A multi-fidelity platform using machine learning for integrated design of aircraft systems

The aim of to minimize the time utilized for the developing the aircraft enables the collaborative foundation for the integrated design of aircraft. The work presented in this paper is a simulated work in Simulink which showcases the integrated design approach of the aircraft. This paper focuses on to down select a feasible architecture, evaluate the architecture based on the KPIs and invoke machine learning algorithm in order to group and to search for the optimal. The designer has privilege to prioritize the requirement and choice of optimal architecture. This paper demonstrates the two use cases: demonstration Primary flight control system and landing gear braking system.