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Efficient simulations of large-scale convective heat transfer problems

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Języki publikacji
EN
Abstrakty
EN
We describe an approach for efficient solution of large-scale convective heat transfer problems that are formulated as coupled unsteady heat conduction and incompressible fluid-flow equations. The original problem is discretized over time using classical implicit methods, while stabilized finite elements are used for space discretization. The algorithm employed for the discretization of the fluid-flow problem uses Picard’s iterations to solve the arising nonlinear equations. Both problems (the heat transfer and Navier–Stokes equations) give rise to large sparse systems of linear equations. The systems are solved by using an iterative GMRES solver with suitable preconditioning. For the incompressible flow equations, we employ a special preconditioner that is based on an algebraic multigrid (AMG) technique. This paper presents algorithmic and implementation details of the solution procedure, which is suitably tuned – especially for ill-conditioned systems that arise from discretizations of incompressible Navier–Stokes equations. We describe a parallel implementation of the solver using MPI and elements from the PETSC library. The scalability of the solver is favorably compared with other methods, such as direct solvers and the standard GMRES method with ILU preconditioning.
Wydawca
Czasopismo
Rocznik
Tom
Strony
517--538
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
autor
  • AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Krakow, Poland
  • AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Krakow, Poland
  • AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Krakow, Poland
  • AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Krakow, Poland
Bibliografia
  • [1] Balay S., Gropp W.D., McInnes L.C., Smith B.F.: Efficient Management of Parallelism in Object-Oriented Numerical Software Libraries. In: E. Arge, A.M. Bruaset, H.P. Langtangen (eds.), Modern Software Tools in Scientific Computing, pp. 163–202, Birkh¨auser Press, 1997.
  • [2] Banaś K.: A Modular Design for Parallel Adaptive Finite Element Computational Kernels. In: M. Bubak, G. van Albada, P. Sloot, J. Dongarra (eds.), Computational Science – ICCS 2004, 4th International Conference, Proceedings, Part II, Lecture Notes in Computer Science, vol. 3037, pp. 155–162, Springer, 2004.
  • [3] Banaś K.: Scalability Analysis for a Multigrid Linear Equations Solver. In: R. Wyrzykowski, J. Dongarra, K. Karczewski, J. Wasniewski, (eds.), Parallel Processing and Applied Mathematics, Proceedings of VIIth International Conference, PPAM 2007, Gdansk, Poland, 2007, Lecture Notes in Computer Science, vol. 4967, pp. 1265–1274. Springer, 2008.
  • [4] Banaś K., Chłoń K., Cybulka P., Michalik K., P laszewski P., Siwek A.: Adaptive Finite Element Modelling of Welding Processes. In: M. Bubak, J. Kitowski, K. Wiatr (eds.), eScience on Distributed Computing Infrastructure – Achievements of PLGrid Plus Domain-Specific Services and Tools, Lecture Notes in Computer Science, vol. 8500, pp. 391–406. Springer, 2014. doi: 10.1007/978-3- 319-10894-0 28.
  • [5] Banaś K., Demkowicz L.: Entropy Controlled Adaptive Finite Element Simulations for Compressible Gas Flow, Journal of Computational Physics, vol. 126, pp. 181–201, 1996.
  • [6] Brandt A.: Multi-Level Adaptive Solutions to Boundary-Value Problems, Mathematics of Computation, vol. 31(138), pp. 333–390, 1977. doi: 10.2307/2006422.
  • [7] Brooks A.N., Hughes T.J.R.: Streamline upwind/Petrov-Galerkin formulations for convection dominated flows with the particular emphasis on the incompressible Navier–Stokes equations, Computer Methods in Applied Mechanics and Engineering, vol. 32(1–3), pp. 199–259, 1982.
  • [8] Cai X., Sarkis M.: A Restricted Additive Schwarz Preconditioner for General Sparse Linear Systems, SIAM Journal on Scientific Computing, vol. 21, pp. 792–797, 1999.
  • [9] Calo V.M., Collier N.O., Pardo D., Paszynski M.R.: Computational complexity and memory usage for multi-frontal direct solvers used in p finite element analysis, Procedia Computer Science, vol. 4, pp. 1854–1861, 2011.
  • [10] Chow E., Falgout R.D., Hu J.J., Tuminaro R.S., Yang U.M.: A Survey of Parallelization Techniques for Multigrid Solvers. In: M.A. Heroux, P. Raghavan and H.D. Simon (eds.), Parallel Processing for Scientific Computing chap. 10,pp. 179–201, SIAM, 2006. doi: 10.1137/1.9780898718133.ch10.
  • [11] Cyr E.C., Shadid J.N., Tuminaro R.S.: Stabilization and scalable block preconditioning for the Navier–Stokes equations, Journal of Computational Physics, vol. 231(2), pp. 345–363, 2012. doi: 10.1016/j.jcp.2011.09.001.
