Adding hypothesis testing to evolutionary RBDO with Monte Carlo simulations

Abstract : Engineers have a long history with accounting for uncertainties in the design process [2]. They have first defined critical loadings and safety factors. More recently, uncertainty quantification is receiving a large attention from the engineering community because a finer characterization of the uncertainties is seen as an important performance reserve. In the presence of uncertainties, the performance of an individual system varies. Reliability based design optimization (RBDO) and robust optimization average out uncertainties by ultimately seeking solutions having the best statistical performance measure [1].
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Communication dans un congrès
ECCM 2010, IV European Conference on Computational Mechanics, May 2010, Paris, France. pp.936, 2010
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https://hal-emse.ccsd.cnrs.fr/emse-00686630
Contributeur : Florent Breuil <>
Soumis le : mardi 10 avril 2012 - 17:23:06
Dernière modification le : mardi 23 octobre 2018 - 14:36:09

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  • HAL Id : emse-00686630, version 1

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Daniel Salazar, Rodolphe Le Riche, Xavier Bay. Adding hypothesis testing to evolutionary RBDO with Monte Carlo simulations. ECCM 2010, IV European Conference on Computational Mechanics, May 2010, Paris, France. pp.936, 2010. 〈emse-00686630〉

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