Efficient Multi-objective Aerodynamic Shape Optimization of 3D Supersonic Transport Using Proper Orthogonal Decomposition

In this research, a proper orthogonal decomposition (POD)-based re-parameterization approach is utilized to realize efficient multi-objective aerodynamic shape optimization (MOASO) by reducing the number of design variables, which results in reducing the number of computational fluid dynamics evaluations. The approach developed is examined in a three-dimensional wing-shape optimization problem of a supersonic transport configuration. As for the multi-objective design optimization problem, aerodynamic/sonic boom evaluations are performed to minimize the drag coefficient and sonic boom strength. By introducing a variable fidelity concept in the POD approach, the optimization problem can be solved with much smaller computational cost. Important design insights can be extracted and discussed from the most dominant (first) POD mode.