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Turbulent Combustion Modeling pp 409–437Cite as

Computational Frameworks for Advanced Combustion Simulations

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Part of the book series: Fluid Mechanics and Its Applications ((FMIA,volume 95))

Abstract

Computational frameworks can significantly assist in the construction, extension and maintenance of simulation codes. As the nature of problems addressed by computational means has grown in complexity, such frameworks have evolved to incorporate a commensurate degree of sophistication, both in terms of the numerical algorithms that they accommodate as well as the software architectural discipline they impose on their users. In this chapter, we discuss a component framework, the Common Component Architecture (CCA), for developing scientific software, and describe how it has been used to develop a toolkit for simulating reacting flows. In particular, we will discuss why a component architecture was chosen and the philosophy behind the particular software design. Using statistics drawn from the toolkit, we will analyze the code structure and investigate to what degree the aims of the software design were actually realized. We will explore how CCA was employed to design a high-order simulation code on block-structured adaptive meshes, as well as a simulation capacity for adaptive stiffness reduction in detailed chemical models. We conclude the chapter with two reacting flow studies performed using the above-mentioned computational capabilities.

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References

  1. Allan, B.A., Armstrong, R.C., Wolfe, A.P., Ray, J., Bernholdt, D.E., Kohl, J.A.: The CCA core specifications in a distributed memory SPMD framework. Concurrency-Pract. Ex. 14, 323–345 (2002)

    Article  MATH  Google Scholar 

  2. Allan, B.A., Norris, B., Elwasif, W.R., Armstrong, R.C.: Managing scientific software complexity with Bocca and CCA. Sci. Program. 16, 315–327 (2008)

    Google Scholar 

  3. Almgren, A., Bell, J., Colella, P., Howell, L., Welcome, M.: A conservative adaptive projection method for the variable density incompressible Navier-Stokes equations. J. Comput. Phys. 142, 1–46 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  4. AmrLib Homepage. Available from (accessed October 2009) https://ccse.lbl.gov/Software/index.html

  5. AMROC Homepage. Available from (accessed October 2009) http://amroc.sourceforge.net/

  6. Anthonissen, M.J.H., Bennett, B.A.V., Smooke, M.D.: An adaptive multilevel local defect correction technique with application to combustion. Combust. Theory Model. 9, 273–299 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  7. Arya, S., Mount, D.M., Netanyahu, N.S., Silverman, R., Wu, A.Y.: An optimal algorithm for approximate nearest neighbor searching in fixed dimensions. J. Assoc. Comput. Mach. 45, 891–923 (1998)

    MATH  MathSciNet  Google Scholar 

  8. Banks, J.W., Schwendeman, D.W., Kapila, A.K., Henshaw, W.D.: A high-resolution Godunov method for compressible multi-material flow on overlapping grids. J. Comput. Phys. 223, 262–297 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  9. Barad, M., Colella, P.: A fourth-order accurate local refinement method for Poisson’s equation. J. Comput. Phys. 209, 1–18 (2005)

    Article  MATH  MathSciNet  Google Scholar 

  10. Bell, J.B., Day, M.S., Grcar, J.F., Lijewski, M.J., Driscoll, J.F., Filatyev, S.F.: Numerical simulation of a laboratory-scale turbulent slot flame. Proc. Combust. Inst. 31, 1299–1307 (2007)

    Article  Google Scholar 

  11. Bell, J.B., Day, M.S., Shepherd, I.G., Johnson, M., Cheng, R.K., Grcar, J.F., Beckner, V.E., Lijewski, M.J.: Numerical simulation of a laboratory-scale turbulent V-flame. Proc. Natl. Acad. Sci. USA 102, 10,006–10,011 (2005)

    Google Scholar 

  12. Bennett, B.A.V., Smooke, M.D.: Local rectangular refinement with application to axisymmetric laminar flames. Combust. Theory Model. 2, 221–258 (1998)

    Article  MATH  Google Scholar 

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

    Article  MATH  Google Scholar 

  14. Bernholdt, D.E., Allan, B.A., Armstrong, R., Bertrand, F., Chiu, K., Dahlgren, T.L., Damevski, K., Elwasif, W.R., Epperly, T.G.W., Govindaraju, M., Katz, D.S., Kohl, J.A., Krishnan, M., Kumfert, G., Larson, J.W., Lefantzi, S., Lewis, M.J., Malony, A.D., McInnes, L.C., Nieplocha, J., Norris, B., Parker, S.G., Ray, J., Shende, S., Windus, T.L., Zhou, S.: A component architecture for high-performance scientific computing. Intl. J. High-Perf. Computing Appl. 20, 162–202 (2006)

