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Parallel Algorithms and Software for Nuclear, Energy, and Environmental Applications. Part II: Multiphysics Software

Published online by Cambridge University Press:  20 August 2015

Derek Gaston ,
Luanjing Guo ,
Glen Hansen ,
Hai Huang ,
Richard Johnson ,
Dana Knoll ,
Chris Newman ,
Hyeong Kae Park ,
Robert Podgorney  and
Michael Tonks
...Show all authors
Derek Gaston*
Affiliation:
Nuclear Science and Technology, Idaho National Laboratory, Idaho Falls, ID 83415, USA
Luanjing Guo*
Affiliation:
Energy and Environment Science and Technology, Idaho National Laboratory, Idaho Falls, ID 83415, USA
Glen Hansen*
Affiliation:
Multiphysics Simulation Technologies Dept. (1444), Sandia National Laboratories, Albuquerque, NM 87185, USA
Hai Huang*
Affiliation:
Energy and Environment Science and Technology, Idaho National Laboratory, Idaho Falls, ID 83415, USA
Richard Johnson*
Affiliation:
Nuclear Science and Technology, Idaho National Laboratory, Idaho Falls, ID 83415, USA
Dana Knoll*
Affiliation:
Fluid Dynamics and Solid Mechanics Group (T-3), Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Chris Newman*
Affiliation:
Fluid Dynamics and Solid Mechanics Group (T-3), Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Hyeong Kae Park*
Affiliation:
Fluid Dynamics and Solid Mechanics Group (T-3), Los Alamos National Laboratory, Los Alamos, NM 87545, USA
Robert Podgorney*
Affiliation:
Energy and Environment Science and Technology, Idaho National Laboratory, Idaho Falls, ID 83415, USA
Michael Tonks*
Affiliation:
Nuclear Science and Technology, Idaho National Laboratory, Idaho Falls, ID 83415, USA
Richard Williamson*
Affiliation:
Nuclear Science and Technology, Idaho National Laboratory, Idaho Falls, ID 83415, USA
*
Email:Derek.Gaston@inl.gov
Email:Luanjing.Guo@inl.gov
Corresponding author.Email:gahanse@sandia.gov
Email:Hai.Huang@inl.gov
Email:Rich.Johnson@inl.gov
Email:nol@lanl.gov
Email:cnewman@lanl.gov
Email:hkpark@lanl.gov
Email:Robert.Podgorney@inl.gov
Email:Michael.Tonks@inl.gov
Email:Richard.Williamson@inl.gov
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Abstract

This paper is the second part of a two part sequence on multiphysics algorithms and software. The first [1] focused on the algorithms; this part treats the multiphysics software framework and applications based on it. Tight coupling is typically designed into the analysis application at inception, as such an application is strongly tied to a composite nonlinear solver that arrives at the final solution by treating all equations simultaneously. The application must also take care to minimize both time and space error between the physics, particularly if more than one mesh representation is needed in the solution process. This paper presents an application framework that was specifically designed to support tightly coupled multiphysics analysis. The Multiphysics Object Oriented Simulation Environment (MOOSE) is based on the Jacobian-free Newton-Krylov (JFNK) method combined with physics-based preconditioning to provide the underlying mathematical structure for applications. The report concludes with the presentation of a host of nuclear, energy and environmental applications that demonstrate the efficacy of the approach and the utility of a well-designed multiphysics framework.

Keywords

65M1265M6065Y0565Z0565H10Multiphysics simulationJacobian-free Newton Krylovfinite element applicationsphysics-based preconditioning

Information

Type
Research Article
Information
Communications in Computational Physics , Volume 12 , Issue 3 , September 2012 , pp. 834 - 865
Copyright
Copyright © Global Science Press Limited 2012

