Uncertainty and sensitivity analysis of functional risk curves based on Gaussian processes

Published: Apr 3, 2017
Abstract
A functional risk curve gives the probability of an undesirable event as a function of the value of a critical parameter of a considered physical system. In several applicative situations, this curve is built using phenomenological numerical models which simulate complex physical phenomena. To avoid cpu-time expensive numerical models, we propose to use Gaussian process regression to build functional risk curves. An algorithm is given to provide...
Paper Details
Title
Uncertainty and sensitivity analysis of functional risk curves based on Gaussian processes
Published Date
Apr 3, 2017
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