    Google Scholar 

  15. Cactus Homepage. Available from (accessed October 2009) http://en.wikipedia.org/wiki/Cactus_Framework

  16. CCA Tutorials Hands-On Guide. Available from (accessed October 2009) http://www.cca-forum.org/tutorials/

  17. CHOMBO. Available from (accessed October 2009) http://seesar.lbl.gov/anag/chombo/

  18. Cirak, F., Deiterding, R., Mauch, S.P.: Large-scale fluid-structure interaction simulation of viscoplastic and fracturing thin shells subjected to shocks and detonations. Comput. Struct. 85, 1049–1065 (2006)

    Article  Google Scholar 

  19. Cohen, S.D., Hindmarsh, A.C.: CVODE, a stiff/nonstiff ODE solver in C. Comput. Phys. 10, 138–143 (1996)

    Google Scholar 

  20. Colella, P., Dorr, M., Hittinger, J., Martin, D.F., McCorquodale, P.: High-order finite-volume adaptive methods on locally rectangular grids. J. Phy.: Conf. Ser. 180, 012,010 (5pp) (2009)

    Google Scholar 

  21. Colella, P., Graves, D.T., Keen, B.J., Modiano, D.: A Cartesian grid embedded boundary method for hyperbolic conservation laws. J. Comput. Phys. 211, 347–366 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  22. CORBA Component Model Webpage. Available from (accessed October 2009) http://www.omg.org

  23. Dahlgren, T., Epperly, T., Kumfert, G., Leek, J.: Babel User’s Guide. CASC, Lawrence Livermore National Laboratory, Livermore, CA (2005)

    Google Scholar 

  24. Day, M.S., Bell, J.B.: Numerical simulation of laminar reacting flows with complex chemistry. Combust. Theory Model. 4, 535–556 (2000)

    Article  MATH  Google Scholar 

  25. Deiterding, R.: Object-oriented design of an AMR algorithm for distributed memory computers. In: 8th Int. Conf. on Hyperbolic Problems. Magdeburg (2000)

    Google Scholar 

  26. Deiterding, R.: Detonation structure simulation with AMROC. In: L.T. Yang (ed.) High Performance Computing and Communications, no. 3726 in Lecture Notes in Computer Science, pp. 916–927. Springer, Berlin Heidelberg (2005)

    Chapter  Google Scholar 

  27. Deiterding, R.: A parallel adaptive method for simulating shock-induced combustion with detailed chemical kinetics in complex domains. Comput. Struct. 87, 769–783 (2009)

    Article  Google Scholar 

  28. Deiterding, R., Cirak, F., Mauch, S., Meiron, D.: A virtual test facility for simulating detonation- and shock-induced deformation and fracture of thin flexible shells. Int. J. Multiscale Computational Engineering 5, 47–63 (2007)

    Article  Google Scholar 

  29. Deiterding, R., Radovitzky, R., Mauch, S.P., Noels, L., Cummings, J.C., Meiron, D.I.: A virtual test facility for the efficient simulation of solid material response under strong shock and detonation wave loading. Eng. Comput. 22, 325–347 (2006)

    Article  Google Scholar 

  30. Drake, J.B., Jones, P.W., Carr Jr., George R., Overview of the software design of the community climate system model. Intl. J. High-Perf. Computing Appl. 19, 177–186 (2005)

    Article  Google Scholar 

  31. Dubey, A., Antypas, K., Ganapathy, M.K., Reid, L.B., Riley, K., Sheeler, D., Siegel, A., Weide, K.: Extensible component based architecture for FLASH, A massively parallel, multiphysics simulation code. Parallel Comput. (2009). Submitted, preprint at http://arxiv.org/pdf/0903.4875

  32. Earth Systems Modeling Framework Homepage. Available from (accessed October 2009) http://www.esmf.ucar.edu/

  33. Englander, R., Loukides, M.: Developing Java Beans (Java Series). O’Reilly and Associates (1997)

    Google Scholar 

  34. Falgout, R., Yang, U.: Hypre: a library of high performance preconditioners, in Computational Science. In: P.M.A. Sloot, C. Tan, J.J. Dongarra, A.G. Hoekstra (eds.) Lecture Notes in Computer Science, vol. 2331, pp. 632–641. Springer-Verlag (2002)