  • [12] Diekert V., Rozenberg G. (eds.): The Book of Traces, World Scientific, 1995. doi: 10.1142/2563.
  • [13] Elman H., Howle V.E., Shadid J., Shuttleworth R., Tuminaro R.: A taxonomy and comparison of parallel block multi-level preconditioners for the incompressible Navier–Stokes equations, Journal of Computational Physics, vol. 227(3), pp. 1790–1808, 2008. doi: 10.1016/j.jcp.2007.09.026.
  • [14] Franca L.P., Frey S.L.: Stabilized finite element methods: II. The incompressible Navier–Stokes equations, Computer Methods in Applied Mechanics and Engineering, vol. 99(2–3), pp. 209–233, 1992. doi: 10.1016/0045-7825(92)90041-H.
  • [15] Franca L.P., Frey S.L., Hughes T.J.R.: Stabilized finite element methods: I. Application to the advective-diffusive model, Computer Methods in Applied Mechanics and Engineering, vol. 95(2), pp. 253–276, 1992. doi: 10.1016/0045-7825(92)90143-8
  • [16] Goik D., Banaś K.: A Block Preconditioner for Scalable Large Scale Finite Element Incompressible Flow Simulations. In: V.V. Krzhizhanovskaya, G. Z´avodszky, M.H. Lees, J.J. Dongarra, P.M.A. Sloot, S. Brissos, J. Teixeira (eds.), Computational Science – ICCS 2020. ICCS 2020, Lecture Notes in Computer Science, vol. 12139, pp. 199–211. Springer, Cham, 2020. doi: : 10.1007/978-3-030-50420-5 15.
  • [17] Henson van E., Yang U.M.: BoomerAMG: A parallel algebraic multigrid solver and preconditioner, Applied Numerical Mathematics, vol. 41(1), pp. 155–177, 2002. doi: 10.1016/S0168-9274(01)00115-5.
  • [18] Jurczyk T., Glut B., Kitowski J.: An Empirical Comparison of Decomposition Algorithms for Complex Finite Element Meshes. In: PPAM ’01: Proceedings of the 4th International Conference on Parallel Processing and Applied Mathematics – Revised Papers, pp. 493–501, Springer-Verlag, Berlin, Heidelberg, 2001.
  • [19] McCormick S.F. (ed.): Multigrid Methods. Frontiers in Applied Mathematics, Society for Industrial and Applied Mathematics, Philadelphia, PA, 1987.
  • [20] Michalik K., Banaś K., Płaszewski P., Cybulka P.: Modular FEM framework “ModFEM” for generic scientific parallel simulations, Computer Science, vol. 14(3), pp. 513–528, 2013. doi: 10.7494/csci.2013.14.3.513.
  • [21] Paszyński M., Pardo D., Paszy´nska A., Demkowicz L.F.: Out-of-core multifrontal solver for multi-physics hp adaptive problems, Procedia Computer Science, vol. 4, pp. 1788–1797, 2011.
  • [22] Patankar S.V.: Numerical Heat Transfer and Fluid Flow. Series on Computational Methods in Mechanics and Thermal Science, Hemisphere Publishing Corporation, 1980.
  • [23] Rehman ur M., Vuik C., Segal G.: A comparison of preconditioners for incompressible Navier–Stokes solvers, International Journal for Numerical Methods in Fluids, vol. 57(12), pp. 1731–1751, 2008. doi: 10.1002/fld.1684.
  • [24] Saad Y.: Iterative methods for sparse linear systems, PWS Publishing, Boston, 1996
  • [25] Saad Y., Schultz M.H.: GMRES: A Generalized Minimal Residual Algorithm for Solving Nonsymmetric Linear Systems, SIAM Journal on Scientific and Statistical Computing, vol. 7(3), pp. 856–869, 1986. doi: 10.1137/0907058.
  • [26] Schloegel K., Karypis G., Kumar V.: Graph partitioning for high performance scientific simulations. In: J. Dongarra, I. Foster, G. Fox, W. Gropp, K. Kennedy, L. Torczon, A. White, (eds.), Sourcebook of Parallel Computing, Morgan Kaufmann Publishers Inc., San Francisco, 2002.
  • [27] Smith B., Bjorstad P., Gropp W.: Domain Decomposition. Parallel Multilevel Methods for Elliptic Partial Differential Equation, Cambridge University Press, Cambridge, 1996.
  • [28] Stuben K.: A review of algebraic multigrid, Journal of Computational and Applied Mathematics, vol. 128(1–2), pp. 281–309, 2001. doi: 10.1016/S0377-0427(00)00516-1.
  • [29] Volker J.: Finite Element Methods for Incompressible Flow Problems, Springer Series in Computational Mathematics, vol. 51, Springer, Cham, 2016.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4b6b506e-1b7f-48ff-967f-c75ce32feb29
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