Figure 4.24 - Model with virtual valves in the extremities of the geometries to simulate the permeability of the mold promoting a more uniformed filling

Dissertação de Mestrado
Ciclo de Estudos Integrados Conducentes ao
Grau de Mestre em Engenharia Mecânica
Trabalho efectuado sob a orientação do
Doutor Hélder de Jesus Fernades Puga
Professor Doutor José Joaquim Carneiro Barbosa


논문의 일부로 튜터 선택 가능성과 해결해야 할 주제가 설정되는 매개변수를 염두에 두고 개발 주제 ‘Flow- 3D ®에 의한 저압 충전 시스템 최적화’가 선택되었습니다. 이를 위해서는 달성해야 할 목표와 이를 달성하기 위한 방법을 정의하는 것이 필요했습니다.

충전 시스템을 시뮬레이션하고 검증할 수 있는 광범위한 소프트웨어에도 불구하고 Flow-3D®는 시장에서 최고의 도구 중 하나로 표시되어 전체 충전 프로세스 및 행동 표현과 관련하여 탁월한 정확도로 시뮬레이션하는 능력을 입증했습니다.

이를 위해 관련 프로세스를 더 잘 이해하고 충진 시스템 시뮬레이션을 위한 탐색적 기반 역할을 하기 위해 이 도구를 탐색하는 것이 중요합니다. 지연 및 재료 낭비에 반영되는 실제적인 측면에서 충전 장치의 치수를 완벽하게 만드는 비용 및 시간 낭비. 이러한 방식으로 저압 주조 공정에서 충진 시스템을 설계하고 물리적 모델을 탐색하여 특성화하는 방법론을 검증하기 위한 것입니다.

이를 위해 다음 주요 단계를 고려하십시오.

시뮬레이션 소프트웨어 Flow 3D® 탐색;
충전 시스템 모델링;
모델의 매개변수를 탐색하여 모델링된 시스템의 시뮬레이션, 검증 및 최적화.

따라서 연구 중인 압력 곡선과 주조 분석에서 가장 관련성이 높은 정보의 최종 마이닝을 검증하기 위한 것입니다.

사용된 압력 곡선은 수집된 문헌과 이전에 수행된 실제 작업을 통해 얻었습니다. 결과를 통해 3단계 압력 곡선이 층류 충진 체계의 의도된 목적과 관련 속도가 0.5 𝑚/𝑠를 초과하지 않는다는 결론을 내릴 수 있었습니다.

충전 수준이 2인 압력 곡선은 0.5 𝑚/𝑠 이상의 속도로 영역을 채우는 더 난류 시스템을 갖습니다. 열전달 매개변수는 이전에 얻은 값이 주물에 대한 소산 거동을 확증하지 않았기 때문에 연구되었습니다.

이러한 방식으로 주조 공정에 더 부합하는 새로운 가치를 얻었습니다. 달성된 결과는 유사한 것으로 나타난 NovaFlow & Solid®에 의해 생성된 결과와 비교되어 시뮬레이션에서 설정된 매개변수를 검증했습니다. Flow 3D®는 주조 부품 시뮬레이션을 위한 강력한 도구로 입증되었습니다.

As part of the dissertation and bearing in mind the parameters in which the possibility of a choice of tutor and the subject to be addressed is established, the subject for development ’Optimization of filling systems for low pressure by Flow 3D ®’ was chosen. For this it was necessary to define the objectives to achieve and the methods to attain them. Despite the wide range of software able to simulate and validate filling systems, Flow 3D® has been shown as one of the best tools in the market, demonstrating its ability to simulate with distinctive accuracy with respect to the entire process of filling and the behavioral representation of the fluid obtained. To this end, it is important to explore this tool for a better understanding of the processes involved and to serve as an exploratory basis for the simulation of filling systems, simulation being one of the great strengths of the current industry due to the need to reduce costs and time waste, in practical terms, that lead to the perfecting of the dimensioning of filling devices, which are reflected in delays and wasted material. In this way it is intended to validate the methodology to design a filling system in lowpressure casting process, exploring their physical models and thus allowing for its characterization. For this, consider the following main phases: The exploration of the simulation software Flow 3D®; modeling of filling systems; simulation, validation and optimization of systems modeled by exploring the parameters of the models. Therefore, it is intended to validate the pressure curves under study and the eventual mining of the most relevant information in a casting analysis. The pressure curves that were used were obtained through the gathered literature and the practical work previously performed. Through the results it was possible to conclude that the pressure curve with 3 levels meets the intended purpose of a laminar filling regime and associated speeds never exceeding 0.5 𝑚/𝑠. The pressure curve with 2 filling levels has a more turbulent system, having filling areas with velocities above 0.5 𝑚/𝑠. The heat transfer parameter was studied due to the values previously obtained didn’t corroborate the behavior of dissipation regarding to the casting. In this way, new values, more in tune with the casting process, were obtained. The achieved results were compared with those generated by NovaFlow & Solid®, which were shown to be similar, validating the parameters established in the simulations. Flow 3D® was proven a powerful tool for the simulation of casting parts.


