Systematic design space exploration and rearrangement of the MDO problem by using probabilistic methodology

This study proposes a probabilistic approach for systematic design space exploration and rearrangement. The stochastic quantities and qualities of design space are explored using a reliability index, and the design space is rearranged to a higher feasible region by using Chebyshev inequality. Four test cases composed of algebraic functions are used to investigate the validity of the proposed method. Results show that the converged design space can include the feasible region outside the initial design space to the rearranged design space. Moreover, the results show that the proposed method is applicable to the aircraft wing design optimization problem, which considers collaborative optimization with three subsystems, namely, aerodynamics, structure, and performance. Wing design optimizations are also performed separately for the initial and converged design spaces. The results indicate that the range obtained in the converged design space improved compared with that in the initial design space. In conclusion, the proposed design space rearrangement method was shown to have the capability to search for feasible regions that are excluded in the initial design phase.