Comparison of Robust Optimization Methods Applied to Hypersonic Vehicle Design

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Comparison of Robust Optimization Methods Applied to Hypersonic Vehicle Design

Ryan, Kevin M. / Lewis, Mark J. / Yu, Kenneth H.

The use of various robust optimization methods to solve engineering problems with environmental parameter uncertainty was investigated. Comparisons were made between a novel multi-objective-based robust optimization formulation and conventional robust regularization-based and aggregation-based methods. The results, performance, and philosophies of each method are discussed. A hypersonic vehicle design problem was used as a test bed for the methods presented here. A focus was put on studying the effect of uncertain roughness-induced boundary-layer transition locations on vehicle controllability. The robust regularization results show that a flat wedgelike vehicle design is best for a worst-case scenario, whereas a pyramidal-shaped vehicle design minimizes the expected detrimental effects on vehicle controllability. The analysis proved that the multi-objective robust optimization method was able to identify these two types of results within an overall set of results while also capturing tradeoffs within the design space.