Multi-physics; Software Coupling Technology; High Performance Computing
Résumé :
[en] Multi-physics simulation approaches by coupling various software modules is paramount to unveil the underlying physics and thus leads to an improved design of equipment and a more efficient operation. These simulations are in general to be carried out on small to massively parallelised computers for which highly efficient partitioning techniques are required. An innovative partitioning technology is presented that relies on a co-located partitioning of overlapping simulation domains meaning that the overlapping areas of each simulation domain are located at one node. Thus, communication between modules is significantly reduced as compared to an allocation of overlapping simulation domains on different nodes. A co-located partitioning reduces both memory and inter-process communication.
Centre de recherche :
LuXDEM - University of Luxembourg: Luxembourg XDEM Research Centre
Disciplines :
Sciences informatiques
Auteur, co-auteur :
PETERS, Bernhard ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
BESSERON, Xavier ; University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE)
Peyraut, Alice
Mehl, Miriam; University of Stuttgart > Institute for Parallel and Distributed Systems
Ueckermann, Benjamin; University of Stuttgart > Institute for Parallel and Distributed Systems
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
An Innovative Partitioning Technology for Coupled Software Modules
Date de publication/diffusion :
juillet 2022
Nom de la manifestation :
12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2022)
Lieu de la manifestation :
Lisbon, Portugal
Date de la manifestation :
July 14-16, 2022
Manifestation à portée :
International
Titre de l'ouvrage principal :
Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH
Enhanced multiphysics interface research engine. https://github.com/DrStS/EMPIRE-Core. Accessed: 2019-03-14.
RCPE/AVL/CATRA: New Software for the Pharmaceutical Industry. https://www.avl.com/-/rcpe-avl-catra-newsoftware-for-the-pharmaceutical-industry. Accessed: 2022-01-11.
Arndt, D., Bangerth, W., Davydov, D., Heister, T., Heltai, L., Kronbichler, M., Maier, M., Pelteret, J.-P., Turcksin, B., and Wells, D. (2021). The deal.ii finite element library: Design, features, and insights. Computers & Mathematics with Applications, 81:407–422. Development and Application of Open-source Software for Problems with Numerical PDEs.
Arya, N. (2020). Volume coupling using preCICE for an aeroacoustic simulation. preCICE Workshop 2020. https://www.youtube.com/watch?v=TrZD9SnG2Ts.
Balachandar, S. and Eaton, J. K. (2010). Turbulent dispersed multiphase flow. Annu. Rev. Fluid Mech., 42:111 – 133.
Belcourt, N., Bartlett, R. A., Pawlowski, R., Schmidt, R., and Hooper, R. (2011). A theory manual for multiphysics code coupling in LIME. Sandia Nationanal Laboratories.
Belytschko, T. and Xiao, S. P. (2003). Coupling methods for continuum model with molecular model. International Journal for Multiscale Computational Engineering, 1(1).
Bensoussan, A., Lions, J., and Papanicolaou, G. (1978). Asymptotic Analysis for Periodic Structures. Studies in mathematics and its applications. North-Holland Publishing Company.
Besseron, X., Rousset, A., Peyraut, A., and Peters, B. (2020). 6-way coupling of DEM+CFD+FEM with preCICE. preCICE Workshop 2020. https://www.youtube.com/watch?v=3FP8y1Zjqns.
Blochwitz, T. (2014). Functional mock-up interface for model exchange and co-simulation.
Boulet, L., Bénard, P., Lartigue, G., Moureau, V., Didorally, S., Chauvet, N., and Duchaine, F. (2018). Modeling of conjugate heat transfer in a kerosene/air spray flame used for aeronautical fire resistance tests. Flow, Turbulence and Combustion, 101(2):579–602.
Buis, S., Piacentini, A., and Declat, D. (2006). Palm: A computational framework for assembling highperformance computing applications. Concurrency and Computation: Practice and Experience, 18(2):231–245.
