Global sensitivity analysis for the efficient solution of optimization problem in design process

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Abstract

Application of the methods of global sensitivity analysis in design process arises due to the complexity associated with structural optimization, e. g., in the automobile industry for an optimal vehicle structure for crash load cases. Usually, thousands of variants are considered for a vehicle design project and each variant represents a combination of a number of model parameters. The computation time for a single variant ranges from several hours to days. To reduce the complexity of the optimization problem, the significant parameters should be identified but possibly with a very few sample points. Since most of the available global sensitivity methods require a good approximation of the model response, a relatively large number of sample points is usually required for the surrogate model. In this contribution, an overview of state-of-the-art methods of global sensitivity analysis is given and an alternative idea is proposed to avoid full approximation of the model response. Instead, only the approximation of the level sets of the model response is used to derive sensitivity measures. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)

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