    Google Scholar 

  35. Fryxell, B., Olson, K., Ricker, P., Timmes, F.X., Zingale, M., Lamb, D.Q., MacNeice, P., Rosner, R., Truran, J.W., Tufo, H.: FLASH: an adaptive mesh hydrodynamics code for modeling astrophysical thermonuclear flashes. Ap. J. Supplement Series 131, 273–334 (2000)

    Article  Google Scholar 

  36. Godfrey, M.W., Tu, Q.: Evolution in open source software: A case study. In: Proceedings of the International Conference on Software Maintenance, pp. 131–142 (2000)

    Google Scholar 

  37. Goodale, T., Allen, G., Lanfermann, G., Mass, J., Radke, T., Seide, E., Shalf, J.: The Cactus framework and tolkit: Design and applications. In: Proceedings of Vector and Parallel Processing - VECPAR 2002 (2002)

    Google Scholar 

  38. GrACE Homepage. Available from (accessed October 2009) http://www.caip.rutgers.edu/TASSL/

  39. Henshaw, W.D.: A fourth-order accurate methods for the incompressible Navier-Stokes equations on overlapping grids. J. Comput. Phys. 113, 13–25 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  40. Henshaw, W.D., Schwendeman, D.W.: An adaptive numerical scheme for high-speed reactive fow on overlapping grids. J. Comput. Phys. 191, 420–447 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  41. Henshaw, W.D., Schwendeman, D.W.: Moving overlapping grids with adaptive mesh refinement for high-speed reactive and non-reactive flow. J. Comput. Phys. 216, 744–779 (2006)

    Article  MATH  MathSciNet  Google Scholar 

  42. Henshaw, W.D., Schwendeman, D.W.: Parallel computation of three-dimensional Flows using Overlapping Grids with Adaptive Mesh Refinement. J. Comput. Phys. 227, 7469–7502 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  43. Huelette, G.C., Sottile, M.J., Armstrong, R., Allan, B.: OnRamp: Enabling a New component-based development paradigm. In: Proceedings of Component-Based High Performance Computing (2009)

    Google Scholar 

  44. Kadioglu, S., Klein, R., Minion, M.: A fourth-order auxiliary variable projection method for zero-Mach number gas dynamics. J. Comput. Phys. 227, 2012–2043 (2008)

    Article  MATH  MathSciNet  Google Scholar 

  45. Kenny, J.P., Janssen, C.L., Valeev, E.F., Windus, T.L.: Components for integral evaluation in quantum chemistry. J. Comput. Chem. 29(4), 562–577 (2008)

    Article  Google Scholar 

  46. Krishnan, M., Alexeev, Y., Windus, T.L., Nieplocha, J.: Multilevel parallelism in computational chemistry using common component architecture and global arrays. In: SC ’05: Proceedings of the 2005 ACM/IEEE Conference on Supercomputing, p. 23. IEEE Computer Society, Washington, DC, USA (2005)

    Google Scholar 

  47. Lam, S.: Using CSP to understand complex chemical kinetics. Combust. Sci. Technol. 89, 375–404 (1993)

    Article  Google Scholar 

  48. Lam, S., Goussis, D.: Understanding complex chemical kinetics with computational singular perturbation. Proc. Combust. Inst. 22, 931–941 (1988)

    Google Scholar 

  49. Lee, J., Najm, H., Lefantzi, S., Ray, J., Frenklach, M., Valorani, M., Goussis, D.: A CSP and tabulation based adaptive chemistry model. Combust. Theory Model. 11(1), 73–102 (2007)

    Article  MATH  Google Scholar 

  50. Lee, J., Najm, H., Lefantzi, S., Ray, J., Goussis, D.: On chain branching and its role in homogeneous ignition and premixed flame propagation. In: K. Bathe (ed.) Computational Fluid and Solid Mechanics 2005, pp. 717–720. Elsevier Science (2005)

    Google Scholar 

  51. Lee, J.C., Najm, H.N., Lefantzi, S., Ray, J., Frenklach, M., Valorani, M., Goussis, D.: A CSP and tabulation based adaptive chemistry model. Combust. Theory Model. 11, 73–102 (2007)

    Article  MATH  Google Scholar 

  52. Lefantzi, S., Ray, J., Kennedy, C.A., Najm, H.N.: A component-based toolkit for reacting flows with high order spatial discretizations on structured adaptively refined meshes. Prog. Comput. Fluid Dy. 5, 298–315 (2005)