Bungartz, H.-J., Lindner, F., Gatzhammer, B., Mehl, M., Scheufele, K., Shukaev, A., and Uekermann, B. (2016). precice – a fully parallel library for multiphysics surface coupling. Computers & Fluids, 141:250–258. Advances in Fluid-Structure Interaction.
Capecelatro, J. and Desjardins, O. (2013). An euler–lagrange strategy for simulating particle-laden flows. Journal of Computational Physics, 238:1–31.
de Laborderie, J., Duchaine, F., Gicquel, L., Vermorel, O., Wang, G., and Moreau, S. (2018). Numerical analysis of a high-order unstructured overset grid method for compressible les of turbomachinery. Journal of Computational Physics, 363:371 – 398.
Deb, S. and Tafti, D. K. (2013). A novel two-grid formulation for fluid–particle systems using the discrete element method. Powder Technology, 246:601–616.
Farzaneh, M., Sasic, S., Almstedt, A.-E., Johnsson, F., and Pallarès, D. (2011). A novel multigrid technique for lagrangian modeling of fuel mixing in fluidized beds. Chemical Engineering Science, 66(22):5628–5637.
Fish, J. (2009). Multiscale Methods: Bridging the Scales in Science and Engineering. Oxford University Press, Inc., New York, NY, USA.
Fish, J., Nuggehally, M. A., Shephard, M. S., Picu, C. R., Badia, S., Parks, M. L., and Gunzburger, M. (2007). Concurrent AtC coupling based on a blend of the continuum stress and the atomistic force. Computer Methods in Applied Mechanics and Engineering, (45–48).
Foundation, T. O. Openfoam v6 user guide. https://cfd.direct/openfoam/user-guide. Accessed: 2019-03-14.
Gaston, D., Newman, C., Hansen, G., and Lebrun-Grandié, D. (2009). Moose: A parallel computational framework for coupled systems of nonlinear equations. Nuclear Engineering and Design, 239(10):1768 – 1778.
Gatzhammer, B., Mehl, M., and Neckel, T. (2010). A coupling environment for partitioned multiphysics simulations applied to fluid-structure interaction scenarios. Procedia Comput. Sci., 1(1).
Gopalakrishnan, P. and Tafti, D. (2013). Development of parallel dem for the open source code mfix. Powder Technology, 235:33 – 41.
Götz, J., Iglberger, K., Stürmer, M., and Rüde, U. (2010). Direct numerical simulation of particulate flows on 294912 processor cores. In 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis, pages 1–11.
Ingram, G. D. and Cameron, I. T. (2008). Challenges in multiscale modelling and its application to granulation systems.
Joppich, W. and Kürschner, M. (2006). MpCCI—a tool for the simulation of coupled applications. Concurrency and computation: Practice and Experience, 18(2):183–192.
Knap, J. and Ortiz, M. (2001). An analysis of the quasicontinuum method. Journal of the Mechanics and Physics of Solids. The JW Hutchinson and JR Rice 60th Anniversary Issue.
Kothe, D. (2012). Consortium for advanced simulation of light water reactors (casl). http://www.casl.gov.
Larson, J., Jacob, R., and Ong, E. (2005). The model coupling toolkit: A new fortran90 toolkit for building multiphysics parallel coupled models. Int’l Jnl of High Perf Comp Applictns, 19(3):277–292.
Li, A., Li, R., and Fish, J. (2008). Generalized mathematical homogenization: From theory to practice. Computer Methods in Appl. Mechanics and Eng., 197(41):3225 – 3248. Recent Adv. in Comput. Study of Nanostructures.
Liu, K., Lakhote, M., and Balachandar, S. (2019). Selfinduced temperature correction for inter-phase heat transfer in euler-lagrange point-particle simulation. Journal of Computational Physics, 396:596–615.
Luo, X., Stylianopoulos, T., Barocas, V. H., and Shephard, M. S. (2009). Multiscale computation for bioartificial soft tissues with complex geometries. Engineering with Computers, 25(1):87–96.
Mehl, M., Uekermann, B., Bijl, H., Blom, D., Gatzhammer, B., and van Zuijlen, A. (2016). Parallel coupling numerics for partitioned fluid–structure interaction simulations. Comp. & Mathematics with Applications.
