Bayesian parameter estimation of SST model for shock wave-boundary layer interaction flows with different strengths  

作　　者：Denggao TANG Jinping LI Fanzhi ZENG Yao LI Chao YAN 

机构地区：[1]School of Aeronautic Science and Engineering,Beihang University,Beijing 100191,China

出　　处：《Chinese Journal of Aeronautics》2023年第4期217-236,共20页中国航空学报（英文版）

基　　金：supported by the National Numerical WindTunnel Project(No.NNW2019ZT1-A03);the National Natural Science Foundation of China(No.11721202).

摘　　要：The Shock Wave-Boundary Layer Interaction(SWBLI)flow generated by compression corner widely occurs in engineering.As one of the primary methods in engineering,the Reynolds Averaged Navier-Stokes(RANS)methods usually cannot correctly predict strong SWBLI flows.In addition to the defects of the eddy viscosity assumption,the uncertainty of the closure coeffi-cients in RANS models often significantly impacts the simulation results.This study performs para-metric sensitivity analysis and Bayesian calibration on the closure coefficients of the Menter k-x Shear-Stress Transport(SST)model based on the SWBLI with different strengths.Firstly,the para-metric sensitivity on prediction results is analyzed using the Sobol index.The results indicate that the Sobol indices of wall pressure and skin friction exhibited opposite fluctuation trends with the increase of SWBLI strength.Then,the Bayesian uncertainty quantification method is adopted to obtain the posterior probability distributions and Maximum A Posteriori(MAP)estimates of the closure coefficients and the posterior uncertainty of the Quantities of Interests(QoIs).The results indicate that the prediction ability for strong SWBLI of the SST model is significantly improved by using the MAP estimates,and the relative errors of QoIs are reduced dramatically.

关 键 词：Bayesian calibration Boundary layers Compression corner Sensitivity analysis Shear-stress transport turbu-lence model Shock waves 

分 类 号：V211[航空宇航科学与技术—航空宇航推进理论与工程] V411