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References

[1]Gaston, D., Guo, L., Hansen, G., Huang, H., Johnson, R., Knoll, D., Newman, C., Park, H., Pod-gorney, R., Tonks, M., Williamson, R., Parallel algorithms and software for nuclear, energy, and environmental applications. Part I: Multiphysics algorithms, Commun. Comput. Phys. 12 (2012) 807–833.Google Scholar
[2]Gaston, D., Newman, C., Hansen, G., Lebrun-Grandié, D., MOOSE: A parallel computational framework for coupled systems of nonlinear equations, Nucl. Engrg. Design 239 (2009) 1768–1778.CrossRefGoogle Scholar
[3]Newman, C., Hansen, G., Gaston, D., Three dimensional coupled simulation of thermome-chanics, heat, and oxygen diffusion in UO2 nuclear fuel rods, Journal of Nuclear Materials 392 (2009) 6–15.Google Scholar
[4]Park, H., Knoll, D. A., Gaston, D. R., Martineau, R. C., Tightly coupled multiphysics algorithms for pebble bed reactors, Nuclear Science and Engineering 166 (2) (2010) 118–133.CrossRefGoogle Scholar
[5]Kirk, B. S., Peterson, J. W., Stogner, R. H., Carey, G. F., libMesh: a C₊₊ library for parallel adaptive mesh refinement⁄coarsening simulations, Eng Comput-Germany 22 (3-4) (2006) 237–254.Google Scholar
[6]Balay, S., Gropp, W. D., McInnes, L. C., Smith, B. F., Efficient management of parallelism in object oriented numerical software libraries, in: Arge, E., Bruaset, A. M., Langtangen, H. P. (Eds.), Modern Software Tools in Scientific Computing, Birkhäuser Press, 1997, pp. 163–202.Google Scholar
[7]Heroux, M., et al., Trilinos: an object-oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific problems, http://trilinos.sandia.gov (2008).Google Scholar
[8]Falgout, R. D., Yang, U. M., HYPRE: A library of high performance preconditioners, in: International Conference on Computational Science (3), 2002, pp. 632–641.Google Scholar
[9]Braess, D., Finite Elements: Theory, Fast Solvers, and Applications in Solid Mechanics, Cambridge University Press, Cambridge, 2001.Google Scholar
[10]Brenner, S. C., Scott, L. R., The Mathematical Theory of Finite Element Methods, Springer, New York, Berlin, Heidelberg, 2002.Google Scholar
[11]Ascher, U. M., Petzold, L. R., Computer Methods for Ordinary Differential Equations and Differential–Algebraic Equations, SIAM, Philadelphia, PA, 1998.Google Scholar
[12]Babuška, I., Suri, M., The p and h-p versions of the finite element method, basic principles and properties, SIAM Rev. 36 (1994) 578–632.Google Scholar
[13]Carey, G. F., Computational Grids: Generation, Adaptation, and Solution Strategies, Taylor & Francis, Washington, DC, 1997.Google Scholar
[14]Kelly, D. W., De SR Gago, J. P., Zienkiewicz, O. C., Babuska, I., A posteriori error analysis and adaptive processes in the finite element method: Part I-error analysis, Internat. J. Numer. Methods Engrg. 19 (11).Google Scholar
[15]Ainsworth, M., Oden, J. T., A Posteriori Error Estimation in Finite Element Analysis, Wiley Interscience, 2000.Google Scholar
[16]Fink, J. K., Thermophysical properties of uranium dioxide, J. Nucl. Materials 279 (1) (2000) 1–18.Google Scholar
[17]Lucuta, P. G., Matzke, H. J., Hastings, I. J., A pragmatic approach to modelling thermal conductivity of irradiated UO2 fuel: review and recommendations, Journal of Nuclear Materials 232 (1996) 166–180.CrossRefGoogle Scholar
[18]Miller, G. K., Petti, D. A., Maki, J. T., Knudsen, D. L., PARFUME theory and model basis report, Tech. Rep. INL/EXT-08-14497, Idaho National Laboratory (2009).Google Scholar
