A hybrid approach combining DNS and RANS simulations to quantify uncertainties in turbulence modelling

Uncertainty quantification (UQ) has recently become an important part of the design process countless engineering applications. However, up to now in computational fluid dynamics (CFD) errors introduced by turbulent viscosity models Reynolds-Averaged Navier Stokes (RANS) have often been neglected UQ studies. Although Direct Numerical Simulations (DNS) are physically correct, obtaining a large enough set DNS data for studies is currently computationally intractable. based only on RANS simulations or thus leads physical and statistical inaccuracies output probability distribution functions (PDF). Therefore, three hybrid methods combining both perform non-intrusive suggested this work. Low-fidelity high-fidelity combined give approximation PDF using advantages sets: accuracy via simulations. The applied flow over 2D periodically arranged hills. It shown that Gaussian CoKriging (GCK) method best approach possible, with more accurate statistically better PDF.