Multi-dimensional aircraft surface pressure interpolation using radial basis functions

Multi-dimensional interpolation via radial basis functions is applied to the problem of using aircraft surface pressure data obtained both computationally and experimentally to obtain pressure distribution predictions through parameter space. In the most complicated cases, the data may be a function of spatial position, Mach number, Reynolds number, and angle of attack as well as other more intricate variables such as control surface deflections. Amalgamation of computational fluid dynamics and wind tunnel data for load prediction is currently a time-consuming task, especially given the large number of load cases that need to be evaluated to achieve aircraft certification, so that an efficient tool for making rapid estimates based on all the information available would be of great use. The approach, using radial basis functions, is tested on a combination of simple computational and experimental results and found to offer great flexibility, while still being capable of reproducing relatively detailed features of the pressure distribution.