A surrogate-based optimization framework for hypersonic aerothermoelastic scaling laws with application to skin panels

This study describes the development of an optimization framework for generating hypersonic aerothermoelastic scaling laws using a novel two-pronged approach. The approach combines a classical scaling approach based on dimensional analysis with augmentation from numerical simulations of the specific problem. From the comparison and adjustment of the full-scale prototype and the scaled model, the “numerical similarity solutions” are generated to replace the analytical similarity solutions for refinement of the scaling laws. The search for an aerothermoelastically scaled model is formulated as an multi-objective optimization problem, which is solved using a surrogate-based optimization algorithm. The effectiveness of the two-pronged approach is demonstrated by its application to the development of refined hypersonic aerothermoelastic scaling law for a composite skin panel configuration.