    Article  MATH  Google Scholar 

  53. Lefantzi, S., Ray, J., Najm, H.N.: Using the common component architecture to design high performance scientific simulation codes. In: Proceedings of the International Parallel and Distributed Processing Symposium. Nice, France (2003)

    Google Scholar 

  54. Li, X., Parashar, M.: Hierarchical partitioning techniques for structured adaptive mesh refinement applications. J. Supercomput. 28, 265–278 (2004)

    Article  MATH  Google Scholar 

  55. Li, X., Parashar, M.: Hybrid runtime management of space-time heterogeneity for parallel structured adaptive applications. IEEE Transactions on Parallel and Distributed Systems 18, 1202–1214 (2007)

    Article  Google Scholar 

  56. Liu, H., Parashar, M.: Enabling self-management of component-based high-performance scientific applications. In: Proceedings of the 14th IEEE International Symposium on High Performance Distributed Computing (HPDC-14). Research Triangle Park, NC (2005)

    Google Scholar 

  57. Liu, H., Parashar, M.: Accord: A programming rramework for autonomic applications. IEEE Transaction on Systems, Man, and Cybernetics 36, 341–352 (2006). Special issue on Engineering Autonomic Systems, Editors: R. Sterritt and T. Bapty

    Google Scholar 

  58. Majda, A., Sethian, J.: The derivation and numerical solution of the equations for zero Mach number combustion. Combust. Sci. Technol. 42, 185–205 (1985)

    Article  Google Scholar 

  59. Martin, D.F., Colella, P.: A cell-centered adaptive projection method for the incompressible euler equations. J. Comput. Phys. 163, 271–312 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  60. McBride, B.J., Gordon, S., Reno, M.: Coefficients for calculating thermodynamic and transport properties of individual species. Tech. Rep. TM-4513, NASA (1993)

    Google Scholar 

  61. McInnes, L.C., Allan, B.A., Armstrong, R., Benson, S.J., Bernholdt, D.E., Dahlgren, T.L., Diachin, L.F., Krishnan, M., Kohl, J.A., Larson, J.W., Lefantzi, S., Nieplocha, J., Norris, B., Parker, S.G., Ray, J., Zhou, S.: Parallel PDE-based simulations using the common component architecture. In: Numerical Solution of Partial Differential Equations on Parallel Computers, pp. 327–384. Springer (2006)

    Chapter  Google Scholar 

  62. McInnes, L.C., Ray, J., Armstrong, R., Dahlgren, T.L., Malony, A., Norris, B., Shende, S., Kenny, J.P., Steensland, J.: Computational quality of service for scientific CCA applications: Composition, substitution, and reconfiguration. Tech. Rep. ANL/MCS-P1326-0206, Argonne National Laboratory (2006). ftp://info.mcs.anl.gov/pub/tech_reports/reports/P1326.pdf

  63. Meir “Manny” Lehman’s FEAST project. Available from (accessed October 2009) http://www.doc.ic.ac.uk/~mml/feast

  64. Najm, H., Knio, O.: Modeling lw Mach number reacting flow with detailed chemistry and transport. J. Sci. Comp. 25, 263–287 (2005)

    Article  MathSciNet  Google Scholar 

  65. Overture Homepage. Available from (accessed October 2009) https://computation.llnl.gov/casc/Overture/

  66. Pantano, C., Deiterding, R., Hill, D.J., Pullin, D.I.: A low numerical dissipation patch-based adaptive mesh refinement method for large-eddy simulation of compressible flows. J. Comput. Phys. 221, 63–87 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  67. Parashar, M., Browne, J.C.: System engineering for high performance computing software: The HDDA/DAGH infrastructure for implementation of parallel structured adaptive mesh refinement. In: D.B.G.S.B. Baden, M.P. Chrisochoides, M.L. Norman (eds.) Structured Adaptive Mesh Refinement, IMA, Vol. 117. Springer-Verlag (2000)

    Google Scholar 

  68. Paul, P.H.: DRFM: A new package for the evaluation of gas-phase-transport properties. Sandia Report SAND98-8203, Sandia National Laboratories, Albuquerque, New Mexico (1997)

    Google Scholar 

  69. Publications from the Applied Numerical Algorithms Group. Available from (accessed October 2009) http://seesar.lbl.gov/anag/publication.html

  70. Publications Using AMROC and Virtual Test Facility. Available from (accessed October 2009) http://www.csm.ornl.gov/~r2v/html/pub.htm

  71. Ray, J., Kennedy, C., Steensland, J., Najm, H.N.: Advanced algorithms for computations on block-structured adaptively refined meshes. J. Phys.: Conf. Ser. 16, 113–118 (2005)

