A Physics-Informed, PIV-Based Method for Surface Pressure Reconstruction

A physics-informed method is proposed for reconstructing surface pressure from PIV data. The method formulates the reconstruction as a weighted least-squares optimization problem in which the surface pressure is represented by B-spline basis functions and constrained by local and global physical conditions. The standard deviation of the surfacenormal pressure gradient, evaluated from the PIV-based pressure field, is introduced as a physically meaningful indicator of local uncertainty and is used to define the weighting function in the optimization. The same quantity is also used to locate the suction peak directly from the PIV data. A global constraint, derived from the Navier-Stokes equation over a control volume surrounding the body, is introduced to anchor the reconstructed pressure distribution outside the suction region. The method is assessed by using time-averaged 3D-LPT data for a NACA 0015 airfoil. reconstructed surface pressure shows very good agreement with pressure-tap measurements. In the leading-edge region, where direct extrapolation is most sensitive to velocity and pressure-gradient errors, the reconstruction error is reduced by approximately a factor of three.