Multidisciplinary optimisation of a supersonic transport using design of experiments theory and response surface modelling

Abstract

Abstract The presence of numerical noise in engineering design optimisation problems inhibits the use of many gradient-based optimisation methods. This numerical noise may result in the inaccurate calculation of gradients which in turn slows or prevents convergence during optimisation, or it may promote convergence to spurious local optima. The problems created by numerical noise are particularly acute in aircraft design applications where a single aerodynamic or structural analysis of a realistic aircraft configuration may require tens of CPU hours on a supercomputer. The computational expense of the analyses coupled with the convergence difficulties created by numerical noise are significant obstacles to performing aircraft multidisciplinary design optimisation. To address these issues, a procedure has been developed to create noise-free algebraic models of subsonic and supersonic aerodynamic performance quantities, for use in the optimisation of high-speed civil transport (HSCT) aircraft configurations. This procedure employs methods from statistical design of experiments theory and response surface modelling to create the noise-free algebraic models. Results from a sample HSCT design problem involving ten variables are presented to demonstrate the utility of this method.