[19]Allison, C. M., et al., SCDAP/RELAP5/MOD3.1 code manual volume IV: MATPRO, Tech. Rep. NUREG/CR-6150, Idaho National Laboratory (1993).Google Scholar
[20]Rashid, Y., Dunham, R., Montgomery, R., Fuel analysis and licensing code: FALCON MOD01, Tech. Rep. EPRI 1011308, Electric Power Research Institute (Dec. 2004).Google Scholar
[21]Forsberg, K., Massih, A. R., Diffusion theory of fission gas migration in irradiated nuclear fuel UO2, Journal of Nuclear Materials 135 (2-3) (1985) 140–148.CrossRefGoogle Scholar
[22]Denis, A., Piotrkowski, R., Simulation of isothermal fission gas release, Journal of Nuclear Materials 229 (1996) 149–154.CrossRefGoogle Scholar
[23]Hansen, G., Martineau, R., Newman, C., Gaston, D., Framework for simulation of pellet cladding thermal interaction (PCTI) for fuel performance calculations, in: American Nuclear Society 2009 International Conference on Advances in Mathematics, Computational Methods, and Reactor Physics, Saratoga Springs, NY, 2009.Google Scholar
[24]Hansen, G., A Jacobian-free Newton Krylov method for mortar-discretized thermomechani-cal contact problems, J. Comput. Phys. 230 (2011) 6546–6562.CrossRefGoogle Scholar
[25]Williamson, R. L., Newman, C. K., Simulation of TRISO fuel using the BISON fuel performance code: Initial feasibility study, Tech. Rep. INL/INT-09-17415, Idaho National Laboratory (Dec. 2009).Google Scholar
[26]Allison, C. M., Berna, G. A., Chambers, R., Coryell, E. W., Davis, K. L., Hagrman, D. L., Hagrman, D. T., Hampton, N. L., Hohorst, J. K., Mason, R. E., McComas, M. L., McNeil, K. A., Miller, R. L., Olsen, C. S., Reymann, G. A., Siefken, L. J., SCDAP/RELAP5/MOD3.1 code manual, volume IV: MATPRO–A library of materials properties for light-water-reactor accident analysis, Tech. rep., NUREG/CR-6150, EGG-2720 (1993).Google Scholar
[27]Tikare, V., Holm, E. A., Simulation of grain growth and pore migration in a thermal gradient, J. Am. Ceram. Soc. 81 (3) (1998) 480–4.CrossRefGoogle Scholar
[28]Oh, J. Y., Koo, Y. H., Lee, B. H., Simulation of high burnup structure in UO2 using Potts model, Nucl. Eng. Technol. 41 (8) (2009) 1109–14.Google Scholar
[29]Rokkam, S. K., El-Azab, A., Millett, P. C., Wolf, D., Phase field modeling of void nucleation and growth in irradiated metals, Modelling Simul. Mater. Sci. Eng. 17 (2009) 064002.Google Scholar
[30]Millett, P. C., Wolf, D., Desai, T. D., Rokkam, S., El-Azab, A., Phase-field simulation of thermal conductivity in porous polycrystalline microstructres, Journal of Applied Physics 104 (2008) 033512.Google Scholar
[31]Tonks, M., Gaston, D., Permann, C., Millett, P., Hansen, G., Wolf, D., A coupling methodology for mesoscale-informed nuclear fuel performance codes, Nucl. Engrg. Design 240 (10) (2010) 2877–2883.Google Scholar
[32]Sens, P. F., The kinetics of pore movement in UO2 fuel rods, Journal of Nuclear Materials 43 (3) (1972) 293–307.Google Scholar
[33] KTA rule 3102.1, Reactor core design for high-temperature gas-cooled reactor Part 1: Calculation of the material properties of helium (1978).Google Scholar
[34] KTA rule 3102.2, Reactor core design for high-temperature gas-cooled reactor Part 2: Heat transfer in spherical fuel elements (1983).Google Scholar
[35] KTA rule 3102.3, Reactor core design of high-temperature gas-cooled reactors Part 3: Loss of pressure through friction in pebble bed cores (1981).Google Scholar
[36] IAEA, Heat transport and afterheat removal for gas cooled reactors under accident conditions, Tech. Rep. IAEA-TECDOC-1163, IAEA (2000).Google Scholar