저압, Flow 3D®, 시뮬레이션, 파운드리, 압력-시간 관계,Low Pressure, Flow 3D®, Simulation, Foundry, Pressure-time relation

Figure 4.24 - Model with virtual valves in the extremities of the geometries to simulate the permeability of the mold promoting a more uniformed filling
Figure 4.24 – Model with virtual valves in the extremities of the geometries to simulate the permeability of the mold promoting a more uniformed filling
Figure 4.39 - Values of temperature contours using full energy heat transfer parameter for simula
Figure 4.39 – Values of temperature contours using full energy heat transfer parameter for simula
Figure 4.40 – Comparison between software simulations (a) Flow 3D® simulation,
(b) NovaFlow & Solid® simulation
Figure 4.40 – Comparison between software simulations (a) Flow 3D® simulation, (b) NovaFlow & Solid® simulation


[1] E. Stanley and D. B. Sc, “Fluid Flow Aspects of Solidification Modelling : Simulation
of Low Pressure Die Casting .”
[2] Y. Sahin, “Computer aided foundry die-design,” Metallography, vol. 24, no. 8, pp.
671–679, 2003.
[3] F. Bonollo, J. Urban, B. Bonatto, and M. Botter, “Gravity and low pressure die casting
of aluminium alloys : a technical and economical benchmark,” La Metall. Ital., vol. 97,
no. 6, pp. 23–32, 2005.
[4] P. a and R. R, “Study of the effect of process parameters on the production of a nonsimmetric low pressure die casting part,” La Metall. Ital., pp. 57–63, 2009.
[5] “Fundição em baixa pressão | Aluinfo.” [Online]. Available: [Accessed: 18-
[6] “Low Pressure Sand Casting by Wolverine Bronze.” [Online]. Available: [Accessed: 18-Sep2015].
[7] A. Reikher, “Numerical Analysis of Die-Casting Process in Thin Cavities Using
Lubrication Approximation,” no. December, 2012.
[8] P. Fu, A. a. Luo, H. Jiang, L. Peng, Y. Yu, C. Zhai, and A. K. Sachdev, “Low-pressure
die casting of magnesium alloy AM50: Response to process parameters,” J. Mater.
Process. Technol., vol. 205, no. 1–3, pp. 224–234, 2008.
[9] X. Li, Q. Hao, W. Jie, and Y. Zhou, “Development of pressure control system in
counter gravity casting for large thin-walled A357 aluminum alloy components,”
Trans. Nonferrous Met. Soc. China, vol. 18, no. 4, pp. 847–851, 2008.
[10] J. a. Hines, “Determination of interfacial heat-transfer boundary conditions in an
aluminum low-pressure permanent mold test casting,” Metall. Mater. Trans. B, vol. 35,
no. 2, pp. 299–311, 2004.
[11] A. Lima, A. Freitas, and P. Magalhães, “Processos de vazamento em moldações
permanentes,” pp. 40–49, 2003.
[12] Y. B. Choi, K. Matsugi, G. Sasaki, K. Arita, and O. Yanagisawa, “Analysis of
Manufacturing Processes for Metal Fiber Reinforced Aluminum Alloy Composite
Fabricated by Low-Pressure Casting,” Mater. Trans., vol. 47, no. 4, pp. 1227–1231,
[13] G. Mi, X. Liu, K. Wang, and H. Fu, “Numerical simulation of low pressure die-casting
aluminum wheel,” China Foundry, vol. 6, no. 1, pp. 48–52, 2009.
[14] J. Kuo, F. Hsu, and W. Hwang, “ADVANCED Development of an interactive
simulation system for the determination of the pressure ± time relationship during the
