/1945-7111/ab7e8f

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.

35-19     Sung-Won Ha, Tae-Won Kim, Joo-Hwan Choi, and Young-Jin Park, Study for flow phenomenon in the circulation water pump chamber using the Flow-3D model, Journal of the Korea Academia-Industrial Cooperation Society, Vol. 20, No. 4, pp. 580-589, 2019. doi: 10.5762/KAIS.2019.20.4.580

27-19     Rolands Cepuritis, Elisabeth L. Skare, Evgeny Ramenskiy, Ernst Mørtsell, Sverre Smeplass, Shizhao Li, Stefan Jacobsen, and Jon Spangeberg, Analysing limitations of the FlowCyl as a one-point viscometer test for cement paste, Construction and Building Materials, Vol. 218, pp. 333-340, 2019. doi: 10.1016.j.conbuildmat.2019.05.127

26-19     Shanshan Hu, Lunliang Duan, Qianbing Wan, and Jian Wang, Evaluation of needle movement effect on root canal irrigation using a computational fluid dynamics model, BioMedical Engineering OnLine, Vol. 18, No. 52, 2019. doi: 10.1186/s12938-019-0679-5

83-18   Elisabeth Leite Skare, Stefan Jacobsen, Rolands Cepuritis, Sverre Smeplass and Jon Spangenberg, Decreasing the magnitude of shear rates in the FlowCyl, Proceedings of the 12th fib International PhD Symposium in Civil Engineering, Prague, Czech Republic, August 29-31, 2018.

71-18   Marc Bascompta, Jordi Vives, Lluís Sanmiqeul and José Juan de Felipe, CFD friction factors verification in an underground mine, Proceedings of the 4th World Congress on Mechanical, Chemical, and Material Engineering, August 16 – 18, 2018, Madrid, Spain, Paper No. MMME 105, 2018. doi.org/10.11159/mmme18.105

56-18   J. Spangenberg, A. Uzala, M.W. Nielsen and J.H. Hattel, A robustness analysis of the bonding process of joints in wind turbine blades, International Journal of Adhesion and Adhesives, vol. 85, pp. 281-285, 2018. doi.org/10.1016/j.ijadhadh.2018.06.009

21-18   Zhang Weikang and Gong Hongwei, Numerical Simulation Study on Characteristics of Airtight Water Film with Flow Deflectors, IOP Conference Series: Earth and Environmental Science vol. 153, no. 3, pp. 032025, 2018. doi.org/10.1088/1755-1315/153/3/032025

59-17  Han Eol Park and In Cheol Bang, Design study on mixing performance of rotational vanes in subchannel with fuel rod bundles, Transactions of the Korean Nuclear Society Autumn Meeting, Gyeongju, Korea, October 26-27, 2017.

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

24-17   Zhiyuan Ge, Wojciech Nemec, Rob L. Gawthorpe, Atle Rotevatn and Ernst W.M. Hansen, Response of unconfined turbidity current to relay-ramp topography: insights from process-based numerical modelling, doi: 10.1111/bre.12255 This article is protected by copyright. All rights reserved.

06-17   Masoud Hosseinpoor, Kamal H. Khayat, Ammar Yahia, Numerical simulation of self-consolidating concrete flow as a heterogeneous material in L-Box set-up: coupled effect of reinforcing bars and aggregate content on flow characteristics, A. Mater Struct (2017) 50: 163. doi:10.1617/s11527-017-1032-8

94-16   Mehran Seyed Ahmadi, Markus Bussmann and Stavros A. Argyropoulos, Mass transfer correlations for dissolution of cylindrical additions in liquid metals with gas agitation, International Journal of Heat and Mass Transfer, Volume 97, June 2016, Pages 767-778

83-16   Masoud Hosseinpoor, Numerical simulation of fresh SCC flow in wall and beam elements using flow dynamics models, Ph.D. Thesis: University of Sherbrooke, September 2016.

51-16   Aditi Verma, Application of computational transport analysis – Oil spill dynamics, Master Thesis: State University of New York at Buffalo, 2016, 56 pages; 1012775

37-16   Hannah Dietterich, Einat Lev, and Jiangzhi Chen, Benchmarking computational fluid dynamics models for lava flow simulation, Geophysical Research Abstracts, Vol. 18, EGU2016-2202, 2016, EGU General Assembly 2016, © Author(s) 2016. CC Attribution 3.0 License.

 19-16   A.J. Vellinga, M.J.B. Cartigny, E.W.M. Hansen, P.J. Tallinga, M.A. Clare, E.J. Sumner and J.T. Eggenhuisen, Process-based Modelling of Turbidity Currents – From Computational Fluid-dynamics to Depositional Signature, Second Conference on Forward Modelling of Sedimentary Systems, 25 April 2016, DOI: 10.3997/2214-4609.201600374

106-15    Hidetaka Oguma, Koji Tsukimoto, Saneyuki Goya, Yoshifumi Okajima, Kouichi Ishizaka, and Eisaku Ito, Development of Advanced Materials and Manufacturing Technologies for High-efficiency Gas Turbines, Mitsubishi Heavy Industries Technical Review Vol. 52 No. 4, December 2015

93-15   James M. Brethour, Modelling of Cavitation within Highly Transient Flows with the Volume of Fluid Method, 1st Pan-American Congress on Computational Mechanics, April 27-29, 2015

90-15   Troy Shinbrot, Matthew Rutala, Andrea Montessori, Pietro Prestininzi and Sauro Succi, Paradoxical ratcheting in cornstarch, Phys. Fluids 27, 103101 (2015); http://dx.doi.org/10.1063/1.4934709

84-15   Nicolas Roussel, Annika Gram, Massimiliano Cremonesi, Liberato Ferrara, Knut Krenzer, Viktor Mechtcherine, Sergiy Shyshko, Jan Skocec, Jon Spangenberg, Oldrich Svec, Lars Nyholm Thrane and Ksenija Vasilic, Numerical simulations of concrete flow: A benchmark comparison, Cem. Concr. Res. (2015), http://dx.doi.org/10.1016/j.cemconres.2015.09.022

02-15   David Souders, FLOW-3D Version 11 Enhances CFD Simulation, Desktop Engineering, January 2015

125-14   Herbert Obame Mve, Romuald Rullière, Rémi Goulet and Phillippe Haberschill, Numerical Analysis of Heat Transfer of a Flow Confined by Wire Screen in Lithium Bromide Absorption Process, Defect and Diffusion Forum, ISSN: 1662-9507, Vol. 348, pp 40-50, doi:10.4028/www.scientific.net/DDF.348.40, © 2014 Trans Tech Publications, Switzerland

55-14   Agni Arumugam Selvi, Effect of Linear Direction Oscillation on Grain Refinement, Master’s Thesis: The Ohio State University, Graduate Program in Mechanical Engineering, Copyright by Agni Arumugam Selvi, 2014

99-13   R. C. Givler and M. J. Martinez, Computational Model of Miniature Pulsating Heat Pipes, SANDIA REPORT, SAND2012-4750, Unlimited Release, Printed January 2013.