[37]Reitsma, F., Ivanov, K., Downar, T., H. de Hass, Sen, S., Strydom, G., Mphahlele, R., Ty-obeka, B., Seker, V., Gougar, H., Lee, H., PBMR coupled neutronics/thermal hydraulics transient benchmark the PBMR-400 core design, Tech. Rep. NEA/NSC/DOC(2007) Draft-V07, OECD/NEA/NSC (2007).Google Scholar
[38]Strydom, G., Reitsma, F., Ngeleka, P. T., Ivanov, K. N., The OECD/NEA/NSC PBMR 400MW coupled neutronics thermal hydraulics transient benchmark: transient results, PHYSOR2010, 2010.Google Scholar
[39] B.Boer, Lathouwers, D., Kloosterman, J.L., T.H. J. J. van der Hagen, Strydom, G., Validation of the DALTON-THERMIX code system with transient analyses of the HTR-10 and application to the PBMR, Nuclear Technology 170 (2010) 306–321.Google Scholar
[40]Rutqvist, J., Wu, Y. S., Tsang, C. F., Bodvarsson, G., A modeling approach for analysis of coupled multiphase fluid flow, heat transfer, and deformation in fractured porous rock, Internat. J. Rock Mech. and Mining Sci. 39 (4) (2002) 429–442.Google Scholar
[41]Pruess, K., Oldenberg, K., Moridis, G., TOUGH2 user’s guide, version 2.0, Tech. Rep. LBNL-43134, Berkeley National Laboratory, Berkeley, California (1999).Google Scholar
[42] FLAC 3D, fast Lagrangian analysis of continua in 3 dimensions. version 2.0., Tech. rep., ITASCA Consulting Group (1997).Google Scholar
[43]Brownell, D. H., Garg, S. K., Pritchett, J. W., Governing equations for geothermal reservoirs, Water Resour. Res. 13 (6) (1977) 929–934.Google Scholar
[44]Faust, C. R., Mercer, J. W., Geothermal reservoir simulation. 2. numerical-solution techniques for liquid-dominated and vapot-dominated hydrothermal system, Water Resour. Res. 15 (1) (1979) 31–46.Google Scholar
[45]Faust, C. R., Mercer, J. W., Geothermal reservoir simulation. 1. mathematical-models for liquid-dominated and vapor-dominated hydrothermal systems, Water Resour. Res. 15 (1) (1979) 23–30.Google Scholar
[46]Jaeger, J. C., Cook, N. G. W., Zimmerman, R. W., Fundamentals of Rock Mechanics, 4th ed., 2007.Google Scholar
[47]Garg, S., Kassoy, D., Convective heat and mass transfer in hydrothermal systems, Geothermal Systems: Principles and Case Histories.Google Scholar
[48a]Graf, T., Simulation of geothermal flow in deep sedimentary basins in Alberta., Tech. Rep. Openb File Report 2009-11, ERCB/AGC (2009).Google Scholar
[49]Elder, J. W., Transient convection in a porous medium, J. Fluid Mech. 27 (Part 3) (1967) 609–&.Google Scholar
[50]Oldenburg, C. M., Pruess, K., Dispersive transport dynamics in a strongly coupled groundwater-brine flow system, Water Resour. Res. 31 (2) (1995) 289–302.CrossRefGoogle Scholar
[51]Frolkovic, P., DeSchepper, H., Numerical modelling of convection dominated transport coupled with density driven flow in porous media, Adv. in Water Res. 24 (1) (2000) 63–72.Google Scholar
[52]Yeh, G. T., Tripathi, V. S., A critical evaluation of recent developments in hydrogeochemical transport models of reactive multichemical components, Water Resour. Res. 25 (1989) 93–108.Google Scholar
[53]Steefel, C. I., MacQuarrie, K. T. B., Approaches to modeling of reactive transport in porous media, in: Lichtner, P. C., Steefel, C. I., Oelkers, E. H. (Eds.), Reactive Transport in Porous Media, Vol. 34, Review in Mineralogy, 1996, pp. 83–125.Google Scholar
[54]Xu, T., Sonnenthal, E. L., Spycher, N., Pruess, K., TOUGHREACT user’s guide: A simulation program for non-isothermal multiphase reactive geochemical transport in variable saturated geologic media, Tech. Rep. LBNL-55460, Berkeley National Laboratory, Berkeley, California (2004).Google Scholar
