This study proposes and validates a novel machine-learned (ML) augmented linear
Reynolds averaged Navier Stokes (RANS) model, and the applicability of model assessed
in both interpolation and extrapolation modes for periodic hill (Hill) test case, which involves
complex flow regimes, such as attached boundary layer, shear-layer, and separation and
reattachment. For this purpose, the ML model is trained using direct numerical simulation
(DNS)/LES datasets for nine different cases with different flow separation and attachment …