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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 evalua
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