, Volume 60, Issue 5, pp 32–39 | Cite as

Open source software for materials and process modeling

Overview Feature


Though open source engineering analysis tools have not been widely deployed, several of them have recently reached a point of maturity and usability in industry. This article focuses on the use of open source tools for modeling of materials and materials processes in particular. After defining open source software, it presents two case studies, surveys open source tools aimed at modeling of materials behavior and processes at multiple length and time scales, and discusses future prospects and application areas for open source tools.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    “Operating System Family Share for 11/2007 | TOP500 Supercomputing Sites,” /stats/list/30/osfam.Google Scholar
  2. 2.
    M. Macedonia, “Linux in Hollywood: A Star is Born,” Computer, 35 (2002), pp. 112–114.CrossRefGoogle Scholar
  3. 3.
  4. 4.
    “,” Scholar
  5. 5.
    “The Open Source Definition | Open Source Initiative,”
  6. 6.
    “Open Source Initiative,” Scholar
  7. 7.
    A. Krishnan, U.B. Pal, and X.G. Lu, “Solid Oxide Membrane Process for Magnesium Production Directly from Magnesium Oxide,” Metallurgical and Materials Transactions B, 36 (2005), pp. 463–473.CrossRefGoogle Scholar
  8. 8.
    A.C. Powell and Y. Lok, “Julian Boundary Element Code,”
  9. 9.
    R.A. DeLucas, A.C. Powell, and U.B. Pal, “Boundary Element Modeling of Solid Oxide Membrane Process,” TMS 2008 Annual Meeting Supplemental Proceedings Volume 2: Materials Characterization, Computation and Modeling (Warrendale, PA: TMS, 2008), pp. 301–306.Google Scholar
  10. 10.
    “Python Programming Language—Official Website,” Scholar
  11. 11.
    “FiPy,” Scholar
  12. 12.
    S. Langer, E. Fuller, and W. Carter, “OOF: An Image-based Finite-Element Analysis of Material Microstructures,” Computing in Science & Engineering, 3 (2001), pp. 15–23.CrossRefGoogle Scholar
  13. 13.
    A. van de Walle and G. Ceder, “The Effect of Lattice Vibrations on Substitutional Alloy Thermodynamics,” Reviews of Modern Physics, 74 (January 2002), p. 11.CrossRefGoogle Scholar
  14. 14.
    Axel van de Walle, Gautam Ghosh, and Mark Asta, “Ab initio Modeling of Alloy Phase Equilibria,” Applied Computational Materials Modeling (2007), pp. 1–34;
  15. 15.
    A. van de Walle, “Alloy Theoretic Automated Toolkit (ATAT),” Scholar
  16. 16.
    L. Kaufman, “Computational Thermodynamics and Materials Design,” CALPHAD, 25 (2001), pp. 141–161.CrossRefGoogle Scholar
  17. 17.
    John Allison, Dan Backman, and Leo Christodoulou, Integrated Computational Materials Engineering: A New Paradigm for the Global Materials Profession,” JOM, 58(11) (2006), pp. 25–27.CrossRefGoogle Scholar
  18. 18.
    G.B. Olson, “Computational Design of Hierarchically Structured Materials,” Science, 277 (August 1997), pp. 1237–1242.CrossRefGoogle Scholar
  19. 19.
    Zi-Kui Liu, Long-Qing Chen, and Krishna Rajan, “Linking Length Scales via Materials Informatics,” JOM, 58(11) (2006), pp. 42–50.CrossRefGoogle Scholar
  20. 20.
    Daniel G. Backman et al., “ICME at GE: Accelerating the Insertion of New Materials and Processes,” in Ref.16, pp. 36–41.Google Scholar
  21. 21.
    J. Allison et al., “Virtual Aluminum Castings: An Industrial Application of ICME,” in Ref. 16, pp. 28–35.Google Scholar
  22. 22.
    J. Hafner, “Atomic-Scale Computational Materials Science,” Acta Materialia, 48 (January 2000), pp. 71–92.CrossRefGoogle Scholar
  23. 23.
    W. Kohn and L.J. Sham, “Quantum Density Oscillations in an Inhomogeneous Electron Gas,” Physical Review, 137 (March 1965), p. A1697.CrossRefGoogle Scholar
  24. 24.
    J. Hafner, “Materials Simulations Using VASP—A Quantum Perspective to Materials Science,” Computer Physics Communications, 177 (July 2007), pp. 6–13.CrossRefGoogle Scholar
  25. 25.
    X. Gonze et al., “First-Principles Computation of Material Properties: The ABINIT Software Project,” Computational Materials Science, 25 (November 2002), pp. 478–492.CrossRefGoogle Scholar
  26. 26.
    J.M. Sanchez, “Cluster Expansions and the Configurational Energy of Alloys,” Physical Review B, 48 (November 1993), p. 14013.CrossRefGoogle Scholar
  27. 27.
    Zi-Kui Liu and Long-Qing Chen, “Integration of First-Principles Calculations, Calphad Modeling, and Phase-Field Simulations,” Applied Computational Materials Modeling (2007), pp. 171–213;
  28. 28.
    P.E.A. Turchi et al., “Interface between Quantum-Mechanical-Based Approaches, Experiments, and CALPHAD Methodology,” CALPHAD, 31 (March 2007), pp. 4–27.CrossRefGoogle Scholar
  29. 29.
    J.Z. Zhu et al., “Linking Phase-Field Model to CALPHAD: Application to Precipitate Shape Evolution in Ni-Base Alloys,” Scripta Materialia, 46 (March 2002), pp. 401–406.CrossRefGoogle Scholar
  30. 30.
    F. Roters, “The Texture Component Crystal Plasticity Finite Element Method,” Continuum Scale Simulation of Engineering Materials (New York: Wiley, 2004), Scholar
  31. 31.
    “CAELinux,” Scholar
  32. 32.
    Electricite de France, “Code_Aster,” Scholar
  33. 33.
    G. Dhondt and K. Wittig, “CALCULIX: A Three-Dimensional Structural Finite Elemente Program,” CALCULIX, Scholar
  34. 34.
    J. Forssell and Y. Mikhaylovski, “Impact Finite Element Program,”
  35. 35.
    “OpenFOAM: The Open Source Computational Fluid Dynamics (CFD) Toolbox,” Scholar
  36. 36.
    “libMesh—C++ Finite Element Library,”
  37. 37.
    Electricite de France, “Code_Saturne,”
  38. 38.
    E. Raymond, “The Magic Cauldron,” The Cathedral and the Bazaar (Sebastopol, CA: O’Reilly, 1999),

Copyright information

© TMS 2008

Authors and Affiliations

  1. 1.OpennovationNewtonUSA
  2. 2.Texas A&M UniversityCollege StationUSA

Personalised recommendations