Robust aeroelastic design optimization of hypersonic vehicles with uncertainties in aerodynamic loads, heat flux, and structure

This study sets the framework for robust aeroelastic design optimization of hypersonic vehicles with mixed uncertainties. A typical hypersonic low-aspect-ratio wing is used as an example to perform the optimization process. Uncertainties in aerodynamic loads, heat flux, and structural dimensions are considered simultaneously within the aerothermoelastic analysis and optimization process. Uncertainty in aerodynamic loads is introduced by aerodynamic load corrections method, and the critical aerodynamic load case can be obtained by sequential quadratic programming (SQP) method. Interval analysis method is employed to perform the transient heat transfer analysis when there is uncertainty in heat flux, and then genetic algorithm is used to obtained critical thermal load case. Uncertainty in structural dimensions is considered when the individual fitness is calculated. Sensitivity method is used to improve the robustness of the existing constraints and provide additional constraints. The author edited genetic algorithm codes together with aerothermoelastic analysis framework with mixed uncertainties form the robust optimization process. Optimization results show that the robust aeroelastic optimization process is a powerful tool to obtain the optimal solution which is capable of satisfying multi-constraints even when there are mixed uncertainties in different disciplines. Though the weight of optimal solution is greater than that without uncertainties, the flight safety can be ensured by this robust optimization process.