82-13    Shizhao Li, Jon Spangenberg, Jesper Hattel, A CFD Approach for Prediction of Unintended Porosities in Aluminum Syntactic Foam A Preliminary Study, 8th International Conference on Porous Metals and Metallic Foams (METFOAM 2013), Raleigh, NC, June 2013

81-13   S. Li, J. Spangenberg, J. H. Hattel, A CFD Model for Prediction of Unintended Porosities in Metal Matrix Composites A Preliminary Study, 19th International Conference on Composite Materials (ICCM 2013), Montreal, Canada, July 2013

78-13   Haitham A. Hussein, Rozi Abdullah, Sobri, Harun and Mohammed Abdulkhaleq, Numerical Model of Baffle Location Effect on Flow Pattern in Oil and Water Gravity Separator Tanks, World Applied Sciences Journal 26 (10): 1351-1356, 2013, ISSN 1818-4952, DOI: 10.5829/idosi.wasj.2013.26.10.1239, © IDOSI Publications, 2013

74-13  Laetitia Martinie, Jean-Francois Lataste, and Nicolas Roussel, Fiber orientation during casting of UHPFRC: electrical resistivity measurements, image analysis and numerical simulations, Materials and Structures, DOI 10.1617/s11527-013-0205-3, November 2013. Available for purchase online at SpringerLink.

67-13 Stefan Jacobsen, Rolands Cepuritis, Ya Peng, Mette R. Geiker, and Jon Spangenberg, Visualizing and simulating flow conditions in concrete form filling using Pigments, Construction and Building Materials 49 (2013) 328–342, © 2013 Elsevier Ltd. All rights reserved. Available for purchase at ScienceDirect.

60-13 Huey-Jiuan Lin, Fu-Yuan Hsu, Chun-Yu Chiu, Chien-Kuo Liu, Ruey-Yi Lee, Simulation of Glass Molding Process for Planar Type SOFC Sealing Devices, Key Engineering Materials, 573, 131, September 2013. Available for purchase at Scientific.net.

32-13 M A Rashid, I Abustan and M O Hamzah, Numerical simulation of a 3-D flow within a storage area hexagonal modular pavement systems, 4th International Conference on Energy and Environment 2013 (ICEE 2013), IOP Conf. Series: Earth and Environmental Science 16 (2013) 012056 doi:10.1088/1755-1315/16/1/012056. Full paper available at IOP.

105-12 Jon Spangenberg, Numerisk modellering af formfyldning ved støbning i selvkompakterende beton, Ph.D. Thesis: Technical University of Denmark, ID: 0eeede98-fb07-4800-86e2-0a6baeb1e7a3, 2012.

100-12 Nurul Hasan, Validation of CFD models using FLOW-3D for a Submerged Liquid Jet, Ninth International Conference on CFD in the Minerals and Process Industries, CSIRO, Melbourne, Australia, 10-12 December 2012.

87-12  Abustan, Ismail, Hamzah, Meor Othman and Rashid, Mohd Aminur, A 3-Dimensional Numerical Study of a Flow within a Permeable Pavement, OIDA International Journal of Sustainable Development, Vol. 04, No. 02, pp. 37-44, April 2012.

86-12 Abustan, Ismail, Hamzah, Meor Othman and Rashid, Mohd Aminur, Review of Permeable Pavement Systems in Malaysia Conditions, OIDA International Journal of Sustainable Development, Vol. 04, No. 02, pp. 27-36, April 2012.

85-12  Mohd Aminur Rashid, Ismail Abustan, Meor Othman Hamzah, Infiltration Characteristic Modeling Using FLOW-3D within a Modular Pavement, Procedia Engineering, Volume 50, 2012, Pages 658-667, ISSN 1877-7058, 10.1016/j.proeng.2012.10.072.

73-12  Mohd Aminur Rashid, Ismail Abustan, Meor Othman Hamzah, Infiltration Characteristic Modeling Using FLOW-3D within a Modular Pavement, Procedia Engineering, Volume 50, 2012, Pages 658-667, ISSN 1877-7058, 10.1016/j.proeng.2012.10.072.

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.

56-12  Giancarlo Alfonsi, Agostino Lauria, Leonardo Primavera, Flow structures around large-diameter circular cylinder, Journal of Flow Visualization and Image Processing, DOI: 10.1615/JFlowVisImageProc.2012005088, 2012. Available for purchase online at Begell Digital Library.

49-12  M. Janocko, M.B.J. Cartigny, W. Nemec, E.W.M. Hansen, Turbidity current hydraulics and sediment deposition in erodible sinuous channels: laboratory experiments and numerical simulations, Marine and Petroleum Geology, Available online 17 September 2012. Available for purchase online at SciVerse.

32-12  Fatih Karadagli, Bruce E. Rittmann, Drew C. McAvoy, and John E. Richardson, Effect of Turbulence on the Disintegration Rate of Flushable Consumer Products, Water Environment Research, Volume 84, Number 5, May 2012

31-12    D. Valero Huerta and R. García-Bartual, Optimization of Air Conditioning Diffusers Location in Large Agricultural Warehouses Using CFD Techniques, International Conference of Agricultural Engineering (CIGR-AgEng2012) Valencia, Spain, July 8-12, 2012

16-12 Yi Fan Fu, Wei Dong, Ying Li, Yi Tan, Ming Hui Yi, Akira Kawasaki, Simulation of the Effects of the Physical Properties on Particle Formation of Pulsated Orifice Ejection Method (POEM), 2012, Advanced Materials Research, 509, 161. Available for purchase online at Scientific.Net.

92-11  Giancarlo Alfonsi, Agostino Lauria, Leonardo Primavera, The lower vertical structure past the Ahmed car model, International Conference on Computational Science, ICCS 2011. Available for purchase online at Begell Digital Library.

80-11  Ismail Abustan, Meor Othman Hamzah, Mohd Aminur Rashid, A 3-Dimensional Numerical Study of a Flow within a Permeable Pavement, OIDA International Conference on Sustainable Development, ISSN 1923-6670, Putrajaya, Malaysia, 5-7th December 2011

66-11   H. Kondo, T. Furukawa, Y. Hirakawa, K. Nakamura, M. Ida, K.Watanabe, T. Kanemura, E. Wakai, H. Horiike, N. Yamaoka, H. Sugiura, T. Terai, A. Suzuki, J. Yagi, S. Fukada, H. Nakamura, I. Matsushita, F. Groeschel, K. Fujishiro, P. Garin and H. Kimura, IFMIF-EVEDA lithium test loop design and fabrication technology of target assembly as a key componentNuclear Fusion Volume 51 Number 12, doi:10.1088/0029-5515/51/12/123008

49-11     N.I. Vatin, A.A. Girgidov, K.I. Strelets, Numerical modelling the three-dimensional velocity field in the cyclone, Inzhenerno-Stroitel’nyi Zhurnal, No. 4, 2011. In Russian.

