Simulation of Turbulent Flows Using a Fully Discrete Explicit hp-nonconforming Entropy Stable Solver of Any Order on Unstructured Grids
Type
Conference PaperAuthors
Parsani, Matteo
Boukharfane, Radouan

Reyna Nolasco, Irving E.
Dalcin, Lisandro
Keyes, David E.

KAUST Department
Applied Mathematics and Computational Science ProgramExtreme Computing Research Center
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
King Abdullah University of Science and Technology
Office of the President
Date
2021-01-04Permanent link to this record
http://hdl.handle.net/10754/667508
Metadata
Show full item recordAbstract
We report the numerical solution of two challenging turbulent flow test cases simulated with the SSDC framework, a compressible, fully discrete hp-nonconforming entropy stable solver based on the summation-by-parts discontinuous collocation Galerkin discretizations and the relaxation Runge—Kutta methods. The algorithms at the core of the solver are systematically designed with mimetic and structure-preserving techniques that transfer fundamental properties from the continuous level to the discrete one. We aim at providing numerical evidence of the robustness and maturity of these entropy stable scale-resolving methods for the new generation of adaptive unstructured computational fluid dynamics tools. The two selected turbulent flows are i) the flow past two spheres in tandem at a Reynolds number based on the sphere diameter of ReD = 3.9 × 103 and 104, and a Mach number of Ma∞ = 0.1, and ii) the NASA junction flow experiment at a Reynolds number based on the crank chord length of Reℓ = 2.4×106 and Ma∞ = 0.189.Citation
ArraySponsors
The research reported in this paper was funded by King Abdullah University of Science and Technology. We are thankful for the computing resources of the Supercomputing Laboratory and the Extreme Computing Research Center at King Abdullah University of Science and Technology.Conference/Event name
AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021ISBN
9781624106095Additional Links
https://arc.aiaa.org/doi/10.2514/6.2021-0495ae974a485f413a2113503eed53cd6c53
10.2514/6.2021-0495