Three-dimensional variational data assimilation of separated flows using time-averaged experimental data
This paper presents a novel three-dimensional variational data assimilation framework that integrates planar PIV experimental data with the Spalart-Allmaras RANS model to effectively separate measurement errors from turbulence model deficiencies, thereby significantly improving flow predictions for separated flows over a NACA0012 airfoil compared to traditional two-dimensional methods.