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Despite a steady decrease in the overall usage of wind tunnels due to the increasing reliability and speed of computational fluid dynamics (CFD), ground testing remains a fundamental part of the development of an air vehicle. In this context, one of the new trends is represented by data assimilation (DA), whereby experimental and numerical measurements are combined together in an attempt to extract more complete and accurate information from the available data. This work presents an assessment of a variational data assimilation framework for the problem of wind tunnel wall interference corrections. The methodology minimizes the discrepancy between experimental measurements and the corresponding values from a Reynolds-averaged Navier-Stokes (RANS) simulation by optimally tuning the free-stream angle of attack and Mach number, as well as a corrective field for the turbulence model. The framework is first validated on synthetic data, and then tested on two cases at high Mach number and low angle of attack using pressure coefficients on the model’s surface as the reference measurements. The assimilated pressure coefficients match the reference ones better than those obtained from a linear correction technique. Furthermore, assimilating also a corrective term in the turbulence model improves the quality of the results with respect to assimilating only the angle of attack and Mach number.

Assessment of a Data Assimilation Technique for Wind Tunnel Wall Interference Corrections