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International Journal for Uncertainty Quantification
Импакт фактор: 4.911 5-летний Импакт фактор: 3.179 SJR: 1.008 SNIP: 0.983 CiteScore™: 5.2

ISSN Печать: 2152-5080
ISSN Онлайн: 2152-5099

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International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.2020030800
pages 35-53

OPTIMAL UNCERTAINTY QUANTIFICATION OF A RISK MEASUREMENT FROM A THERMAL-HYDRAULIC CODE USING CANONICAL MOMENTS

Jerome Stenger
EDF R&D, 6 quai Watier, 78401 Chatou, France; Université Paul Sabatier, 118 route de Narbonne, 31400 Toulouse, France
Fabrice Gamboa
Université Paul Sabatier, 118 route de Narbonne, 31400 Toulouse, France; Artificial and Natural Intelligence Toulouse Institute (ANITI), France
M. Keller
EDF R&D, 6 quai Watier, 78401 Chatou, France
Bertrand Iooss
EDF R&D, 6 quai Watier, 78401 Chatou, France; Université Paul Sabatier, 118 route de Narbonne, 31400 Toulouse, France

Краткое описание

In uncertainty quantification studies, a major topic of interest lies in assessing the uncertainties tainting the results of a computer simulation. In this work we seek to 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 end, we evaluate the maximum quantile over a class of bounded distributions satisfying moments constraint. 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 maximal quantile based on the theory of canonical moments. It allows an effective, free of constraints, optimization. This methodology is applied to an industrial computer code related to nuclear safety.

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