41-11    Maiko Hosoda, Taichi Hirano, and Keiji Sakai, Low-Viscosity Measurement by Capillary Electromagnetically Spinning Technique, © 2011 The Japan Society of Applied Physics, Japanese Journal of Applied Physics, July 20, 2011.

18-11  Ortloff, C.R., Vogel, M., Spray cooling heat transfer — Test and CFD analysis, Semiconductor Thermal Measurement and Management Symposium (SEMI-THERM), 2011 27th Annual IEEE, 20-24 March 2011, pp 245 – 252, San Jose, CA, 10.1109/STHERM.2011.5767208.

82-10   Dr. John Abbott, Two problems on the flow of viscous sheets of molten glass, 26th Annual Workshop on Mathematical Problems in Industry, Rensselear Polytechnic Institute, June 14-18, 2010

57-10  Chouet, B. A., Dawson, P. B., James, M. R. and Lane, S. J., Seismic source mechanism of degassing bursts at Kilauea Volcano, Hawaii: Results from waveform inversion in the 10–50 s band, J. Geophys. Res., 115, B09311, doi:10.1029/2009JB006661, September 2010. Available online at JOURNAL OF GEOPHYSICAL RESEARCH.

55-10 Pamela Waterman, FEA and CFD: Getting Better All the Time, Desktop Engineering, December 2010.

53-10  Nicolas Fries, Capillary transport processes in porous materials – experiment and model, Cuvillier Verlag Göttingen; 2010; ISBN 978-3-86955-507-2. Available at www.cuvillier.de  and www.amazon.de.

45-10  Meiring Beyers, Thomas Harms, and Johan Stander, Mitigating snowdrift at the elevated SANAE IV research station in Antarctica CFD simulation and field application, The Fifth International Symposium on Computational Wind Engineering (CWE2010), Chapel Hill, North Carolina, USA, May 23-27, 2010.

31-10 J. Spangenberg, N. Roussel, J.H. Hattel, J. Thorborg, M.R. Geiker, H. Stang and J. Skocek, Prediction of the Impact of Flow-Induced Inhomogeneities in Self-Compacting Concrete (SCC), Ch. 25 of “Design, Production and Placement of Self-Consolidating Concrete,” RILEM Bookseries, 2010, Volume 1, Part 5, 209-215, DOI: 10.1007/978-90-481-9664-7_18. Available online at Springer Link.

28-10 Sirisha Burra, Daniel P. Nicolella, W. Loren Francis, Christopher J. Freitas, Nicholas J. Mueschke, Kristin Poole, and Jean X. Jiang, Dendritic processes of osteocytes are mechanotransducers that induce the opening of hemichannels, Proc Natl Acad Sci U S A. 2010 Jul 19. [Epub ahead of print], Available for purchase at PNAS.

19-10 Michael T. Tolley, Michael Kalontarov, Jonas Neubert, David Erickson and Hod Lipson, Stochastic Modular Robotic Systems A Study of Fluidic Assembly Strategies, IEEE Transactions on Robotics, Vol. 26, NO. 3, June 2010

59-17   Han Eol Park and In Cheol Bang, Design study on mixing performance of rotational vanes in subchannel with fuel rod bundles, Transactions of the Korean Nuclear Society Autumn Meeting, Gyeongju, Korea, October 26-27, 2017.

44-09 Micah Fuller, Fabian Bombardelli, Deb Niemeier, Particulate Matter Modeling in Near-Road Vegetation Environments, Contract AQ-04-01: Developing Effective and Quantifiable Air Quality Mitigation Measures, UC Davis, Caltrans, 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).

24-09 Richard C. Givler and Mario J. Martinez, Modeling of Pulsating Heat Pipes, Sandia Report, SAND2009-4520, Sandia National Laboratories, August 2009.

45-08  J. Saeki, Seikei Kakou, Three-Dimensional Flow Analysis of a Thermosetting Compound in a Motor Stator, 20, 750-754 (2008) [in Japanese] (Zipped file contains paper and appendices)

38-08 Yoshifumi Kuriyama, Ken’ichi Yano and Masafumi Hamaguchi, Trajectory Planning for Meal Assist Robot Considering Spilling Avoidance, 17th IEEE International Conference on Control Applications, Part of 2008 1EEE Multi-conference on Systems and Control, San Antonio, Texas, September 3-5, 2008

29-08 Ernst W.M. Hansen, Wojciech Nemec and Snorre Heimsund, Numerical CFD simulations — a new tool for the modelling of turbidity currents and sand dispersal in deep-water basins, Production Geoscience 2008 in Stavanger, Norway, © 2008

17-08 James, M. R., Lane, S. J. & Corder, S. B., Modelling the rapid near-surface expansion of gas slugs in low-viscosity magmas, In Lane S. J., Gilbert J. S. (eds) Fluid Motion in Volcanic Conduits: A Source of Seismic and Acoustic Signals. Geol. Soc., London, Spec. Pub., 307, 147-167, doi: 10.1144/SP307.9. 2008

16-08 Stefano Malavasi, Nicola Trabucchi, Numerical Investigation of the Flow Around a Rectangular Cylinder Near a Solid Wall, BBAA VI International Colloquium on: Bluff Bodies Aerodynamics & Applications, Milano, Italy, July 2008

41-07 Nicolas Roussel, Mette R. Geiker, Frederic Dufour, Lars N. Thrane and Peter Szabo, Computational modeling of concrete flow General Overview, Cement and Concrete Research 37 (2007) 1298-1307, © 2007 Elsevier Ltd.

40-07 Nemec, W., Heimsund, S., Xu, J. & Hansen, E.W.M., Numerical CFD simulation of turbidity currents, British Sedimentological Research Group (BSRG) Annual Meeting, Birmingham, 17-18 December 2007

39-07 Heimsund, S, Xu, J. & Nemec, W., Numerical Simulation of Recent Turbidity Currents in the Monterey Canyon System, Offshore California, American Geophysical Union Fall Meeting, 10-14 December 2007

32-07 James, M. R., Lane, S. J. & Corder, S. B., Modeling the near-surface expansion of gas slugs in basaltic magmaEos Trans. A.G.U., 88(52), Fall Meet. Suppl.. Abs. V12B-03. 2007

31-07 James, M. R., Lane, S. J. and Corder, S. B., Degassing low-viscosity magma: Quantifying the transition between passive bubble-burst and explosive activityE.G.U. Geophys. Res. Abstr., 905336, SRef-ID: 1607-7962/gra/EGU2007-A-05336. 2007

35-06  S. Green and C. Manepally, Software Validation Report for FLOW-3D Version 9.0, Center for Nuclear Waste Regulatory Analyses, August 2006

33-06 N. Roussel, Correlation between yield stress and slump: Comparison between numerical simulations and concrete rheometers results, © RILEM 2006, Materials and Structures (2006) 39:501-509, Purchase online at Springer Link.