    Article  Google Scholar 

  72. Ray, J., Kennedy, C.A., Lefantzi, S., Najm, H.N.: Using high-order methods on adaptively refined block-structured meshes - derivatives, interpolations, and filters. SIAM J. Sci. Comp. 29, 139–181 (2007)

    Article  MATH  MathSciNet  Google Scholar 

  73. Ray, J., Najm, H.N., Milne, R.B., Devine, K.D., Kempka, S.: Triple flame structure and dynamics at the stabilization point of an unsteady lifted jet diffusion flame. Proc. Combust. Inst. 28, 219–226 (2000)

    Article  Google Scholar 

  74. Safta, C.: (2009). Personal Communication

    Google Scholar 

  75. Safta, C., Ray, J., Najm, H.: A high-order projection scheme for AMR computations of chemically reacting flows. In: Proceedings of the 2009 Fall Meeting of the Western States Section of the Combustion Institute, Irvine, CA (2009)

    Google Scholar 

  76. Sommeijer, B.P., Shampine, L.F., Verwer, J.G.: RKC: An explicit solver for parabolic PDEs. J. Comp. Appl. Math. 88, 315–326 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  77. de St. Germain, J.D., McCorquodale, J., Parker, S.G., Johnson, C.R.: UINTAH: A massively parallel problem solving environment. In: HPDC ’00: Ninth IEEE International Symposium on High Performance and Distributed Computing (2000)

    Google Scholar 

  78. van Straalen, B., Shalf, J., Ligocki, T., Keen, N., Yang, W.S.: Scalability challenges for massively parallel AMR applications. In: Proceedings of the 23rd IEEE International Symposium on Parallel and Distributed Processing (2009)

    Google Scholar 

  79. TAU: Tuning and Analysis Utilities. Available from (accessed November 2009) http://www.cs.uoregon.edu/research/paracomp/tau/

  80. The OpenFOAM Homepage. Available from (accessed October 2009) http://www.opencfd.co.uk/openfoam/

  81. Tonse, S., Moriarty, N., Brown, N., Frenklach, M.: PRISM: Piecewise reusable implementation of solution mapping. An economical strategy for chemical kinetics. Israel J. Chem. 39, 97–106 (1999)

    Google Scholar 

  82. Trebon, N., Morris, A., Ray, J., Shende, S., Malony, A.D.: Performance modeling using component assemblies. Concurr. Comp.-Pract. E. 19, 685–696 (2007)

    Article  Google Scholar 

  83. Valorani, M., Goussis, D.: Explicit time-scale splitting algorithm for stiff problems: Auto-ignition of gaseous-mixtures behind a steady shock. J. Comput. Phys. 169, 44–79 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  84. Verwer, J.G., Sommeijer, B.P., Hundsdorfer, W.: RKC time-stepping for advection-diffusion-reaction problems. J. Comput. Phys. 201, 61–79 (2004)

    Article  MATH  MathSciNet  Google Scholar 

  85. Visual Basic Webpage. Available from (accessed October 2009) http://msdn.microsoft.com/en-us/vbasic/default.aspx

  86. Williams, F.: Combustion Theory, 2nd edn. Addison-Wesley, New York (1985)

    Google Scholar 

  87. XCAT Homepage. Available from (accessed October 2009) http://www.extreme.indiana.edu/xcat/

  88. Yetter, R., Dryer, F., Rabitz, H.: A comprehensive reaction mechanism for carbon monoxide/hydrogen/oxygen kinetics. Combust. Sci. Technol. 79, 97–128 (1991)

    Article  Google Scholar 

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  1. Sandia National Laboratories, Livermore, CA, USA

    J. Ray

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  1. J. Ray
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  2. R. Armstrong
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  3. C. Safta
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  1. Dept. Mechanical & Aerospace Engineering, North Carlolina State University, Stinson Drive 2601, Raleigh, 27695, North Carolina, USA

    Tarek Echekki

  2. Department of Engineering, University of Cambridge, Cambridge, CB2 1PZ, United Kingdom

    Epaminondas Mastorakos

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Ray, J., Armstrong, R., Safta, C., Debusschere, B.J., Allan, B.A., Najm, H.N. (2011). Computational Frameworks for Advanced Combustion Simulations. In: Echekki, T., Mastorakos, E. (eds) Turbulent Combustion Modeling. Fluid Mechanics and Its Applications, vol 95. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0412-1_17

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