[55]White, M. D., Oostrom, M., STOMP (Subsurface Transport over Multiple Phases) version 2.0: Theory guide, Tech. Rep. PNNL-12030, Pacific Northwest National Laboratory, Richland, Washington (2000).Google Scholar
[56]White, M. D., McGrail, B. P., STOMP (Subsurface Transport over Multiple Phases) version 1.0 addendum: Eckechem equilibrium-conservation-kinetic equation chemistry and reactive transport, Tech. Rep. PNNL-15482, Pacific Northwest National Laboratory, Richland, Washington (2005).Google Scholar
[57]Zheng, C., Wang, P. P., MT3DMS: A modular three-dimensional multispecies transport model for simulation of advection, dispersion, and chemical reactions of contaminants in ground-water systems; documentation and user’s guide, Tech. Rep. SERDP-99-1, U. S. Army Corps of Engineers, Washington, D. C. (1999).Google Scholar
[58]Xu, T., Gerard, F., Pruess, K., Brimhall, G., Modeling non-isothermal multiphase multi-species reactive chemical transport in geologic media, Tech. Rep. LBNL-40504, Ernest Orlando Lawrence Berkeley National Laboratory (1997).Google Scholar
[59]Li, L., Steefel, C. I., Yang, L., Scale dependence of mineral dissolution rates within single pores and fractures, Geochimica Et Cosmochimica Acta 72 (2) (2008) 360–377.Google Scholar
[60]Warren, L. A., Maurice, P. A., Parmar, N., Ferris, F. G., Microbially mediated calcium carbonate precipitation: Implications for interpreting calcite precipitation and for solid-phase capture of inorganic contaminants, Geomicrobiol. J. 18 (2001) 93–115.Google Scholar
[61]Fujita, Y., Redden, G. D., Ingram, J. C., Cortez, M. M., Ferris, F. G., Smith, R. W., Strontium incorporation into calcite generated by bacterial ureolysis, Geochemica et Cosmochimica Acta 68 (15) (2004) 3261–3270.Google Scholar
[62]Fujita, Y., Taylor, J. L., Gresham, T. L., Delwiche, M. E., Colwell, F. S., McLing, T. L., Petzke, L. M., Smith, R. W., Stimulation of microbial urea hydrolysis in groundwater to enhance calcite precipitation, Environmental Science & Technology.Google Scholar
[63]Lasaga, A. C., Kinetic Theory in the Earth Sciences, Princeton Univ. Press, Princeton, N. J., 1998.Google Scholar
[64]Fialeo, M., Lavecchia, R., Kinetic study of enzymatic urea hydrolysis in the pH range 4-9, Chemical Biochemical Engineering Quarterly 17 (4) (2003) 305–318.Google Scholar
[65]Wolery, T. J., EQ3⁄6, A software package for geochemical modeling of aqueous systems: Package overview and installation guide (version 7.0), Tech. Rep. UCRL-MA-110662 PT I, Lawrence Livermore National Laboratory (1992).Google Scholar
[66]Yabusaki, S. B., Fang, Y., Waichler, S. R., Building conceptual models of field-scale uranium reactive transport in A dynamic vadose zone-aquifer-river system, Water Resour. Res. 44 (W12403).Google Scholar
[67]Bader, B. W., Pawlowski, R. P., Kolda, T. G., Robust large-scale parallel nonlinear solvers for simulations, Tech. Rep. SAND2005-6865, Sandia National Laboratories (2005).Google Scholar
[68]Fichtl, E.D., Warsa, J. S., Densmore, J. D., The Newton-Krylov method appliedto negative-flux fixup in SN transport calculations, Nuclear Science and Engineering 165 (3) (2010) 331–341.Google Scholar
[69]Park, H., Nourgaliev, R., Knoll, D., Jacobian-Free Newton-Krylov Discontinuous Galerkin (JFNK-DG) method and its physics-based preconditioning for all-speed flows, in: Bulletin of the American Physical Society, 60th Annual Meeting of the Division of Fluid Dynamics, Vol. 52, American Physical Society, 2007, abstract: GB.00004, http://meetings.aps.org/link/BAPS.2007.DFD.GB.4.Google Scholar