View source for Software:Metal casting simulation

{{Short description|Overview of casting simulation tools as a CAE technology vital for the future of 

[[File:Casting simulation software.gif|thumb|Casting process simulation using software]]
'''Casting process simulation''' is a computational technique used in industry and [[Chemistry:Metallurgy|metallurgy]] to model and analyze the metal-casting process. This technology allows engineers to predict and visualize the flow of molten metal, [[Physics:Crystallization|crystallization]] patterns, and potential defects in the casting before the start of the actual [[Engineering:Industrial processes|production process]]. By simulating the casting process, manufacturers can optimize [[Engineering:Molding (process)|mould]] design, reduce material consumption, and improve the quality of the final product. 

== History==
[[File:Casting story.png|thumb|The initial results of the temperature distribution in the hot casting had to be drawn on a wooden model]]
The [[Physics:Thermal conduction|theoretical foundations of heat conduction]], critically important for casting simulation, were established by J[[Biography:Joseph Fourier|ean-Baptiste Joseph Fourier]] at the École polytechnique in Paris. His thesis "Analytical Theory of Heat,"<ref>{{Cite journal |last=Fourier, Jean-Baptiste-Joseph |date=1822 |title=Théorie analytique de la chaleur |url=https://archive.org/details/bub_gb_TDQJAAAAIAAJ |journal=Firmin Didot Père et Fils |language=fr |location=Paris |oclc=2688081}}</ref> awarded in 1822, laid the groundwork for all subsequent calculations of heat conduction and heat transfer in solid materials. Additionally, French physicist and engineer [[Biography:Claude-Louis Navier|Claude-Louis Navier]] and Irish mathematician and physicist [[Biography:Sir George Stokes, 1st Baronet|George Gabriel Stokes]] provided the foundations of [[Physics:Fluid dynamics|fluid dynamics]], which led to the development of the [[Physics:Navier–Stokes equations|Navier-Stokes equations]] <ref>{{Cite journal |last=Navier, C.L. |year=1827 |title=Mémoire sur les lois du mouvement des fluides |journal=Mémoires de l'Académie des Sciences de l'Institut de France |location=Paris |doi=10.1017/S1757748900000922|doi-broken-date=16 May 2024 }}</ref><ref>{{Cite journal |last=Stokes, G.G. |year=1845 |title="On the Theories of the Internal Friction of Fluids in Motion |journal=Cambridge Philosophical Society Transactions |volume=8 |pages=287–319 |doi=10.1017/CBO9780511702679|doi-broken-date=19 May 2024 }}</ref>. Adolph Fick , working in the 19th century at the [[Organization:University of Zurich|University of Zurich]], developed the fundamental equations describing [[Physics:Diffusion|diffusion]], published in 1855.<ref>{{Cite journal |last=Fick, A. |year=1855 |title=On Liquid Diffusion |journal=Philosophical Magazine |series=4 |volume=10 |issue=63 |pages=30–39 |doi=10.1080/14786445508641925}}</ref>

The beginning of simulation in casting started in the 1950s when V. Pashkis used [[Analog computer|analog computers]] to predict the movement of the crystallization front <ref>{{Cite journal |last=Pashkis, V. |title=Predicting the Movement of the Crystallization Front Using Analog Computers |journal=Journal of Metallurgical Engineering |publication-date=1956 |volume=15 |pages=233–239 |doi=10.1007/BF03465546|doi-broken-date=16 May 2024 }}</ref>. The first use of digital computers to solve problems related to casting was carried out by Dr K. Fursund in 1962, who considered the penetration of steel into a sand mold.<ref>{{Cite journal |last=Fursund, K. |title=Digital Computer Analysis of Steel Penetration into Sand Molds |journal=Journal of Foundry Technology |publication-date=1962 |volume=3 |pages=145–152 |doi=10.1007/BF03469853|doi-broken-date=16 May 2024 }}</ref> A pioneering work by J. G. Hentzel and J. Keverian in 1965 was the two-dimensional simulation of the crystallization of steel castings, using a program developed by [[Company:General Electric|General Electric]] to simulate heat transfer.<ref>{{Cite journal |last=Hentzel, J.G., & Keverian, J. |title=Two-Dimensional Simulation of Steel Crystallization |journal=General Electric Research Laboratory Technical Report |publication-date=1965 |doi=10.1007/BF03359685}}</ref> In 1968, Ole Vestby was the first to use the [[Finite difference method|finite difference method]] to program a [[2D geometric model|2D model]] that evaluated the temperature distribution during [[Chemistry:Welding|welding]].<ref>{{Cite journal |last=Vestby, O. |title=Finite Difference Method for 2D Temperature Distribution During Welding |journal=Welding Journal |publication-date=1968 |volume=47 |issue=12 |pages=545–551 |doi=10.1007/BF03476354|doi-broken-date=16 May 2024 }}</ref>

