Assessment of Computational Fluid Dynamics and Experimental Data for Shock Boundary-Layer Interactions

A workshop on the computational fluid dynamics (CFD) prediction of shock boundary-layer interactions (SBLIs) was held at the 48th AIAA Aerospace Sciences Meeting. As part of the workshop, numerous CFD analysts submitted solutions to four experimentally measured SBLIs. This paper describes the assessment of the CFD predictions. The assessment includes an uncertainty analysis of the experimental data, the definition of an error metric, and the application of that metric to the CFD solutions. The CFD solutions provided very similar levels of error and, in general, it was difficult to discern clear trends in the data. For the Reynolds-averaged Navier-Stokes (RANS) methods, the choice of turbulence model appeared to be the largest factor in solution accuracy. Scale-resolving methods, such as large-eddy simulation (LES), hybrid RANS/LES, and direct numerical simulation, produced error levels similar to RANS methods but provided superior predictions of normal stresses. Copyright © 2012 by Daniella E. Raveh and Michael Iovnovich.

[1]  T. Shih,et al.  A new k-ϵ eddy viscosity model for high reynolds number turbulent flows , 1995 .

[2]  J. Benek Lessons Learned from the 2010 AIAA Shock Boundary Layer Interaction Prediction Workshop , 2010 .

[3]  Christopher J. Roy,et al.  Verification and Validation in Scientific Computing: Design and execution of validation experiments , 2010 .

[4]  J. S. Hunter,et al.  Statistics for Experimenters: Design, Innovation, and Discovery , 2006 .

[5]  E. Reshotko,et al.  Shock-wave boundary layer interactions , 1986 .

[6]  William L. Oberkampf,et al.  Joint Computational/Experimental Aerodynamics Research on a Hypersonic Vehicle, Part 1: Experimental Results , 1991 .

[7]  Sergio Pirozzoli,et al.  Direct numerical simulation of impinging shock wave/turbulent boundary layer interaction at M=2.25 , 2006 .

[8]  Christopher J. Roy,et al.  Verification and Validation in Scientific Computing , 2010 .

[9]  Christopher L. Rumsey,et al.  Turbulence modeling effects on calculation of lobed nozzle flowfields , 2006 .

[10]  P. Durbin On the k-3 stagnation point anomaly , 1996 .

[11]  John Benek Overview of the 2010 AIAA Shock Boundary Layer Interaction Workshop , 2010 .

[12]  Jan-Renee Carlson,et al.  Turbulent Output-Based Anisotropic Adaptation , 2010 .

[13]  Andrew P. Lapsa,et al.  Stereo particle image velocimetry of nonequilibrium turbulence relaxation in a supersonic boundary layer , 2011 .

[14]  Hugh W. Coleman,et al.  Experimentation and Uncertainty Analysis for Engineers , 1989 .

[15]  B. Launder,et al.  Application of the energy-dissipation model of turbulence to the calculation of flow near a spinning disc , 1974 .

[16]  P. Spalart,et al.  A hybrid RANS-LES approach with delayed-DES and wall-modelled LES capabilities , 2008 .

[17]  D. Wilcox Turbulence modeling for CFD , 1993 .

[18]  Stephen B. Pope,et al.  Filtered mass density function for large-eddy simulation of turbulent reacting flows , 1999, Journal of Fluid Mechanics.

[19]  A. Sidorenko,et al.  Investigation by Particle Image Velocimetry Measurements of Oblique Shock Reflection with Separation , 2008 .

[20]  P. Spalart A One-Equation Turbulence Model for Aerodynamic Flows , 1992 .

[21]  Hassan Hassan,et al.  Simulation of Shock / Boundary Layer Interactions Using Improved LES/RANS Models , 2010 .

[22]  William L. Oberkampf,et al.  Assessment of CFD models for shock boundary-layer interaction , 2010 .

[23]  William L. Oberkampf,et al.  Surface pressure measurements for CFD code validation in hypersonic flow , 1995 .

[24]  F. Menter Two-equation eddy-viscosity turbulence models for engineering applications , 1994 .

[25]  S. Pope,et al.  Filtered density function for large eddy simulation of turbulent reacting flows , 1998 .