Frozen propagation of Reynolds force vector from high-fidelity data into Reynolds-averaged simulations of secondary flows

Successful propagation of information from high-fidelity sources (i.e., direct numerical simulations and large-eddy simulations) into Reynolds-averaged Navier–Stokes (RANS) equations plays an important role in the emerging field data-driven RANS modeling. Small errors carried data can propagate amplified mean flow field, higher Reynolds numbers worsen error propagation. In this study, we compare a series methods for two cases Prandtl's secondary flows second kind: square-duct at low number roughness-induced very high number. We show that frozen treatments result less than implicit treatment stress tensor (RST), with numbers, explicit are not recommended. Inspired by obtained results, introduce to force vector (RFV), which leads Specifically, both RFV results one order magnitude lower compared RST method, three different eddy-viscosity models used evaluate effect turbulent diffusion on that, regardless baseline model, combined extra correction term kinetic energy RFV, makes our technique capable reproducing velocity fields similar data.