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Slip-Wall-Modeled Large-Eddy Simulation for the Prediction of Smooth-Body Separation

AMS Seminar Series

Speaker: Michael P. Whitmore, Center for Turbulence Research, Stanford University

Presentation

Seminar Slide Deck (PDF-5.9MB)

Abstract

Wall-modeled large-eddy simulation is increasingly used as a tool for analysis of external aerodynamic applications. It has been observed that traditional wall models, which are typically based on Reynolds-averaged Navier-Stokes closures, can under-perform in flows with mild, adverse pressure gradients that result in boundary layer separation. Slip wall models are presented as an alternative formulation to predict high Reynolds number boundary layers undergoing separation. Prior studies utilizing slip wall models have shown sensitivity of results to the choices of slip length in attached boundary layers. The slip wall model is applied to a canonical case of smooth-body separation, the Boeing speed bump, and, subsequently, to the JAXA Standard Model at a low angle of attack. Significant errors in skin friction predictions are observed at coarse resolutions, particularly in regions of zero or favorable pressure gradients when using a slip length based on Prandtl mixing lengths. However, under specific choices of slip lengths, improved predictions for the JAXA Standard Model are obtained due to improved predictions of flap separation compared with the equilibrium wall model. This suggests that more robust separation predictions may be possible if a more accurate method for computing slip lengths could be developed.

Biography

Photo of Michael Whitmore
Michael Whitmore is a Ph.D. candidate in mechanical engineering at Stanford University, working under the guidance of Professor Parviz Moin at the Center for Turbulence Research. He holds an M.S. from Stanford in mechanical engineering and a B.S.E. from Princeton University in mechanical and aerospace engineering. Michael's research interests lie in the intersection of physics, numerical analysis, and computational modeling, with applications to aerodynamics, turbomachinery, and design of complex engineering systems. In addition, he is interested in applications of computer science and programming for high performance computing.