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Facing Challenges in Computational Fluid Mechanics with Lattice Boltzmann Methods and HighPerformance Computers

Kolloquium der Abteilung 8

An overall strategy for numerical simulations and optimization of fluid flows is introduced. The integrative approach takes advantage of 

numerical simulation strategies and newly developed mathematical optimization techniques, which are all based on kinetic model 

descriptions and on Lattice Boltzmann Methods (LBM) as discretization strategies [1]. Thereby, the resulting algorithms were implemented 

in a highly generic way in the open-source framework OpenLB [2]. 

In the talk, particular focus is placed on the design and application of the approach in order to face contemporary challenges in 

Computational Fluid Dynamics (CFD) [3, 4]. Further, the consideration of LBM as a generic technique for the approximation of Partial 

Differential Equations (PDE) [5] and its implementation for heterogeneous high-performance computing (HPC) platforms are highlighted. 

The presented approaches and realizations are illustrated by means of various fluid flow simulation and optimization examples, where 

specific aspects are discussed for the simulation of particulate [6] and turbulent flows [7].



[1] Krause, M.J., 2010. Fluid Flow Simulation and Optimisation with Lattice Boltzmann Methods on High Performance Computers - Application to the Human Respiratory System, url: publikationen.bibliothek.kit.edu/1000019768.

[2] Krause, M.J., Kummerländer, A., Avis, S.J., Kusumaatmaja, H., Dapelo, D., Klemens, F., Gaedtke, M., Hafen, N., Mink, A., Trunk, R. and Marquardt, J.E., 2020. Openlb—Open source lattice Boltzmann code. Computers & Mathematics with Applications, doi:10.1016/j.camwa.2020.04.033.

[3] Slotnick, J., Khodadoust, A., Alonso, J., Darmofal, D., Gropp, W., Lurie, E. and Mavriplis, D., 2014. CFD Vision 2030 Study: A Path to Revolutionary Computational Aerosciences, NASA Technical Report, no. NASA/CR-2014-218178, url: https://ntrs.nasa.gov/citations/20140003093.

[4] Kwak, D., Kiris, C. and Kim, C.S., 2005. Computational challenges of viscous incompressible flows. Computers & Fluids, 34(3), pp.283-299, doi: 10.1016/j.compfluid.2004.05.008.

[5] Simonis, S., Frank, M. and Krause, M.J., 2020. On relaxation systems and their relation to discrete velocity Boltzmann models for scalar advection–diffusion equations. Philosophical Transactions of the Royal Society A, 378(2175), p.20190400, doi: 10.1098/rsta.2019.0400.

[6] Trunk, R., Weckerle, T., Hafen, N., Thäter, G., Nirschl, H., Krause, M.J., 2021. Revisiting the homogenized lattice Boltzmann method with applications on particulate flows, Computation 9 (2), p. 11, doi: 10.3390/computation9020011

[7] Haussmann, M., Ries, F., Jeppener-Haltenhoff, J.B., Li, Y., Schmidt, M., Welch, C., Illmann, L., Böhm, B., Nirschl, H., Krause, M.J. and Sadiki, A., 2020. Evaluation of a Near-Wall-Modeled Large Eddy Lattice Boltzmann Method for the Analysis of Complex Flows Relevant to IC Engines. Computation, 8(2), p.43, doi: 10.3390/computation8020043.