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Fuzzy analysis as alternative to stochastic methods – a comparison by means of a crash analysis

M. Thiele (DYNAmore), M. Liebscher, Prof. W. Graf (Technical University Dresden) A realistic and reliable numerical simulation demands suitable computational models and applicable data models for the structural design parameters. Structural design parameters are in general nondeterministic. The choice of an appropriate uncertainty model for describing selected structural design parameters depends on the characteristics of the available information. Besides the most often used probabilistic models and the stochastic analysis techniques newer uncertainty models have been developed that offer the chance to take account of non-stochastic uncertainty that frequently appears in engineering problems. In this paper a crash analysis example with uncertain structural parameters is presented. The uncertainty quantification is realized with aid of the uncertainty models randomness and fuzziness. The quantified uncertain structural parameters are introduced into their respective analysis algorithms: the stochastic structural analysis and the fuzzy structural analysis. Specifies and advantages of the uncertainty models fuzziness and randomness and of the associated simulation techniques are addressed. The authors would like to thank Daimler Chrysler Commercial Vehicles for supporting this study.

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