32-06 Heimsund, S., Möller, N. and Guargena, C., FLOW-3D simulation of the Ormen Lange field, mid-Norway, In: Hoyanagi, K., Takano, O. and Kano, K. (Ed.), Abstracts, International Association of Sedimentologists 17th International Sedimentological Congress, Fukuoka, Vol. B, p. 107, 2006

10-06 Gengsheng Wei, An Implicit Method to Solve Problems of Rigid Body Motion Coupled with Fluid Flow, Flow Science Technical Note #76, FSI-05-TN76.

8-06 Gengsheng Wei, Three-Dimensional Collision Modeling for Rigid Bodies and its Coupling with Fluid Flow Computation, Flow Science Technical Note #75, FSI-06-TN75.

34-05  Young Bae Kim, Kyung Do Kim, Sang Eui Hong, Jong Goo Kim, Man Ho Park, and Ju Hyun Kim, and Jae Keun Kweon, 3D Simulation of PU Foaming Flow in a Refrigerator Cabinet, Appliance Magazine.com, January 2005.

33-05 N. Roussel, Fifty-cent rheo-meter for yield stress measurements From slump to spreading flow, @2005 by The Society of Rheolgoy, Inc., J. Rheol. 49(3), 705-718 May/June (2005)

32-05 Heimsund, S., Möller, N., Guargena, C. and Thompson, L., Field-scale modeling of turbidity currents by FLOW-3D simulations, In: Workshop Abstracts, Modeling of Turbidity Currents and Related Gravity Currents, University of California, Santa Barbara, 2 p., (2005)

15-05 Gengsheng Wei, A Fixed-Mesh Method for General Moving Objects, Flow Science Technical Note #73, FSI-05-TN73

14-05 James M. Brethour, Incremental Thermoelastic Stress Model, Flow Science Technical Note #72, FSI-05-TN72

9-05 Gengsheng Wei, A Fixed-Mesh Method for General Moving Objects in Fluid Flow, Modern Physics Letters B, Vol. 19, Nos. 28-29 (2005) 1719-1722

1-05 C.W. Hirt, Electro-Hydrodynamics of Semi-Conductive Fluids: With Application to Electro-Spraying Flow Science Technical Note #70, FSI-05-TN70

35-04  J. Saeki, T. Kono and T. Teramae, Seikei Kakou, Formulation of Mathematical Models for Estimating Residual Stress and Strain Components Correlated with 3-D Flow of Thermosetting Compounds, 16, 5, 309-316 (2004) [in Japanese]. (Zipped file contains paper and appendices)

31-04 Heimsund, S., Möller, N., Guargena, C. and Thompson, L., The control of seafloor topography on turbidite sand dispersal in the Ormen Lange field: a large-scale application of FLOW-3D simulations, In: Martinsen, O.J. (Ed.), Abstracts and Proceedings of the Geological Society of Norway (NGF), Deep Water Sedimentary Systems of Arctic and North Atlantic Margins, Stavanger, 3, p. 25, (2004)

26-04 Beyers, J.H.M., Harms, T.M. and Sundsbø, P.A., 2004, Numerical simulation of three dimensional, transient snow drifting around a cube, Journal of wind engineering and industrial aerodynamics, vol. 92, pp. 725-747, ISSN 0167-6105

25-04 Beyers, J.H.M, Harms, T.M. and Sundsbø, P.A., 2004, Numerical simulation of snow drifting around an elevated obstacle, Proceedings of the 5th conference on snow engineering, Davos, Switzerland, pp.185-191

17-04 Michael Barkhudarov, Multi-Block Gridding Technique for FLOW-3D (Revised), Flow Science Technical Note #59-R2, FSI-00-TN59-R2

36-03 Heimsund, S., Hansen, E.W.M. and Nemec, W., Numerical CFD simulation of turbidity currents and comparison with laboratory data, In: Hodgetts, D., Hodgson, D. and Smith, R. (Ed.), Slope Modelling Workshop Abstracts, Experimental, Reservoir and Forward Modelling of Turbidity Currents and Deep-Water Sedimentary Systems, Liverpool Univ., p. 13., (2003b)

35-03 Heimsund, S., Hansen, E.W.M. and Nemec, W. Computational 3-D fluid-dynamics model for sediment transport, erosion and deposition by turbidity currents, In: Nakrem, H.A. (Ed.), Abstracts and Proceedings of the Geological Society of Norway (NGF), Den 18. Vinterkonferansen, Oslo, 1, p. 39., (2003a)

33-03 Beyers, J.H.M., Sundsbø, P.A. and Harms, T.M., 2003, Numerical simulation and verification of drifting snow around a cube, Proceedings of the 11th international conference on wind engineering, Texas Tech University, Lubbock, Texas, USA, pp. 1886-1893

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)

25-03 J. M Brethour, Moving Boundaries an Eularian Approach, Moving Boundaries VII, Computational Modelling of Free and Moving Boundary Problems, A. A. Mammoli & C.A. Brebbia, WIT Press

19-03 James Brethour, Incremental Elastic Stress Model, Flow Science Technical Note (FSI-03-TN64)

18-03 Michael Barkhudarov, Semi-Lagrangian VOF Advection Method for FLOW-3D, Flow Science Technical Note (FSI-03-TN63)

11-02 Junichi Saeki and Tsutomu Kono, Three-Dimensional Flow Analysis of a Thermosetting Compound during Mold Filling, Polymer Processing Society 18th Annual Meeting, June 2002, Guimares, Portugal.

46-01 Yasunori Iwai, Takumi Hayashi, Toshihiko Yamanishi, Kazuhiro Kobayashi and Masataka Nishi, Simulation of Tritium Behavior after Intended Tritium Release in Ventilated Room, Journal of Nuclear Science and Technology, Vol. 38, No. 1, p. 63-75, January 2001

23-01 Borre Bang, Dag Lukkassen, Application of Homogenization Theory Related to Stokes Flow in Porous Media, Applications of Mathematics, Narvik, Norway, No 4, pp. 309-319.