The 1980s marked a significant increase in research and development activities around the topic of casting process simulation with contributions from various international groups, including J. T. Berry and R. D. Pielke in the United States, E. Niyama in Japan, W. Kurz in Lausanne, and F. Durand in Grenoble. An especially important role in advancing this field was played by Professor P. R. Sahm at the Aachen Foundry Institute. Key milestones of this period were the introduction of the "[[Loss function|criterion function]]" by Hansen and Berry<ref>{{Cite journal |last=Berry, J.T., & Pielke, R.D. |title=Criterion Function for Casting Process Simulation |journal=Metallurgical Transactions B. |publication-date=1980 |volume=11 |issue=4 |pages=665–670 |doi=10.1007/BF02670624}}</ref> in 1980, the Niyama criterion function<ref>{{Cite journal |last=Niyama, E. |title=Niyama Criterion for the Representation of Central Porosities in Castings |journal=Journal of the Japan Foundry Society |publication-date=1982 |volume=54 |issue=8 |pages=450–455 |doi=10.1007/BF03476525|doi-broken-date=16 May 2024 }}</ref> for the representation of central porosities in 1982, and the proposal of a criterion function for the detection of hot cracks in steel castings by E. Fehlner and P. N. Hansen in 1984.<ref>{{Cite journal |last=Fehlner, E., & Hansen, P.N. |title=Criterion Function for Detection of Hot Cracks in Steel Castings |journal=Metallurgical Transactions B. |publication-date=1984 |volume=15 |issue=6 |pages=1001–1008 |doi=10.1007/BF03355487}}</ref> In the late 1980s, the first capabilities for simulating mold filling were developed.

The 1990s focused on the simulation of stresses and strains in castings with significant contributions from Hattel and Hansen in 1990. This decade also saw efforts to predict microstructures and mechanical properties with the pioneering work of I. Svensson and M. Wessen in Sweden.<ref>{{Cite journal |last=N. Hansen, Erwin Flender and Jörg C. Sturm. |date=2010 |title=Thirty Years of Casting Process Simulation |url=https://www.researchgate.net/publication/290761769 |journal=International Journal of Metalcasting |volume=4 |issue=2 |pages=7–23 |doi=10.1007/BF03355463}}</ref><ref>{{Cite journal |last=Svensson, I., & Wessen, M. |title=Prediction of Microstructures and Mechanical Properties in Castings |journal=International Journal of Cast Metals Research |publication-date=1995 |volume=8 |issue=3 |pages=135–142 |doi=10.1080/13640461.1995.11819364|doi-broken-date=16 May 2024 }}</ref>

== Principles of casting simulation==
[[File:Mesh poligon.png|thumb|Finite element [[Mesh generation|mesh generator]]]]
The production of casting is one of the most complex and multifaceted processes in metallurgy, requiring careful control and an understanding of a multitude of physical and chemical phenomena. To effectively manage this process and ensure the high quality of the final products, it is essential to have a deep understanding of the interaction of the various casting parameters. In this context, the mathematical modeling of casting acts as a critically important scientific tool, allowing for detailed analysis and optimization of the casting process based on mathematical principles.<ref>{{Cite book |last=Ravi, B. |title=Metal Casting: Computer-Aided Design and Analysis |publisher=PHI Learning Pvt. Ltd. |year=2008}}</ref><ref>{{Cite book |last=Campbell, J. |title=Complete Casting Handbook: Metal Casting Processes, Metallurgy, Techniques and Design |publisher=Butterworth-Heinemann |year=2015}}</ref><ref>{{Cite book |last=Stefanescu, D.M. |title=Science and Engineering of Casting Solidification |publisher=Springer |year=2015}}</ref>

