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A component-based parallel infrastructure for the simulation of fluid–structure interaction

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Abstract

The Uintah computational framework is a component-based infrastructure, designed for highly parallel simulations of complex fluid–structure interaction problems. Uintah utilizes an abstract representation of parallel computation and communication to express data dependencies between multiple physics components. These features allow parallelism to be integrated between multiple components while maintaining overall scalability. Uintah provides mechanisms for load-balancing, data communication, data I/O, and checkpoint/restart. The underlying infrastructure is designed to accommodate a range of PDE solution methods. The primary techniques described here, are the material point method (MPM) for structural mechanics and a multi-material fluid mechanics capability. MPM employs a particle-based representation of solid materials that interact through a semi-structured background grid. We describe a scalable infrastructure for problems with large deformation, high strain rates, and complex material behavior. Uintah is a product of the University of Utah Center for Accidental Fires and Explosions (C-SAFE), a DOE-funded Center of Excellence. This approach has been used to simulate numerous complex problems, including the response of energetic devices subject to harsh environments such as hydrocarbon pool fires. This scenario involves a wide range of length and time scales including a relatively slow heating phase punctuated by pressurization and rupture of the device.

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References

  1. Henderson T, McMurtry P, Smith P, Voth G, Wight C, Pershing D (1994) Simulating accidental fires and explosions. Comp Sci Eng 2:64–76

    Article  Google Scholar 

  2. Krishnamoorthy G, Borodai S, Rawat R, Spinti J, Smith P (2005) Numerical modeling of radiative heat transfer in pool fire simulations. ASME International Mechanical Engineering Congress (IMECE), Orlando, Florida

  3. Kashiwa B, Rauenzahn R (1994) A multimaterial formalism. Technical Report LA-UR-94-771, Los Alamos National Laboratory, Los Alamos

  4. Kashiwa B, Lewis M, Wilson T (1996) Fluid–structure interaction modeling. Technical Report LA-13111-PR, Los Alamos National Laboratory, Los Alamos

  5. Kashiwa B (2001) A multified model and method for fluid–structure interaction dynamics. Technical Report LA-UR-01-1136, Los Alamos National Laboratory, Los Alamos

  6. Kashiwa B, Gaffney E (2003) Design basis for cfdlib. Technical Report LA-UR-03-1295, Los Alamos National Laboratory, Los Alamos

  7. Harlow F, Amsden A (1968) Numerical calculation of almost incompressible flow. J Comp Phys 3:80–93

    Article  MATH  Google Scholar 

  8. Kashiwa B, Rauenzahn R (1994) A cell-centered ice method for multiphase flow simulations. Technical Report LA-UR-93-3922, Los Alamos National Laboratory, Los Alamos

  9. Guilkey J, Harman T, Xia A, Kashiwa B, McMurtry P (2003) An eulerian–lagrangian approach for large deformation fluid–structure interaction problems, part 1: Algorithm development. In: Fluid structure interaction II. WIT Press, Cadiz

  10. Harman T, Guilkey J, Kashiwa B, Schmidt J, McMurtry P (2003) An eulerian–lagrangian approach for large deformation fluid–structure interaction problems, part 2: Multi-physics simulations within a modern computational framework. In: Fluid structure interaction II. Cadiz, Spain, WIT Press

  11. Guilkey J, Hoying J, Weiss J (2006) Modeling of multicellular constructs with the material point method. J Biomech 39:2074–2086

    Article  Google Scholar 

  12. Brydon A, Bardenhagen S, Miller E, Seidler G (2005) Simulation of the densification of real open-celled foam microstructures. J Mech Phys Solids 53:2638–2660

    Article  Google Scholar 

  13. Guo Y, Nairn J (2004) Calculation of j-integral and stress intensity factors using the material point method. Comput Model Eng Sci 6:295–308

    MATH  Google Scholar 

  14. Sulsky D, Chen Z, Schreyer H (1994) A particle method for history-dependent materials. Comp Methods Appl Mech Eng 118:179–196

    Article  MATH  MathSciNet  Google Scholar 

  15. Sulsky D, Zhou S, Schreyer H (1995) Application of a particle-in-cell method to solid mechanics. Comput Phys Commun 87:236–252

    Article  MATH  Google Scholar 

  16. Brackbill J, Ruppel H (1986) Flip: a low-dissipation, particle-in-cell method for fluid flows in two dimensions. J Comp Phys 65:314–343

    Article  MATH  MathSciNet  Google Scholar 

  17. Guilkey J, Weiss J (2003) Implicit time integration for the material point method: quantitative and algorithmic comparisons with the finite element method. Int J Num Meth Eng 57:1323–1338

    Article  MATH  Google Scholar 

  18. Vajracharya S, Karmesin S, Beckman P, Crotinger J, Malony A, Shende S, Oldehoeft R, Smith S (1999) Smarts: exploiting temporal locality and parallelism through vertical execution. In: Proceedings of the 13th international conference on supercomputing

  19. Atlas S, Banerjee S, Cummings J, Hinker P, Srikant M, Reynders J, Tholburn M (1995) POOMA: a high-performance distributed simulation environment for scientific applications. In: Supercomputing ’95 proceedings

  20. Feo J, Cann D, Oldehoeft R (1990) A report on the sisal language project. J Parallel Distrib Comput 10(4):349–366

    Article  Google Scholar 

  21. Berger M, Colella P (1989) Local adaptive mesh refinement for shock hydrodynamics. J Comput Phys 82:64–84

    Article  MATH  Google Scholar 

  22. Bardenhagen S, Guilkey J, Roessig K, Brackbill J, Witzel W, Foster J (2001) An improved contact algorithm for the material point method and application to stress propagation in granular material. CMES 2:509–522

    MATH  Google Scholar 

  23. Banerjee B (2005) The mechanical threshold stress model for various tempers of ansi 4340 steel. Int J Solids Struct (in press)

  24. Banerjee B (2005) Validation of a multi-physics code: plasticity models and taylor impact. In: Proceedings of joint ASME/ASCE/SES conference on mechanics and materials. Baton Rouge, LA

  25. Banerjee B (2004) Material point method simulations of fragmenting cylinders. In: Proceedings of the 17th ASCE engineering mechanics conference. Newark, DE

  26. Banerjee B, Guilkey J, Harman T, Schmidt J, McMurtry P (2005) Simulation of impact and fragmentation with the material point method. In: Proceedings of the 11th international conference on fracture, Turin, Italy, p 689

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Correspondence to Steven G. Parker.

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Parker, S.G., Guilkey, J. & Harman, T. A component-based parallel infrastructure for the simulation of fluid–structure interaction. Engineering with Computers 22, 277–292 (2006). https://doi.org/10.1007/s00366-006-0047-5

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  • DOI: https://doi.org/10.1007/s00366-006-0047-5

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