The application of inverse design in engineering is constrained by uncertainty over when to cease calculations owing to solution fluctuations and suboptimal aerodynamic parameter distribution. The proposed method for inverse design optimization incorporates active subspace assistance to effectively address these significant limitations. The optimal load distribution is achieved by the integration of sparse polynomial approximation and genetic algorithm. Furthermore, active subspace method is employed to solve the control zone of optimal static pressure/load distribution. The inverse design calculation is terminated when current load distribution falls completely within the control zone. Within the control zone, all static pressure/load distributions following a certain variance are guaranteed to provide nearly identical aerodynamic performance. The results indicate that the static pressure/load distribution of the final solution entirely falls within the control zone, while its aerodynamic performance approximates the optimal target value. In comparison to the initial solution, the final solution exhibits a significant decrease of 3.6% in the total pressure loss coefficient.
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