Combined Aircraft and Payload Design Optimization Using a Multidisciplinary Architecture

Abstract

Aircraft design is a complex process, often focusing on a single use case and requiring extensive iteration to yield a sufficient result. This process is further complicated by the analysis of payload performance. Depending on the subsystem being considered, extensive modeling efforts may be required. Unintuitive performance tradeoffs can also become inherent to a design when multiple subsystems are considered simultaneously. To support the development of a payload-integrated aircraft in this work, a multidisciplinary optimization framework is developed. Response surface modeling and genetic algorithms are implemented in a system modeling structure to inform the unique performance tradeoffs of this complex system. This framework permits the optimization of a vehicle which incorporates balanced performance capabilities rather than the maximization of a single metric. This optimized vehicle is also found to be unique compared to existing UAS. In future work, statistical analysis and higher sub-model fidelity could improve mission performance and decision-making processes.