Surrogate-Based Optimization for Thin-Walled Deployable Propeller Blades

Deployable propeller blades provide an effective solution for packaging large blades before launch and for rapidly deploying them to generate thrust during cruise, demonstrating potential for launching aerial vehicles under highly constrained environments. A novel thin-walled propeller blade concept that utilizes buckling instability for folding and deployment has been proposed recently. The blade structural design needs to fulfill multiple competing objectives. In this study, a multi-objective optimization is conducted to find the optimal design parameters. First, the optimization problem is formulated with three conflicting objectives: maximizing the critical moment, maximizing the blade length, and minimizing the post-buckled steady-state moment. Three geometric design variables are considered under a maximum strain energy constraint. Four surrogate models are employed and evaluated, resulting in a combined surrogate model chosen for optimization. Finally, the performance of three optimization algorithms is compared and a genetic algorithm is applied to determine the optimal design.