LEMAÎTRE, Paul; SERGIENKO, Ekaterina; ARNAUD, Aurélie; BOUSQUET, Nicolas; GAMBOA, Fabrice; IOOSS, Bertrand

doi:10.1080/00949655.2013.873039

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LEMAÎTRE, Paul
Simulation et Traitement de l'information pour l'Exploitation des systèmes de Production [EDF R&D STEP]
Advanced Learning Evolutionary Algorithms [ALEA]

SERGIENKO, Ekaterina
Institut de Mathématiques de Toulouse UMR5219 [IMT]
IFP Energies nouvelles [IFPEN]

ARNAUD, Aurélie
Simulation et Traitement de l'information pour l'Exploitation des systèmes de Production [EDF R&D STEP]

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Journal of Statistical Computation and Simulation. 2014-07-25, vol. 85, n° 6, p. 1200-1223

Taylor & Francis

Résumé en anglais

Sensitivity 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.< Réduire

Mots clés en anglais

computer experiment

Kullback-Leibler

sensitivity analysis

structural reliability

uncertainty

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Density modification based reliability sensitivity analysis

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