Optimal Uncertainty Quantification of a risk measurement from a thermal-hydraulic code using Canonical Moments

Abstract : We study an industrial computer code related to nuclear safety. A major topic of interest is to assess the uncertainties tainting the results of a computer simulation. In this work we gain robustness on the quantification of a risk measurement by accounting for all sources of uncertainties tainting the inputs of a computer code. To that extent, we evaluate the maximum quantile over a class of distributions defined only by constraints on their moments. Two options are available when dealing with such complex optimization problems: one can either optimize under constraints; or preferably, one should reformulate the objective function. We identify a well suited parameterization to compute the optimal quantile based on the theory of canonical moments. It allows an effective, free of constraints, optimization.
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https://hal.archives-ouvertes.fr/hal-01987449
Contributor : Jerome Stenger <>
Submitted on : Tuesday, August 20, 2019 - 11:20:49 AM
Last modification on : Monday, September 2, 2019 - 3:25:33 PM

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  • HAL Id : hal-01987449, version 2
  • ARXIV : 1901.07903

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Jerome Stenger, Fabrice Gamboa, Merlin Keller, Bertrand Iooss. Optimal Uncertainty Quantification of a risk measurement from a thermal-hydraulic code using Canonical Moments. 2019. ⟨hal-01987449v2⟩

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