15-01 Ernst Hansen, SINTEF Energy Research, Trondheim, Norway, Computer Simulation Helps Increase Flow Rate in Three-Phase Separator, Drilling Marketplace, Vol 55, No 10, May 15, 2001, pp.14

10-01 Ernst Hansen, SINTEF Energy Research, Phenomeological Modeling and Simulation of Fluid Flow and Separation Behaviour in Offshore Gravity Separators, PVP-Col 431, Emerging Technologies for Fluids, Structures and Fluids, Structures and Fluid Structure Interaction — 2001, ASME 2001, pp. 23-29

7-01 C. Bohm, D. A. Weiss, and C. Tropea, Multi-droplet Impact onto Solid Walls Droplet-droplet Interaction and Collision of Kinemeatic Discontinuities, DaimlerChrysler Research and Technology, ILASS-Europe 2000, September 11-13, 2000

6-01 Ernst Hansen, Simulation Raises Separator Flow RateEngineering Talk, March 21, 2001

3-01 M. Sick, H. Keck, G. Vullioud, and E. Parkinson, New Challenges in Pelton Research

1-01 Y. Darsht, K. Kuvanov, A. Puzanov, I. Kholkin, FLOW-3D in Designing Hydraulic Systems for Heavy Machinery  (in Russian), SAPR I Grafika (CAD and Graphics), August 2000, pp. 50-55.

22-00 A. K. Temu, O. K. Sønju and E. W. M. Hansen, Criteria for Minimum Particle Deposition onto a Cylinder in Crossflow, International Symposium on Multiphase Flow and Transport Phenomena, November 2000, Tekirova, Antalya, Turkey

21-00 Claus Maier, Stefan aus der Wiesche and Eberhard P. Hofer, Impact of Microdrops on Solid Surfaces for DNA-Synthesis, Department of Measurement, Control and Microtechnology, University of Ulm, Technical Proceedings of the 2000 International Conference on Modeling and Simulation of Microsystems, pp. 586-589

11-00 Thomas K. Thiis, A Comparison of Numerical Simulations and Full-scale Measurements of Snowdrifts around Buildings, Wind and Structures – ISSN: 1226-6116,Vol. 3, nr. 2 (2000), pp. 73-81

10-00 P.A. Sundsbo and B. Bang, Snow drift control in residential areas-Field measurements and numerical simulations, Fourth International Conference on Snow Engineering, pp. 377-382

9-00 Thomas K. Thiis and Christian Jaedicke, The Snowdrift Pattern Around Two Cubical Obstacles with Varying Distance—Measurement and Numerical Simulations, Snow Engineering, edited by Hjorth-Hansen, et al, Balkema, Rotterdam, 2000, pp.369-375.

8-00 Thomas K. Thiis and Christian Jaedicke, Changes in the Snowdrift Pattern Caused by a Building Extension—Investigations Through Scale Modeling and Numerical Simulations, Snow Engineering, edited by Hjorth-Hansen, et al, Balkema, Rotterdam, 2000, pp. 363-368

7-00 Bruce Letellier, Louis Restrepo, and Clinton Shaffer, Near-Field Dispersion of Fission Products in Complex Terrain Using a 3-D Turbulent Fluid-Flow Model, CCPS International Conference, San Francisco, CA, September 28-October 1, 1999

6-00 Bruce Letellier, Patrick McClure, and Louis Restrepo, Source-Term and Building-Wake Consequence Modeling for the GODIVA IV Reactor at Los Alamos National Laboratory, 1999 Safety Analysis Workshop, Portland, Oregon, June 13-18, 1999

11-99 Thomas K. Thiis and Yngvar Gjessing, Large-scale Measurements of Snowdrifts Around Flat-roofed and Single-pitch-roofed Buildings, Cold Regions Science and Technology 30, Narvik, Norway, May 17, 1999, pp. 175-181

3-99 A. A. Gubaidullin, Jr., T. N. Dinh, and B. R. Sehgal, Analysis of Natural Convection Heat Transfer and Flows in Internally Heated Stratified Liquid, accepted for publication 33rd Natl. Heat Transfer Conf. CD proceedings, Albuquerque, NM, August 15-17, 1999

20-98 Mark W. Silva, A Computational Study of Highly Viscous Impinging Jets, published by the Amarillo National Resource Center for Plutonium, ANRCP-1998-18, November 1998

17-98 P. A. Sundsbo and B. Bang, 1998, Calculation of Snowdrift Around Roadside Safety Barriers, Proc of the International Snow Science Workshop, Sept. 1998, Sunriver, Oregon, USA 279-283

11-98 P-A Sundsbo, Numerical simulations of wind deflection fins to control snow accumulation in building steps, Journal of Wind Engineering and Industrial Aerodynamics 74-76 (1998) 543-552

23-97  P.E. O’Donoghue, M.F. Kanninen, C.P. Leung, G. Demofonti, and S. Venzi, The development and validation of a dynamic propagation model for gas transmission pipelines, Intl J. Pres. Ves. & Piping 70 (1997) 11-25, P11 : S0308 – 0161 (96) 00012 – 9.

22-97  Christopher J. Matice, Simulation of High Speed Filling, Presented at High Speed Processing & Filling of Plastic Containers, SME, Chicago, Illinois, November 11, 1997.

12-97 B. Entezam and W. K. Van Moorhem, University of Utah, Salt Lake City, UT and J. Majdalani, Marquette University, Milwaukee, WI, Modeling of a Rijke-Tube Pulse Combustor Using Computational Fluid Dynamics, presented at 33rd AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, Seattle, WA, July 6-9, 1997.

11-97 B. Entezam, Computational and Experimental Investigation of Unsteady Flowfield Inside the Rijke Tube, doctoral thesis submitted to University of Utah, Dept. Mechanical Engineering, Salt Lake City, UT, June 1997

2-97 K. Fujisaki, T. Ueyama, and K. Okazawa, Magnetohydrodynamic Calculation of In-Mold Electromagnetic Stirring, Nippon Steel Corp., IEEE Transactions on Magnetics, Vol. 33, No. 2, March 1997

1-97 P. A. Sundsbo, Four Layer Modelling and Numerical Simulations of Snow Drift, to be submitted to the Journal of Glaciology, 1997

23-96 Andy K Palmer, Computational Fluid Dynamic Software Comparison and Electrostatic Precipitator Modeling, Presented to the Faculty of California State University, Summer 1996

21-96 P. A. Sundsbo, Computer Simulation of Snow-Drift around Structures, Proceedings of the 4th Symposium on Building Physics in the Nordic Countries, Vol. 2, 533-539, Finland, 9-10 Sep. 1996

20-96 P. A. Sundsbo and E.W.M. Hansen, Modelling and Numerical Simulation of Snow-Drift around Snow Fences, Proceedings of the 3rd International Conference on Snow Engineering, Sendai, Japan, 26-31 May 1996

19-96 P. A. Sundsbo, Numerical Modelling and Simulation of Snow Accumulations around Porous FencesProceedings of the International Snow Science Workshop, Banff, Alberta, Canada, 6-10 Oct. 1996

18-96 T. Iverson, Editor, Applied Modelling and Simulation, Proceedings of the 38th SIMS Simulation Conference, Norwegian University of Science and Technology, Trondheim, Norway, June 11-13, 1996