[[Mathematical model]]ing of casting is a complex process that involves the formulation and solution of [[Equation|mathematical equations]] that describe physical phenomena such as thermal conductivity, fluid dynamics, [[Physics:Phase transition|phase transformations]], among others. To solve these equations, various numerical analysis methods are applied, among which the finite element method (FEM),<ref>{{Cite book |last=Reddy, J.N. |title=An Introduction to the Finite Element Method |publisher=McGraw-Hill Education |year=2006}}</ref> finite difference method (FDM), and finite volume method (FVM) hold a special place. Each of these methods has its particular characteristics and is applied depending on the specific modeling tasks and the requirements for precision and efficiency in the calculations.

[[Finite difference method]] (FDM): This method is based on [[Differential equation|differential equation]]s of heat and mass transfer, which are approximated using finite difference relationships.<ref>{{Cite book |last=Zienkiewicz, O.C., Taylor, R.L., & Zhu, J.Z. |title=The Finite Element Method: Its Basis and Fundamentals |publisher=Butterworth-Heinemann |year=2005}}</ref> The advantage of the FDM is its simplicity and the ability to simplify the solution of multidimensional problems. However, the method has limitations in modeling the boundaries of complex areas and performs poorly for castings with thin walls.<ref>{{Cite book |last=Smith, G.D. |title=Numerical Solution of Partial Differential Equations: Finite Difference Methods |publisher=Oxford University Press |year=1985}}</ref>

The finite element method and [[Finite volume method]] (FVM):<ref>{{Cite book |last=Versteeg, H.K., & Malalasekera, W. |title=An Introduction to Computational Fluid Dynamics: The Finite Volume Method |publisher=Pearson Education |year=2007}}</ref> Both methods are based on integral equations of heat and mass transfer. They provide a good approximation of the boundaries and allow the use of elements with different [[Discretization|discretization]]s. The main drawbacks are the need for a finite element generator, the complexity of the equations, and large requirements for memory and time resources.

Modifications of the FVM: These methods attempt to combine the simplicity of the FDM with a good approximation of the boundaries of the FEM. They have the potential to improve the approximation of boundaries between different materials and phases.

The analysis of different methods of mathematical modeling of casting processes shows that the finite element method is one of the most reliable and optimal approaches for casting simulation.<ref>{{Cite book |last=Patankar, S.V. |title=Numerical Heat Transfer and Fluid Flow |publisher=Hemisphere Publishing Corporation |year=1980}}</ref> Despite higher computational resource requirements and complexity in implementation compared to the finite difference method and finite volume method, the FEM provides high accuracy in modeling boundaries, complex geometries, and temperature fields, which is critically important for predicting defects in castings and optimizing casting processes.<ref>{{Cite journal |last=E. Abhilash and M. A. Joseph |date=2009 |title=Modelling and Simulation of Casting Process: an Overview |url=https://www.researchgate.net/publication/270757498 |journal=Indian Foundry Journal |volume=55}}</ref><ref>{{Cite book |last=Incropera, F.P., & DeWitt, D.P. |title=Fundamentals of Heat and Mass Transfer |publisher=John Wiley & Sons |year=2001}}</ref>

== Application in production==
[[Computer-aided engineering]] (CAE) systems for casting processes have long been used by foundries around the world as a "virtual foundry workshop," where it is possible to perform and verify any idea that arises in the minds of designers and [[Engineering:Engineering technologist|technologists]].<ref>{{Cite journal |last=Prasad, B.K., & Sahu, S. |title=Optimization of gating system design for castings using computational modeling and simulation |journal=Transactions of the Indian Institute of Metals |publication-date=2014 |volume=67 |issue=2 |pages=155–163 |doi=10.1007/s12666-013-0350-5|doi-broken-date=16 May 2024 }}</ref> The [[Finance:International finance|global market]] for CAE for casting processes can already be considered established.<ref>{{Cite book |last=Chougule, R.G. |title=Casting Simulation and Optimization: Benefits, Bottlenecks, and Best Practices |publisher=Springer |year=2012}}</ref>

