Development of turbulent inflow methods for the high order HPC framework FLEXI

Daniel Kempf (), Min Gao (), Andrea Beck (), Marcel Blind (), Patrick Kopper (), Thomas Kuhn, Marius Kurz (), Anna Schwarz () and Claus-Dieter Munz ()
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Daniel Kempf: University of Stuttgart, Institute of Aerodynamics and Gas Dynamics
Min Gao: University of Stuttgart, Institute of Aerodynamics and Gas Dynamics
Andrea Beck: University of Stuttgart, Institute of Aerodynamics and Gas Dynamics
Marcel Blind: University of Stuttgart, Institute of Aerodynamics and Gas Dynamics
Patrick Kopper: University of Stuttgart, Institute of Aircraft Propulsion Systems
Thomas Kuhn: University of Stuttgart, Institute of Aerodynamics and Gas Dynamics
Marius Kurz: University of Stuttgart, Institute of Aerodynamics and Gas Dynamics
Anna Schwarz: University of Stuttgart, Institute of Aerodynamics and Gas Dynamics
Claus-Dieter Munz: University of Stuttgart, Institute of Aerodynamics and Gas Dynamics

A chapter in High Performance Computing in Science and Engineering '21, 2023, pp 289-304 from Springer

Abstract: Abstract Turbulent inflow methods offer new possibilities for an efficient simulation by reducing the computational domain to the interesting parts. Typical examples are turbulent flow over cavities, around obstacles or in the context of zonal large eddy simulations. Within this work, we present the current state of two turbulent inflow methods implemented in our high order discontinuous Galerkin code FLEXI with special focus laid on HPC applications. We present the recycling-rescaling anisotropic linear forcing (RRALF), a combination of a modified recycling-rescaling approach and an anisotropic linear forcing, and a synthetic eddy method (SEM). For both methods, the simulation of a turbulent boundary layer along a flat plate is used as validation case. For the RRALF method, a zonal large eddy simulation of the rear part of a tripped subsonic turbulent boundary layer over a flat plate is presented. The SEM is validated in the case of a supersonic turbulent boundary layer using data from literature at the inflow. In the course of the cluster upgrade to the HPE Apollo system at HLRS, our framework was examined for performance on the new hardware architecture. Optimizations and adaptations were carried out, for which we will present current performance data.

Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-17937-2_17

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DOI: 10.1007/978-3-031-17937-2_17

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