Goal-Oriented Weighting of Reynolds-Stress Data for Learning Turbulence Models in Complex Flows
Data-driven turbulence models for the Reynolds-averaged Navier-Stokes (RANS) equations offer a promising route to improving predictions of complex flows. Such models, specifically the turbulence constitutive relations, can be learned efficiently from high-fidelity Reynolds-stress data without evaluating the RANS equati...