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Density modification based reliability sensitivity analysis

hal.structure.identifierSimulation et Traitement de l'information pour l'Exploitation des systèmes de Production [EDF R&D STEP]
hal.structure.identifierAdvanced Learning Evolutionary Algorithms [ALEA]
dc.contributor.authorLEMAÎTRE, Paul
hal.structure.identifierInstitut de Mathématiques de Toulouse UMR5219 [IMT]
hal.structure.identifierIFP Energies nouvelles [IFPEN]
dc.contributor.authorSERGIENKO, Ekaterina
hal.structure.identifierSimulation et Traitement de l'information pour l'Exploitation des systèmes de Production [EDF R&D STEP]
dc.contributor.authorARNAUD, Aurélie
hal.structure.identifierSimulation et Traitement de l'information pour l'Exploitation des systèmes de Production [EDF R&D STEP]
hal.structure.identifierGraphes, AlgOrithmes et AppLications [GOAL]
dc.contributor.authorBOUSQUET, Nicolas
hal.structure.identifierInstitut de Mathématiques de Toulouse UMR5219 [IMT]
dc.contributor.authorGAMBOA, Fabrice
hal.structure.identifierSimulation et Traitement de l'information pour l'Exploitation des systèmes de Production [EDF R&D STEP]
hal.structure.identifierInstitut de Mathématiques de Toulouse UMR5219 [IMT]
dc.contributor.authorIOOSS, Bertrand
dc.date.created2012-10-01
dc.date.issued2014-07-25
dc.identifier.issn0094-9655
dc.description.abstractEnSensitivity analysis of a numerical model, for instance simulating physical phenomena, is useful to quantify the influence of the inputs on the model responses. This paper proposes a new sensitivity index, based upon the modification of the probability density function (pdf) of the random inputs, when the quantity of interest is a failure probability (probability that a model output exceeds a given threshold). An input is considered influential if the input pdf modification leads to a broad change in the failure probability. These sensitivity indices can be computed using the sole set of simulations that has already been used to estimate the failure probability, thus limiting the number of calls to the numerical model. In the case of a Monte Carlo sample, asymptotical properties of the indices are derived. Based on Kullback-Leibler divergence, several types of input perturbations are introduced. The relevance of this new sensitivity analysis method is analysed through three case studies.
dc.language.isoen
dc.publisherTaylor & Francis
dc.subject.encomputer experiment
dc.subject.enKullback-Leibler
dc.subject.ensensitivity analysis
dc.subject.enstructural reliability
dc.subject.enuncertainty
dc.title.enDensity modification based reliability sensitivity analysis
dc.typeArticle de revue
dc.identifier.doi10.1080/00949655.2013.873039
dc.subject.halMathématiques [math]/Statistiques [math.ST]
dc.subject.halStatistiques [stat]/Théorie [stat.TH]
dc.identifier.arxiv1210.1074
bordeaux.journalJournal of Statistical Computation and Simulation
bordeaux.page1200-1223
bordeaux.volume85
bordeaux.issue6
bordeaux.peerReviewedoui
hal.identifierhal-00737978
hal.version1
hal.popularnon
hal.audienceNon spécifiée
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00737978v1
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