Examining improved experimental designs for wind tunnel testing using Monte Carlo sampling methods

Wind tunnels are used in the design and testing of a wide variety of systems and products. Wind tunnel test campaigns involve a large number of experimental data points, can take a long time to accomplish, and can consume tremendous resources. Design of Experiments is a systematic, statistically based approach to experimental design and analysis that has the potential to improve the efficiency and effectiveness of wind tunnel testing. In Defense Acquisition, wind tunnel testing of aircraft systems may require years of effort to fully characterize the system of interest. We employ data from a fairly large legacy wind tunnel test campaign and compare that data's corresponding response surface to the response surfaces derived from data generated using smaller, statistically motivated experimental design strategies. The comparison is accomplished using a Monte Carlo sampling methodology coupled with a statistical comparison of the system's estimated response surfaces. Initial results suggest a tremendous opportunity to reduce wind tunnel test efforts without losing test information.