® lling in a low pressure casting process,” vol. 2, pp. 131–145, 2001.
[15] S.-G. Liu, F.-Y. Cao, X.-Y. Zhao, Y.-D. Jia, Z.-L. Ning, and J.-F. Sun, “Characteristics
of mold filling and entrainment of oxide film in low pressure casting of A356 alloy,”
Mater. Sci. Eng. A, vol. 626, pp. 159–164, 2015.
[16] “Casting Training Class – Lecture 10 – Solidification and Shrinkage-Casting.” FLOW3D®.
[17] “UAB Casting Engineering Laboratory.” [Online]. Available:
file:///C:/Users/Jos%C3%A9 Belo/Desktop/Artigo_Software/UAB Casting
Engineering Laboratory.htm. [Accessed: 09-Nov-2015].
[18] A. Louvo, “Casting Simulation as a Tool in Concurrent Engineering,” pp. 1–12, 1997.
[19] T. R. Vijayaram and P. Piccardo, “Computers in Foundries,” vol. 30, 2012.
[20] M. Sadaiah, D. R. Yadav, P. V. Mohanram, and P. Radhakrishnan, “A generative
computer-aided process planning system for prismatic components,” Int. J. Adv.
Manuf. Technol., vol. 20, no. 10, pp. 709–719, 2002.
[21] Ministry_of_Planning, “Digital Data,” vol. 67, pp. 1–6, 2004.
[22] S. Shamasundar, D. Ramachandran, and N. S. Shrinivasan, “COMPUTER
[23] J. M. Siqueira and G. Motors, “Simulation applied to Aluminum High Pressure Die
Casting,” pp. 1–5, 1998.
[24] C. Fluid, COMPUTATIONAL FLUID DYNAMICS. Abdulnaser Sayma & Ventus
Publishing ApS, 2009.
[25] C. a. Felippa, “1 – Overview,” Adv. Finite Elem. Methods, pp. 1–9.
[26] a. Meena and M. El Mansori, “Correlative thermal methodology for castability
simulation of ductile iron in ADI production,” J. Mater. Process. Technol., vol. 212,
no. 11, pp. 2484–2495, 2012.
[27] T. R. Vijayaram, S. Sulaiman, a. M. S. Hamouda, and M. H. M. Ahmad, “Numerical
simulation of casting solidification in permanent metallic molds,” J. Mater. Process.
Technol., vol. 178, pp. 29–33, 2006.
[28] “General CFD FAQ — CFD-Wiki, the free CFD reference.” [Online]. Available: [Accessed: 10-Nov-2015].
[29] “FEM | FEA | CFD.” [Online]. Available: [Accessed:
[30] “Fundição; revista da Associação portuguesa de fundição,” Fundição, vol. N
[31] “Casting Training Class – Lecture 1 – Introduction_to_FLOW-3D – Casting.” FLOW3D®.
[32] F. Science, “FLOW-3D Cast Documentation,” no. 3.5, p. 80, 2012.
[33] “Casting Training Class – Lecture 4 – Geometry Building – General.” FLOW-3D®.
[34] F. Science, “FLOW-3D v11.0.3 User Manual,” pp. 1–132, 2015.
[35] “Casting Training Class – Lecture 5 Meshing Concept – General.” FLOW-3D®.
[36] “Casting Training Class – Lecture 6 – Boundary_Conditions – Casting.” FLOW-3D®.
[37] “Casting Training Class – Lecture 9 – Physical Models-castings.” FLOW-3D®.
[38] P. A. D. Jácome, M. C. Landim, A. Garcia, A. F. Furtado, and I. L. Ferreira, “The
application of computational thermodynamics and a numerical model for the
determination of surface tension and Gibbs–Thomson coefficient of aluminum based
alloys,” Thermochim. Acta, vol. 523, no. 1–2, pp. 142–149, 2011.
[39] J. P. Anson, R. A. L. Drew, and J. E. Gruzleski, “The surface tension of molten
aluminum and Al-Si-Mg alloy under vacuum and hydrogen atmospheres,” Metall.
Mater. Trans. B Process Metall. Mater. Process. Sci., vol. 30, no. 6, pp. XVI–1032,