17-96 C. L. Parish, Modeling Compressible Flow Through an Orifice Stack Using Numerical Methods, thesis submitted for M.S. Mech. Engineering, NM State University, Las Cruces, NM, December 1996

15-96 T. Wiik and R. K. Calay, A Study of Balcony on Flow-Field and Wind Loads for Low-Rise Buildings, Fourth Symposium on Building Physics in the Nordic Countries, Dipoli, Espoo, Finland, September 1996

14-96 T. Wiik, E.W.M. Hansen, The Assessment of Wind Loads on Roof Overhang of Low-Rise Buildings, Second International Symposium Wind Engineering, Fort Collins, CO, September 1996

13-96 T. Wiik, R. K. Calay, and A. Holdo, A Study of Effects of Eaves on Flow-Field and Wind Loads for Low-Rise Houses, Third International Colloquium on Bluff Body Aerodynamics and Applications, Blacksburg, Virginia, August 1996

11-96 Y. Miyamoto and M. Harada, A Flow Analysis accompanied by Formation of the Liquid Droplets shown with an Animation Display Technique, SEA Corporation, presented at Visualization Information Conference, Tokyo, Japan, July 17, 1996

8-96 J. Bakken, E. Naess, T. Engebretsen, and E. W. M. Hansen, Fluid Flow in Porous Media, proceedings of the 38th SIMS Simulations Conference, Norwegian Univ. of Science & Technology, Trondheim, Norway, June 11-13, 1996

7-96E. W. M. Hansen, Performance of Oil/Water Gravity Separators Imposed to Motion, proceedings of the 38th SIMS Simulations Conference, Norwegian Univ. of Science & Technology, Trondheim, Norway, June 11-13, 1996

8-95 J. J. Francis, Computational Hydrodynamic Study of Flow through a Vertical Slurry Heat Exchanger, NSF Summer Research Program, Dept. Mech. Engineering, Univ. of Nevada Las Vegas, August 9, 1995

4-94 J. L. Ditter and C. W. Hirt, A Scalable Model for Mixing Vessels, Flow Science report, FSI-94-00-1, presented at the 1994 ASME Fluids Engineering Summer Meeting, Incline Village, NV, June 1994

3-94 A. Nielsen, B. Bang, P. A. Sundsbo and T. Wiik, Computer Simulation of Windspeed, Windpressure and Snow Accumulation around Buildings (SNOW-SIM), 1st International Conference on HVAC in Cold Climate, Rovaniemi, Finland, from Narvik Institute of Technology, Narvik, Norway, March 1994

2-94 J. M. Sicilian, Addition of an Extended Bubble Model to FLOW-3D, Flow Science report, FSI-94-58-1, March 1994

1-94 T. Hong, C. Zhu, P. Cal and L-S Fan, Numerical Modeling of Basic Modes of Formation and Interactions of Bubbles in Liquids, Dept. Chem. Engineering, Ohio State University, Columbus, OH 43210, March 1994

14-93 J. L. Ditter and C. W. Hirt, A Scalable Model for Stir Tanks, Flow Science Technical Note #38, December 1993 (FSI-93-TN38)

13-93 J. Partinen, N. Saluja and J. K. Kirtley, Jr., Experimental and Computational Investigation of Rotary Electromagnetic Stirring in a Woods Metal System, Dept. of Math, Science and Engr. and Dept. of Electrical Engr. and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139-4307

12-93 J. Partinen, N. Saluja and J. K. Kirtley, Jr., Modeling of Surface Deformation in an Electromagnetically Stirred Metallic Melt, Dept. of Math, Science, and Engr. and Dept. of Electrical Engr. and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139-4307

10-93 C. Philippe, Summary Report on Test Calculations with FLOW-3D/CAST93, (coupled-rigid-body dynamics model), ESTEC, Noordwijk, The Netherlands, September 17, 1993

5-93 J. M. Sicilian, J. L. Ditter and C. L. Bronisz, FLOW-3D Analyses of CFD Triathlon Benchmark, Flow Science report, presented at the ASME Fluids Engineering Conference, Washington DC, June 20-24, 1993

4-93 T. Wiik, Ventilation of the Attic due to Wind Loads on Low-Rise Buildings, paper for 3rd Symposium of Building Physics in Nordic Countries, Narvik Institute of Technology, Narvik, Norway, summer 1993

3-93 E. W. M. Hansen, Modelling and Simulation of Separation Effects and Fluid Flow Behaviour in Process-Units, SIMS’93 – 35th Simulation Conference, Kongsberg, Norway, June 9-11, 1993

2-93 M. A. Briones, R. S. Brodsky and J. J. Chalmers, Computer Simulation of the Rupture of a Gas Bubble at a Gas-Liquid Interface and its Implications in Animal Cell Damage, Dept. Chemical Engineering, Ohio State University, Manuscript No. RB68, April 1993

11-92 G. Trapaga, E. F. Matthys, J. J. Valencia and J. Szekely, Fluid Flow, Heat Transfer, and Solidification of Molten Metal Droplets Impinging on Substrates: Comparison of Numerical and Experimental Results, Metallurgical Transactions B, Vol. 23B, pp. 701-718, December 1992

10-92 J. B. Dalin, J. M. Le Guilly, P. Le Roy and E. Maas, Numerical Simulations Applied to the Production of Automotive Foundry Components, Numerical Methods in Industrial Forming Processes, Wood & Zienkiewicz (eds), Balkema, Rotterdam, 1992

5-92 C. W. Hirt, Volume-Fraction Techniques: Powerful Tools for Flow Modeling, Flow Science report (FSI-92-00-02), presented at the Computational Wind Engineering Conference, University of Tokyo, August 1992

3-92 C. L. Bronisz and C.W. Hirt, Lubricant Flow in a Rotary Lip Seal, Flow Science Technical Note #33, February 1992 (FSI-92-TN33)

16-91 A. Nielsen, SNOW-SIM – Computer Model for Simulation of Wind and Snow Loads on Buildings and Structures, Building Science, Narvik Institute of Technology, Narvik, Norway, (not dated)

15-91 E. W. M. Hansen, H. Heitmann, B. Laska, A. Ellingsen, O. Ostby, T. B. Morrow and F. T. Dodge, Fluid Flow Modelling of Gravity Separators, SINTEF, Norway and Southwest Research Institute, Texas, Elsevier Science Publishers, 1991

14-91 E. W. M. Hansen, H. Heitmann, B. Laska and M. Loes, Numerical Simulation of Fluid Flow Behaviour Inside, and Redesign of a Field Separator, SINTEF, Norway and STATOIL, Norway (not dated)

13-91 G. Trapaga and J. Szekely, Mathematical Modeling of the Isothermal Impingement of Liquid Droplets in Spraying Processes, Metallurgical Transactions, Vol. 22B, pp. 901-914, December 1991

11-91 N. Saluja and J. Szekely, Velocity Fields and Free Surface Phenomena in an Inductively Stirred Mercury Pool, European Journal of Mechanics, B/Fluids, Vol. 10, No. 5, pp. 563-572, Oct. 1991

4-90 J. M. Sicilian, A Note on Implementing Specified Velocities and Momentum Sources, Flow Science report, September 1990 (FSI-90-00-5)

13-90 P. Jonsson, N. Saluja, O. J. Ilegbusi, and J. Szekely, Fluid Flow Phenomena in the Filling of Cylindrical Molds Using Newtonian (Turbulent) and Non-Newtonian (Power Law) Fluids, submitted to Trans. of the American Foundrymen’s Soc., June 1990

12-90 N. Saluja, O. J. Ilegbusi, and J. Szekely, On the Computation of the Velocity Fields and the Dynamic Free Surface Generated in a Liquid Metal Column by a Rotating Magnetic Field, submitted to J. Fluid Mech., July 1990

7-90 C. L. Bronisz and C. W. Hirt, Modeling Unsaturated Flow in Porous Media: A FLOW-3D Extension, Flow Science report, July 1990 (FSI-90-48-2)

5-90 C. L. Bronisz and C. W. Hirt, Hydrodynamic Ram Simulations Using FLOW-3D, Flow Science report, May 1990 (FSI-90-49-1)

3-90 C. W. Hirt, Turbojet Plume Flow Analysis, Flow Science report, February 1990 (FSI-90-45-1)

5-89 K. S. Eckhoff and E. W. M. Hansen, Mathematical Modelling and Numerical Investigation of Separation in Two-Phase Rotating Flow, SINTEF-Foundation for Scientific and Industrial Research at the Norwegian Institute of Technology, Trondheim, Norway, Report No. OR 22 1907.00.01.89, 29 April 1989

2-89 J. M. Sicilian and J. R. Tegart, Comparisons of FLOW-3D Calculations with Very Large Amplitude Slosh Data, presented at the Symposium on Computational Experiments, PVP ASME Conference, Honolulu, HI, July 22-27, 1989

2-88 J. M. Sicilian and C. W. Hirt, AFT Field Joint: CFD Analysis Using the FLOW-3D Program, in Redesigned Solid Rocket Motor Circumferential Flow Technical Interchange Meeting Final Report, NASA-TWR-17788, February 1988

14-87 C. J. Freitas, S. T. Green, and T. B. Morrow, Fluid Dynamics Associated with Ductile Pipeline Fracture, Southwest Research Institute report presented at ASME Winter Annual Meeting, Boston, MA, December 1987

13-87 J. Sicilian, The FLOW-3D Model for Thermal Conduction in Solids, Flow Science report, Dec. 1987 (FSI-87-00-4)

7-87 C.W. Hirt, Vectored Nozzle Flow with Turbulence Modeling, Flow Science report, Sept. 1987 (FSI-87-29-1)

4-87 J.M. Sicilian, C.W. Hirt, and R. P. Harper, FLOW-3D: Computational Modeling Power for Scientists and Engineers, Flow Science report, 1987 (FSI-87-00-1)

3-86 J. M. Sicilian, Natural-Convection Heat-Transfer Analysis, Flow Science Technical Note #4, June 1986 (FSI-86-00-TN4)

2-86 J. Navickas and C. R. Cross, Air Circulation Characteristics and Convective Losses in a 5-MW Molten Salt Cavity Solar Receiver, ASME 8th Annual Conference on Solar Engineering, Anaheim, California, April 13-16, 1986

5-85 C. W. Hirt and R. P. Harper, Calculations of Vent Clearing in a Chemical Process Tank, Flow Science report, December 1985 (FSI-85-28-1)

2-84 Applications of SOLA-3D/FSI to Fluid Slosh, Flow Science report, May 1984

Metal Casting Bibliography

다음은 금속 주조 참고 문헌의 기술 문서 모음입니다. 
이 모든 논문은 FLOW-3D  CAST  결과를 포함하고 있습니다. FLOW-3D  CAST 를 사용하여 금속 주조 산업의 어플리케이션을 성공적으로 시뮬레이션  하는 방법에 대해 자세히 알아보십시오.

2023년 3월 10일 Update

45-23   Daniel Martinez, Philip King, Santosh Reddy Sama, Jay Sim, Hakan Toykoc, Guha Manogharan, Effect of freezing range on reducing casting defects through 3D sand-printed mold designs, The International Journal of Advanced Manufacturing Technology, 2023. doi.org/10.1007/s00170-023-11112-x

38-23   Emanuele Pagone, Christopher Jones, John Forde, William Shaw, Mark Jolly, Konstantinos Salonitis, Defect minimization in vacuum-assisted plaster mould investment casting through simulation of high-value aluminium alloy components, TMS 2023: Light Metals, pp. 1078-1086, 2023.

33-23   Philip King, Guha Manogharan, Novel experimental method for metal flow analysis using open molds for sand casting, International Journal of Metalcasting, 2023. doi.org/10.1007/s40962-023-00966-2

32-23   Sujeet Kumar Gautam, Himadri Roy, Aditya Kumar Lohar, Sudip Kumar Samanta, Studies on mold filling behavior of Al–10.5Si–1.7Cu Al alloy during rheo pressure die casting system, International Journal of Metalcasting, 2023. doi.org/10.1007/s40962-023-00958-2

31-23   Anand Kumbhare, Prasenjit Biswas, Anil Bisen, Chandan Choudary, Investigation of effect of the rheological parameters on the flow behavior of ADC12 Al alloy in rheo-pressure die casting, International Journal of Metalcasting, 2023. doi.org/10.1007/s40962-023-00962-6

24-23   Natalia Raźny, Anna Dmitruk, Maria Serdechnova, Carsten Blawert, Joanna Ludwiczak, Krzysztof Naplocha, The performance of thermally conductive tree-like cast aluminum structures in PCM-based storage units, International Communications in Heat and Mass Transfer, 142; 106606, 2023. doi.org/10.1016/j.icheatmasstransfer.2022.106606

172-22 J. Yokesh Kumar, S. Gopi, K.S. Amirthagadeswaran, Redesigning and numerical simulation of gating system to reduce cold shut defect in submersible pump part castings, Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 2022. doi.org/10.1177/0954408922114218

125-22   Maximilian Erber, Tobias Rosnitschek, Christoph Hartmann, Bettina Alber-Laukant, Stephan Tremmel, Wolfram Volk, Geometry-based assurance of directional solidification for complex topology-optimized castings using the medial axis transform, Computer-Aided Design, 152; 103394, 2022. doi.org/10.1016/j.cad.2022.103394

