Stochastic deconvolution of wall statistics in Reynolds‐averaged Navier–Stokes simulations based on one‐dimensional turbulence

Abstract Reynolds‐averaged Navier–Stokes simulation (RaNS) is state‐of‐the‐art for numerical analysis of complex flows at high Reynolds number. Standalone RaNS may yield a reasonable estimate the wall‐shear stress and turbulent drag if proper wall‐function prescribed, but detailed turbulence statistics cannot be obtained, especially wall. This lack in modeling addressed here by stochastic deconvolution strategy based on one‐dimensional (ODT) model. Here, one‐way coupling proposed which forcing term computed from balanced solution that turn utilized ODT The temporally developing exhibits perturbations relaxes toward local due to resolved molecular‐diffusive processes. It demonstrated approach able recover distribution positive fluctuations channel flow. When formulated as post‐processing tool, it suggested can enhanced providing economical means high‐fidelity low‐fidelity flow solution.