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

01/22/2019
by   Jerome Stenger, et al.
0

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.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset