Bulletin of the American Physical Society
75th Annual Meeting of the Division of Fluid Dynamics
Volume 67, Number 19
Sunday–Tuesday, November 20–22, 2022; Indiana Convention Center, Indianapolis, Indiana.
Session G24: Boundary Layers: LES Wall Modeling
3:00 PM–4:05 PM,
Sunday, November 20, 2022
Room: 232
Chair: Adrian Lozano-Duran, MIT
Abstract: G24.00002 : Solution Enrichment Wall-Modeled LES in the Spectral Element Method Framework*
3:13 PM–3:26 PM
Presenter:
Steven R Brill
(Stanford University)
Authors:
Steven R Brill
(Stanford University)
Pinaki Pal
(Argonne National Laboratory)
Muhsin Ameen
(Argonne National Laboratory)
Chao Xu
(Argonne National Laboratory)
Matthias Ihme
(Stanford University)
simulations (WMLES) of turbulent flows. Ordinarily, higher-order methods, such as SEM, require significant mesh
refinement near the wall in order to resolve the turbulent boundary layer without spurious oscillations due to the large
gradients in the boundary layer. To avoid this issue, as is done in traditional WMLES, we take the velocity at matching
points away from the wall and fit them with an analytical wall function to compute the shear stress on the wall and apply
it to the flow. To increase the fidelity of the model beyond the traditional method, we incorporate the wall function as an
enrichment term in the solution representation. This improves the accuracy of the model and allows for the solution to
be physically relevant up to the wall, unlike with shear-stress wall models. We discuss the procedure for integrating the
enrichment term in a SEM and its implementation in the SEM CFD solver Nek5000. The method is demonstrated in the
context of WMLES for canonical wall-bounded turbulent flows.
*Financial support from the Department of Defense (DoD) through the National Defense Science & EngineeringGraduate Fellowship (NDSEG) Program and from the Department of Energy (DOE) Vehicle Technologies Office (VTO)through project DE-EE0008875 are gratefully acknowledged. The authors also acknowledge the computing core hourson the Bebop cluster provided by the Laboratory Computing Resource Center (LCRC) at Argonne National Laboratory.
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