Miller, R. E. and Tadmor, E. (2002). The quasicontinuum method: Overview, applications and current directions. Journal of Computer-Aided Materials Design, 9(3):203–239.
Peters, B. (2013). The extended discrete element method (xdem) for multi-physics applications. Scholarly Journal of Engineering Research, 2:1–20.
Phuc, P. V., Chiba, S., and Minami, K. (2016). Large scale transient CFD simulations for buildings using OpenFOAM on a world’s top-class supercomputer. In 4th OpenFOAM User Conference 2016.
Piacentini, A., Morel, T., and Thevenin, A. (2011). OPALM: An open source dynamic parallel coupler. In Coupled problems 2011, Kos Island, Greece.
Pozzetti, G., Besseron, X., Rousset, A., and Peters, B. (2018). A co-located partitions strategy for parallel cfd–dem couplings. Advanced Powder Technology, 29(12):3220–3232.
Pozzetti, G., Jasak, H., Besseron, X., Rousset, A., and Peters, B. (2019). A parallel dual-grid multiscale approach to cfd–dem couplings. Journal of Computational Physics, 378:708–722.
Predari, M. (2016). Load Balancing for Parallel Coupled Simulations. Theses, Université de Bordeaux, LaBRI; Inria Bordeaux Sud-Ouest.
Predari, M. and Esnard, A. (2014). Coupling-Aware Graph Partitioning Algorithms: Preliminary Study. In IEEE Int. Conf. on High Performance Computing (HiPC 2014), Goa, India.
Sanchez-Palencia, E. (1980). Non-Homogeneous Media and Vibration Theory. 0075-8450. Springer-Verlag Berlin Heidelberg, 1 edition.
Shunji, K., Satsuki, M., Hiroshi, K., Tomonori, Y., and Shinobu, Y. (2014). A parallel iterative partitioned coupling analysis system for large-scale acoustic fluid– structure interactions. Computational Mechanics, 53(6):1299–1310.
Spogis, N. (2008). Multiphase modeling using EDEM– CFD coupling for FLUENT. CFD OIL.
Sun, R. and Xiao, H. (2015). Diffusion-based coarse graining in hybrid continuum–discrete solvers: Theoretical formulation and a priori tests. International Journal of Multiphase Flow, 77:142–157.
Sun, R. and Xiao, H. (2016). Sedifoam: A general-purpose, open-source CFD–DEM solver for particle-laden flow with emphasis on sediment transport. Computers & Geosciences, 89:207 – 219.
Tadmor, E. B., Ortiz, M., and Phillips, R. (1996). Quasicontinuum analysis of defects in solids. Philos. Mag. A.
Tang, Y.-H., Kudo, S., Bian, X., Li, Z., and Karniadakis, G. E. (2015). Multiscale universal interface: A concurrent framework for coupling heterogeneous solvers. Journal of Computational Physics, 297:13– 31.
Valcke, S. (2013). The oasis3 coupler: a european climate modelling community software. Geoscientific Model Development, 6(2):373–388.
Wagner, G. J. and Liu, W. K. (2003). Coupling of atomistic and continuum simulations using a bridging scale decomposition. Journal of Computational Physics, 190(1):249 – 274.
Wu, H., Gui, N., Yang, X., Tu, J., and Jiang, S. (2018). A smoothed void fraction method for cfd-dem simulation of packed pebble beds with particle thermal radiation. International Journal of Heat and Mass Transfer, 118:275–288.
Xiao, S. and Belytschko, T. (2004). A bridging domain method for coupling continua with molecular dynamics. Computer Methods in Applied Mechanics and Engineering, 193(17–20):1645 – 1669. Multiple Scale Methods for Nanoscale Mechanics and Materials.
Yang, Q., Cheng, K., Wang, Y., and Ahmad, M. (2019). Improvement of semi-resolved cfd-dem model for seepage-induced fine-particle migration: Eliminate limitation on mesh refinement. Computers and Geotechnics, 110:1–18.
