Grid-adaptation for wall-modeled large eddy simulations

Seminar Speaker: Dr. Johan Larsson, Professor, University of Maryland

Abstract: Turbulence resolving simulations, such as Direct Numerical Simulations (DNS) and Large-Eddy Simulations (LES), can provide detailed insights into fluid phenomena in ways that are not available with the more common Reynolds Averaged Navier-Stokes (RANS) methods.  As the Reynolds number increases, the cost of DNS and LES quickly becomes prohibitive, which has inhibited application to more applied problems of interest.  Grid adaptation can help reduce the expense and has reached a certain level of maturity in several areas of computational fluid dynamics.  However, grid adaptation for turbulence-resolving simulations (most notably, LES) is still in its infancy.  The chaotic and broadband nature of the dynamics in an LES leads to two major challenges.  First, the grid affects both the numerical and modeling error in LES, compared to only the numerical error in non-broadband problems.  As a result, the estimation of the local error production cannot be purely mathematical but must also require physics-informed reasoning and assumptions. Secondly, the chaotic nature causes adjoints to diverge exponentially, which makes direct application of the adjoint-weighted residual method cumbersome.  The talk will discuss progress made on this problem over the last 5-10 years in the PI's group, along with outstanding issues and ongoing/future work, including attempts at applying grid-adaptation techniques to wall-modeled LES.

Bio: Johan Larsson is a Professor at the University of Maryland where he works on multiple problems in the field of computational turbulence including wall-modeling for large eddy simulation, grid-adaptation for turbulence-resolving simulations, high-speed turbulent flows, and uncertainty quantification for turbulence problems.  He earned his PhD at the University of Waterloo, Canada, in 2006, and then worked at the Center for Turbulence Research at Stanford University as a postdoctoral fellow and Research Associate for 6 years before joining the University of Maryland in 2012. He is an Associate Editor of the AIAA Journal.