Towards High Reynolds Number Turbulent Boundary Layer Direct Numerical Simulation by Data Assimilation of Stereo Particle Image Velocimetry Data

High-Reynolds-number direct numerical simulation (DNS) of turbulent boundary layers is limited by the difficulty of generating realistic inflow conditions and the cost of resolving all turbulent scales. This presentation investigates a data-assimilation approach in which time-resolved 3-component – 2-dimensional stereo particle image velocimetry (3C–2D SPIV) data are used as inflow conditions for spatially developing DNS. Using channel-flow DNS as a reference, synthetic SPIV fields are generated by applying interrogation-volume filtering and spatial limitation, then imposed at the inlet of an inflow–outflow DNS. Comparisons of skin friction, velocity and pressure statistics, coherent structures, and spectra show that mean wall shear stress recovers rapidly downstream, while accurate reproduction of turbulent fluctuations and spectral content requires a longer development distance. The results indicate that current SPIV sensor technology can provide realistic inflow data for high-Reynolds-number wall-bounded DNS, enabling experimentally informed simulations with recovered pressure fields and fully resolved three-dimensional turbulent structures.