Multidisciplinary design optimization of an electric-powered unmanned air vehicle

Abstract

The Concurrent Subspace Design (CSD) framework has been used to conduct a preliminary design optimization of an electric-powered, unmanned air vehicle operating at low Reynolds number. A multidisciplinary system analysis has been developed for this class of vehicles and includes aerodynamics, weights, propulsion, performance and stability and control. The CSD framework employs artificial neural network-based response surfaces to provide approximations to the design space. This approach was applied to a number of conceptual aircraft design studies. In each case the CSD framework was able to identify feasible designs with significant weight reductions relative to any previously considered (i.e. initial database) designs. This was accomplished with a reasonable number of system analyses. The results also demonstrate the adaptive nature of this design framework to changes in design requirements.