Multi-objective optimization and analysis of rotor blades in Mars atmospheric environment based on surrogate model and non-dominated sorting genetic algorithm

The successful flight demonstration of Ingenuity in the Martian atmosphere offers novel insights for Mars exploration, where the rotor, as a core component of Mars drones, critically determines mission success. This study presents a surrogate model-based optimization method for rotor design, employing the clf5605 airfoil as a baseline for parametric modeling. To achieve efficient optimization, a sensitivity analysis was first conducted to identify high-impact design variables. A radial basis function neural network surrogate model was then constructed, coupled with a non-dominated sorting genetic algorithm to derive optimal airfoil configurations. Results indicate that five key parameter categories—twist angle distribution, chord length distribution, thickness distribution, maximum curvature position, and maximum curvature (totaling 14 control parameters)—dominate rotor performance, with sensitivity coefficients of 0.914 (Earth) and 0.947 (Mars). The optimized airfoils outperformed the clf5605 baseline across all objectives: a 16.4% increase in the A1 figure of merit, a 10.03% boost in the A2 lift coefficient, a 10.00% reduction in A3 rotor mass, and an 8.62% decrease in A4 energy consumption. Aerodynamic tests of an A1 prototype under Earth conditions further validated the method's efficacy. This work systematically analyzes the influence of rotor parameters on aerodynamic performance and provides a practical framework for future rotor optimization in extraterrestrial environments.