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.


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    Title :

    Comparison of Robust Optimization Methods Applied to Hypersonic Vehicle Design


    Contributors:

    Published in:

    Journal of Aircraft ; 52 , 5 ; 1510-1523


    Publication date :

    2015-02-06


    Size :

    14 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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