74-22    Vasilios Fourlakidis, Ilia Belov, Attila Diószeg, Experimental model of the pearlite interlamellar spacing in lamellar graphite iron, Tecnologia em Metalurgia, Materiais e Mineração, 19; e2634, 2022. doi.org/10.4322/2176-1523.20222634

71-22   M. G. Mahmoud, Amr Abdelghany, Serag Salem, Numerical simulation of door lock plates castings produced by high pressure die casting process, International Journal of Metalcasting, 2022. doi.org/10.1007/s40962-022-00797-7

70-22   Andreas Schilling, Daniel Schmidt, Jakob Glück, Niklas Schwenke, Husam Sharabi, Martin Fehlbier, About the impact on gravity cast salt cores in high pressure die casting and rheocasting, Simulation Modelling Practice and Theory, 119; 102585, 2022. doi.org/10.1016/j.simpat.2022.102585

52-22   Manthan Dhisale, Jitesh Vasavada, Asim Tewari, An approach to optimize cooling channel parameters of low pressure die casting process for reducing shrinkage porosity in aluminium alloy wheels, Materials Today: Proceedings, in print, 2022. doi.org/10.1016/j.matpr.2022.03.478

44-22   Zihan Lang, Feng Wang, Wei Wang, Zhi Wang, Le Zhou, Pingli Mao, Zheng Liu, Numerical simulation and experimental study on semi-solid forming process of 319s aluminum alloy test bar, International Journal of Metalcasting, 2022. doi.org/10.1007/s40962-022-00788-8

32-22   Elisa Fracchia, Federico Simone Gobber, Claudio Mus, Raul Pirovino, Mario Russo, The local squeeze technology for challenging aluminium HPDC automotive components, Light Metals, pp. 772-778, 2022. doi.org/10.1007/978-3-030-92529-1_102

141-21   O. Ayer, O. Kaya, Mould design optimisation by FEM, Journal of Physics: Conference Series, 2130; 012021, 2021. doi.org/10.1088/1742-6596/2130/1/012021

117-21   I. Rajkumar, N. Rajini, T. Ram Prabhu, Sikiru O. Ismail, Suchart Siengchin, Faruq Mohammad, Hamad A. Al-Lohedan , Applicability of angular orientations of gating designs to quality of sand casting components using two-cavity mould set-up, Transactions of the Indian Institute of Metals, 2021. doi.org/10.1007/s12666-021-02434-z

106-21   M. Ahmed, E. Riedel, M. Kovalko, A. Volochko, R. Bähr, A. Nofal, Ultrafine ductile and austempered ductile irons by solidification in ultrasonic field, International Journal of Metalcasting, 2021. doi.org/10.1007/s40962-021-00683-8

97-21   J. Glueck, A. Schilling, N. Schwenke, A. Fros, M.Fehlbier, Efficiency and agility of a liquid CO2 cooling system for molten metal systems, Case Studies in Thermal Engineering, 28; 101485, 2021. doi.org/10.1016/j.csite.2021.101485

82-21   Giulia Scampone, Raul Pirovano, Stefano Mascetti, Giulio Timelli, Experimental and numerical investigations of oxide-related defects in Al alloy gravity die castings, The International Journal of Advanced Manufacturing Technology, 117; pp. 1765-1780, 2021. doi.org/10.1007/s00170-021-07680-5

74-21   Shuyang Ren, Feng Wang, Jingying Sun, Zheng Liu, Pingli Mao, Gating system design based on numerical simulation and production experiment verification of aluminum alloy bracket fabricated by semi-solid rheo-die casting process, International Journal of Metalcasting, 2021. doi.org/10.1007/s40962-021-00648-x

69-21   Ozen Gursoy, Murat Colak, Kazim Tur, Derya Dispinar, Characterization of properties of Vanadium, Boron and Strontium addition on HPDC of A360 alloy, Materials Chemistry and Physics, 271; 124931, 2021. doi.org/10.1016/j.matchemphys.2021.124931

54-21   K. Munpakdee, P. Ninpetch, S. Otarawanna, R. Canyook, P. Kowitwarangkul, Effect of feed sprue size on porosity defects in Platinum 950 centrifugal investment casting via numerical modelling, IOP Conference Series: Materials Science and Engineering, 11th TSME-International Conference on Mechanical Engineering, Ubon Ratchathani, Thailand, December 1-4, 2020, 1137; 012021, 2021. doi.org/10.1088/1757-899X/1137/1/012021/

44-21   Yunxiang Zhang, Haidong Zhao, Fei Liu, Microstructure characteristics and mechanical properties improvement of gravity cast Al-7Si-0.4Mg alloys with Zr additions, Materials Characterization, 176; 111117, 2021. doi.org/10.1016/j.matchar.2021.111117

05-21   Heqian Song, Lunyong Zhang, Fuyang Cao, Xu Gu, Jianfei Sun, Oxide bifilm defects in aluminum alloy castings, Materials Letters, 285; 129089, 2021. doi.org/10.1016/j.matlet.2020.129089

127-20   Eric Riedel, Niklas Bergedieck, Stefan Scharf, CFD simulation based investigation of cavitation cynamics during high intensity ultrasonic treatment of A356, Metals, 10.11; 1529, 2020. doi.org/10.3390/met10111529

86-20       Malte Leonhard, Matthias Todte, Jörg Schäfer, Realistic simulation of the combustion of exothermic feeders, Modern Casting, August 2020; pp. 35-40, 2020. (See also 58-19)

52-20       Mingfan Qi, Yonglin Kang, Jingyuan Li, Zhumabieke Wulabieke, Yuzhao Xu, Yangde Li, Aisen Liu, Junchen Chen, Microstructures refinement and mechanical properties enhancement of aluminum and magnesium alloys by combining distributary-confluence channel process for semisolid slurry preparation with high pressure die-casting, Journal of Materials Processing Technology, 285; 116800, 2020. doi.org/10.1016/j.jmatprotec.2020.116800

46-20       Yasushi Iwata, Shuxin Dong, Yoshio Sugiyama, Jun Yaokawa, Melt permeability changes during solidification of aluminum alloys and application to feeding simulation for die castings, Materials Transactions, 61.7; pp. 1381-1386, 2020. doi.org/10.2320/matertrans.F-M2020822

45-20       Daniel Bernal, Xabier Chamorro, Iñaki Hurtado, Iñaki Madariaga, Effect of boron content and cooling rate on the microstructure and boride formation of β-solidifying γ-TiAl TNM alloy, Metals, 10.5; 698, 2020. doi.org/10.3390/met10050698

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: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: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: 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: 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: 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: 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: 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: 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: 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: 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: 10.1016/j.jmatprotec.2018.11.016

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: 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: 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: 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: 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: 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: 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: 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: 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: 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: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, http://hdl.handle.net/1822/40132, 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: 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 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: 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: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: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: 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: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, 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: 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), http://dx.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 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: 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 Form; Europe 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)