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

摘要

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.