Parallel Performance in Multi-physics Simulation

  • Kevin McManus
  • Mark Cross
  • Chris Walshaw
  • Nick Croft
  • Alison Williams
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2330)


A comprehensive simulation of solidification/melting processes requires the simultaneous representation of free surface fluid flow, heat transfer, phase change, non-linear solid mechanics and, possibly, electromagnetics together with their interactions in what is now referred to as ’multi-physics’ simulation. A 3D computational procedure and software tool, PHYSICA, embedding the above multi-physics models using finite volume methods on unstructured meshes (FV-UM) has been developed. Multi-physics simulations are extremely compute intensive and a strategy to parallelise such codes has, therefore, been developed. This strategy has been applied to PHYSICA and evaluated on a range of challenging multi-physics problems drawn from actual industrial cases.


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  1. 1.
    Abaqus. URL:
  2. 2.
    G. M. Amdahl. Validity of the single-processor approach to achieving large scale computing capabilities. In Proc AFIPS, pages 483–485, 1967.Google Scholar
  3. 3.
  4. 4.
    C. Bailey and M. Cross. A finite volume procedure to solve elastic solid mechanics problems in three dimensions on an unstructured mesh. Int. J Num Meth in Engg, 38:1757–776, 1995.MATHCrossRefGoogle Scholar
  5. 5.
  6. 6.
    P. Chow, M. Cross, and K. Pericleous. A natural extension of standard control volume CFD procedures to polygonal unstructured meshes. Appl. Math Modelling, 20:170–183, 1995.CrossRefGoogle Scholar
  7. 7.
    Concerto. URL: Vector Fields.
  8. 8.
    N. Croft, K. Pericleous, and M. Cross. PHYSICA: a multiphysics environment for complex flow processes. Numerical Methods in Laminar and Turbulent Flows, Vol IX:1269–1280, 1995.Google Scholar
  9. 9.
    M. Cross. Computational issues in the modelling of materials based manufacturing processes. Journal of Computationally Aided Materials, 3:100–116, 1996.CrossRefGoogle Scholar
  10. 10.
    M.Cross et al. Computational modelling of casting processes-a multi-physics challenge. In G. Irons and A. Cramb, editors, Brimacombe Memorial Symposium Proceedings, pages 439–450. Met Soc (Canada), 2000.Google Scholar
  11. 11.
    Fluent. URL:
  12. 12.
    JOSTLE. URL: University of Creenwich.
  13. 13.
    P. Leggett, S. P. Johnson, and M. Cross. CAPLib-a’ thin layer’ message processing library to support computational mechanics codes on distributed memory parallel systems. Advances in Engineering Software, 32:61–81, 2001.CrossRefGoogle Scholar
  14. 14.
    K. McManus, M. Cross,, C. Walshaw, S. Johnson, and P. Leggett. A scalable strategy for the parallelization of multiphysics unstructured-mesh iterative codes on distributed-memory systems. Int Jnl of High Performance Computing Applications, 14(2):137–174, 2000.CrossRefGoogle Scholar
  15. 15.
    MPI: Message Passing Interface. URL: Argonne National Laboratory.
  16. 16.
    E. Onate, M. Ceiveia, and O. C. Zienkiewicz. A finite volume format for structural mechanics. Int J Num Maths in Engg, 37:181–201, 1994.MATHCrossRefGoogle Scholar
  17. 17.
    S. V. Patankar and D. B. Spalding. A calculation procedure for heat, mass and momentum transfer in three dimensional parabolic flows. Int J Heat Mass Trans, 15:1787–1806, 1972.MATHCrossRefGoogle Scholar
  18. 18.
    K. Pericleous, M. Cross, M. Hughes, and D. Cook. Mathematical modelling of the solidification of liquid tin with electromagnetic stirring. Jnl of Magnetohydrody-namics, 32(4):472–478, 1996.Google Scholar
  19. 19.
    Physica. URL: University of Creenwich.
  20. 20.
    PVM Parallel Virtual Machine. URL: Oak Ridge National Laboratory.
  21. 21.
    C. Rhie and W. Chow. A numerical study of the flow past an isolated airfoil with trailing edge separation. JAIAA, 21:1525–1532, 1982.Google Scholar
  22. 22.
    G. Taylor, C. Bailey, and M. Cross. Solution of elasto-visco-plastic constitutive equalities: a finite volume approach. Appl Math Modelling, 19:746–760, 1995.MATHCrossRefGoogle Scholar
  23. 23.
    C. Walshaw and M. Cross. Parallel optimisation algorithms for multi-level mesh partitioning. Parallel Computing, 26:1635–1660, 2000.MATHCrossRefMathSciNetGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Kevin McManus
    • 1
  • Mark Cross
    • 1
  • Chris Walshaw
    • 1
  • Nick Croft
    • 1
  • Alison Williams
    • 1
  1. 1.Centre for Numerical Modelling and Process AnalysisUniversity of GreenwichLondon

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