Within the structure of the company for the development of the technology of a new casting, a computer-aided design department for casting processes is created, responsible for operating CAE systems for casting processes. Calculations are carried out by specialists of the department according to their job instructions, and interaction with other departments is regulated by technological design instructions.<ref>{{Cite journal |last=Polishetty, A., Littlefair, G., & Pramanik, A. |title=Development of a CAE System for Simulation of Casting Defects |journal=Advances in Materials Science and Engineering |publication-date=2014 |volume=2014 |pages=1–8 |doi=10.1155/2014/956274|doi-broken-date=16 May 2024 |doi-access=free}}</ref>

The [[Engineering:Engineering design process|process]] begins with the delivery of the [[3D modeling|3D model]] and drawing of the part to the foundry technologists, who coordinate the casting configuration with the mechanical workshop and determine the [[Margin of error|margins]].<ref>{{Cite journal |last=Biswas, P., & Sarkar, A. |title=Integration of CAD/CAE for developing casting process simulation |journal=Journal of Materials Processing Technology |publication-date=2016 |volume=238 |pages=244–253 |doi=10.1016/j.jmatprotec.2016.07.004}}</ref> Then, the technology is developed in the CAE department and transferred to the foundry workshop for experimental castings. The results are monitored, and if necessary, the castings are examined in the central laboratory of the factory. If defects are detected, an adjustment of the model parameters and the technological process is made in the CAE department, after which the technology is tested again in the workshop.

This cycle is repeated until suitable castings are obtained, after which the technology is considered developed and implemented in [[Finance:Mass production|mass production]].<ref>{{Cite journal |last=Peter Trebuˇna, Miriam Pekarˇc´ıkov´a, Jana Kronov´ |date=2018 |title=AUTOMATION OF THE CASTING PROCESS BY THE USE OF SIMULATION SOFTWARE |url=https://bibliotekanauki.pl/articles/407215.pdf |journal=Management and Production Engineering Review |volume=9 |issue=1 |doi=10.24425/119403}}</ref><ref>{{Cite journal |last=Hu, H., & Pang, H. |title=Use of CAE for casting process design and defect analysis in aluminum castings |journal=Journal of Manufacturing Processes |publication-date=2013 |volume=15 |issue=1 |pages=14–23 |doi=10.1016/j.jmapro.2012.09.002}}</ref>

== Software and tools==
[[File:Csoft.jpg|thumb|Configuration and preparation for simulation in the software]]
In the modern foundry industry, software for the simulation of casting processes is widely used. Among the multitude of software solutions available, it is worth mentioning the most prominent and widely used products: Procast, MAGMASOFT, and PoligonSoft.

ProCAST: a casting process modeling system using the finite element method, which provides the joint solution of temperature, [[Physics:Hydrodynamics|hydrodynamics]], and [[Physics:Deformation|deformation]] problems, along with unique metallurgical capabilities, for all casting processes and casting alloys. In addition to the main aspects of casting production – filling, crystallization, and porosity prediction, ProCAST is capable of predicting the occurrence of deformations and residual stresses in the casting and can be used to analyze processes such as core making, [[Engineering:Centrifugal casting (silversmithing)|centrifugal casting]], [[Engineering:Lost-wax casting|lost wax casting]], continuous casting.<ref>{{Cite journal |last=Schmidt, P., & Heilmann, C. |title=Simulation of Casting Processes Using ProCAST |journal=Journal of Materials Processing Technology |publication-date=2004 |pages=1485–1490 |doi=10.1016/j.jmatprotec.2004.04.310}}</ref>

PoligonSoft: a casting process modeling system using the finite element method. Applicable for modeling almost any casting technology and any casting alloy. For a long time, PoligonSoft was the only casting process modeling system in the world that included a special model for calculating [[Earth:Porosity|microporosity]].<ref>{{Cite journal |last=V.P. Monastyrsky |date=2023 |title=Experience in application of new porosity model "PoligonSoft" for prediction of shrinkage defects in castings |url=https://www.researchgate.net/publication/369810018 |journal=Blanking Productions in Mechanical Engineering (Press Forging Foundry and Other Productions) |pages=51–57 |doi=10.36652/1684-1107-2023-21-2-51-57}}</ref><ref>{{Cite journal |last=Bogomolov, D.M., & Polyakov, V.S. |title=Application of PoligonSoft for Microporosity Prediction in Castings |journal=Theoretical Foundations of Chemical Engineering |publication-date=2011 |volume=45 |issue=6 |pages=896–900 |doi=10.1134/S004057951106008X}}</ref> To date, this model can be considered the most stable, and the results obtained with its help can satisfy the most demanding users. In many respects, PoligonSoft can be considered the Russian equivalent of the ProCAST system.<ref>{{Cite journal |last=Zolotorevsky, N.Y., & Klimenov, V.A. |title=Modeling and Analysis of Casting Processes Using PoligonSoft |journal=Russian Metallurgy (Metally) |publication-date=2009 |volume=2009 |issue=2 |pages=144–149 |doi=10.1134/S0036029509020115|doi-broken-date=16 May 2024 }}</ref>

