LAUSR

Abstract Uncertainty and sensitivity analyses are required in fuel cycle analyses for studying the viability of electronuclear scenarios by means of their response to variations in the input parameters. This implies that nuclear fuel cycle simulators have to be extended for dealing with this kind of problems in order to become reliable tools. However, given their complexity, the excessive computational effort these analyses demand constraint the ability of the codes to solve the problem without making any approximation. In this work, we propose to use a methodology based on a sparse Polynomial Chaos expansion that, given the low computational demand, makes it possible to be used for sensitivity analyses in any fuel cycle code. This has been applied to a European collaborative advanced scenario where the results have been compared with previous studies with the aim of showing the potential that this technique has when applied to fuel cycle studies.