Quantification of the uncertainty within a SAS-SST simulation caused by the unknown high-wavenumber damping factor

Abstract This paper aims to quantify the uncertainty in the SAS-SST simulation of a prism bluff-body flow due to varying the higher-wavenumber damping factor ( C s ). Instead of performing the uncertainty quantification on the CFD simulation directly, a surrogate modelling approach is adopted. The mesh sensitivity is first studied and the numerical error due to the mesh is approximated accordingly. The Gaussian processes/Kriging method is used to generate surrogate models for quantities of interest (QoIs). The suitability of the surrogate models is assessed using the leave-one-out cross-validation tests (LOO-CV). The stochastic tests are then performed using the cross-validated surrogate models to quantify the uncertainty of QoIs by varying C s . Four prior probability density functions (such as U 0 , 1 , N 0.5 , 0.1 2 , B e t a 2 , 2 and B e t a 5 , 1.5 ) of C s are considered. It is demonstrated in this study that the uncertainty of a predicted QoI due to varying C s is regionally dependent. The flow statistics in the near wake of the prism body are subject to larger variance due to the uncertainty in C s . The influence of C s rapidly decays as the location moves downstream. The response of different QoIs to the changing C s varies greatly. Therefore, the calibration of C s only using observations of one variable may bias the results. Last but not least, it is important to consider different sources of uncertainties within the numerical model when scrutinising a turbulence model, as ignoring the contributions to the total error may lead to biased conclusions.