This Small Business Innovation Research Phase I project aims at developing a shape design optimization tool by integrating a state-of-the-art computational fluid dynamics (CFD) technique within an efficient multi-disciplinary design optimization (MDO) strategy. The ability to adaptively optimize aerodynamic shape of hypersonic flight vehicles is an issue of prime interest to aircraft and spacecraft designers. The physics of flow and the spectrum of aerodynamic features involved in this flight regime are quite involved and include expansions, shocks, separation, recirculations, and reattachments. The computational simulation of such complex flow fields requires an efficient, robust, and extremely accurate numerical solution technique that is stable for a wide range in Reynolds number and Mach number flows. At the same time, nonlinear optimization of aerodynamic shape requires a sequence of these problems to be solved successively to arrive at an optimum design. The optimization techniques that can reduce the number of redundant design options can result in considerable savings in time. Employing an Artificial Intelligence (AI) network around this highly accurate shape design synthesis capability, the resulting tool shows a drastic reduction in the number of cycles required to reach an optimum aerodynamic shape, thus economizing the design cycle and reducing the cost and time. If successful, the project will lead to an inexpensive and fast tool for aerodynamic shape optimization of hypersonic and transonic flight vehicles. The two products from this work; (a) the optimization tool, and (b) the flow solver, will be marketed as stand-alone capabilities as well as an integrated design-optimization software. In addition to the aeronautical industry, this software will be of tremendous interest to the automotive industry for aerodynamic shape optimization of the new generation cars, trucks and bullet trains.
