Low-Boom and Low-Drag Optimization of the Twin Engine Version of Silent Supersonic Business Jet

Abstract

Multi-Objective Optimization has been applied to a design problem of the twin engine concept for Silent Supersonic Business Jet (SSBJ). This problem aims to find main wing, body, tail wing and engine nacelle configurations, which can minimize both sonic boom and drag in a supersonic cruising flight. The multi-objective genetic algorithm (MOGA) coupled with the Kriging model has been used to globally and effectively search for optimal design candidates in the multi-objective problem. The drag and the sonic boom have been evaluated by the computational fluid dynamics (CFD) simulation and the waveform parameter method. As a result, the present optimization has successfully obtained low-boom and low-drag design candidates, which are better than the baseline design by more than 40% regarding each performance. Moreover, the structure of design space has been visualized by the self-organizing map (SOM).