MAGMASOFT: a casting process modeling system using the finite difference method. It allows analyzing thermal processes, mold filling, crystallization, and predicting defects in castings.<ref>{{Cite journal |last=Lee, S.Y., & Lee, P.D. |title=Simulation of Casting Processes with MAGMASOFT |journal=International Journal of Cast Metals Research |publication-date=2001 |volume=14 |issue=2 |pages=87–92 |doi=10.1080/13640461.2001.11819321|doi-broken-date=16 May 2024 }}</ref> The program includes modules for different casting technologies and helps optimize casting parameters to improve product quality. MAGMASOFT is an effective tool for increasing the productivity and quality of casting production.<ref>{{Cite journal |last=Nikanorov A.V. |date=2018 |title=Comparative analysis of computer programs for modeling casting processes |url=https://cyberleninka.ru/article/n/sravnitelnyy-analiz-kompyuternyh-programm-dlya-modelirovaniya-liteynyh-protsessov |journal=Vestnik IrGTU |volume=11 |issue=142 |pages=209–218 |doi=10.21285/1814-3520-2018-11-209-218 |language=ru |issn=1814-3520}}</ref>

== Future trends==
The simulation of the casting process reflects the user's knowledge, who decides whether the filling system has led to an acceptable result. [[Engineering:Engineering optimization|Optimization]] suggestions must come from the operator. The main problem is that all processes occur simultaneously and are interconnected: changes in one parameter affect many quality characteristics of the casting.<ref>{{Cite journal |last=Xiao, X., & Yang, J. |title=Impact of Process Parameters on Casting Quality and Optimization |journal=Journal of Manufacturing Science and Engineering |publication-date=2020 |volume=142 |issue=8 |doi=10.1115/1.4047830}}</ref>

Autonomous optimization, which began in the late 1980s, uses the simulation tool as a virtual testing ground, changing filling conditions and process parameters to find the optimal solution.<ref>{{Cite journal |last=Zhu, H., & Liao, H. |title=Autonomous Process Optimization in Casting Simulation |journal=Advances in Mechanical Engineering |publication-date=2017 |volume=9 |issue=3 |pages=1–12 |doi=10.1177/1687814017694538|doi-broken-date=16 May 2024 }}</ref> This allows evaluating numerous process parameters and their impact on process stability.

It is important to remember that only what can be modeled can be optimized. Optimization does not replace process knowledge or experience.<ref>{{Cite journal |last=Wang, S., & Guo, Z. |title=Combining Knowledge-Based Systems with Simulation for Casting Process Optimization |journal=Engineering Applications of Artificial Intelligence |publication-date=2016 |volume=52 |pages=165–173 |doi=10.1016/j.engappai.2016.03.014|doi-broken-date=16 May 2024 }}</ref> The simulation user must know the objectives and quality criteria necessary to achieve those objectives and formulate specific questions to the program to obtain quantitative solutions.<ref>{{Cite journal |last=Yasuhiro Maeda |date=2010 |title=Status and Future Trends of Casting CAE |url=https://www.researchgate.net/publication/276054122 |journal=Journal of the Japan Society for Precision Engineering |volume=76 |issue=4 |pages=395–398 |doi=10.2493/jjspe.76.395}}</ref>

==References==
{{Reflist}}

==External links==

* [https://www.researchgate.net/publication/364458348_PoligonSoft_for_foundry Сasting simulation software]
* [https://www.researchgate.net/publication/371766526_The_efficiency_of_multithreaded_computing_in_casting_simulation_software The efficiency of multithreaded computing in casting simulation software]

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[[Category:Foundries| ]]
[[Category:Metalworking]]
[[Category:Software]]
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{{Sourceattribution|Metal casting simulation}}