A Karhunen–Loève least-squares technique for optimization of geometry of a blunt body in supersonic flow

Abstract

A novel Karhunen–Loève (KL) least-squares model for the supersonic flow of an inviscid, calorically perfect ideal gas about an axisymmetric blunt body employing shock-fitting is developed; the KL least-squares model is used to accurately select an optimal configuration which minimizes drag. Accuracy and efficiency of the KL method is compared to a pseudospectral method employing global Lagrange interpolating polynomials. KL modes are derived from pseudospectral solutions at Mach 3.5 from a uniform sampling of the design space and subsequently employed as the trial functions for a least-squares method of weighted residuals. Results are presented showing the high accuracy of the method with less than 10 KL modes. Close agreement is found between the optimal geometry found using the KL model to that found from the pseudospectral solver. Not including the cost of sampling the design space and building the KL model, the KL least-squares method requires less than half the central processing unit time as the pseudospectral method to achieve the same level of accuracy. A decrease in computational cost of several orders of magnitude as reported in the literature when comparing the KL method against discrete solvers is shown not to hold for the current problem. The efficiency is lost because the nature of the nonlinearity renders a priori evaluation of certain necessary integrals impossible, requiring as a consequence many costly reevaluations of the integrals.