A Robust Method for Reliable Transition Detection in Temperature-Sensitive Paint Data

Abstract

This work presents a method to automatically detect boundary-layer transition on thermographic images of aerodynamic surfaces, acquired using the temperature-sensitive paint measurement technique. It is applied to surface temperature distributions mapped onto three-dimensional grids representing the surfaces of interest. Motivated and substantiated by earlier work, the transition location is determined at the location corresponding to the maximal value of the streamwise gradient of the surface temperature in the transitional region. The robustness of the transition detection method was proven for a challenging case with low signal to-noise ratio and moderate streamwise temperature gradients. Moreover, the present method was validated against transition data obtained using an uncorrelated transition detection method based on the measurement of surface pressure fluctuations. The developed transition detection algorithm enabled the accurate, reliable, and consistent detection of the transition location under a variety of test conditions, including experiments on natural laminar flow airfoil and wing models at high Reynolds numbers and high subsonic Mach numbers.