^{a}, José Felipe Villanueva

^{b}, Sebastián Martorell

^{c}, Sofia Carlos

^{d}, and Isabel Martón

^{e}

^{a}aisanche@eio.upv.es

^{b}jovillo0@iqn.upv.es

^{c}smartore@iqn.upv.es

^{d}scarlos@iqn.upv.es

^{e}ismarllu@upv.es

The International Atomic Energy Agency's guidance on the use of deterministic safety analysis for the design and licensing of nuclear power plants, addresses four options for Deterministic Safety Analysis applications. In Option 3, the use of best-estimate codes and data together with an evaluation of the uncertainties is considered, the so-called Best Estimated Plus Uncertainty (BEPU) methodologies. The most popular statistical method used in BEPU is the Wilks' method. The use of the Wilks' method and first order statistics mostly leads to conservative results. An alternative to solve this problem is the use of parametric methods which assume the data are coming from a particular parametric model. However, the problem with this alternative is that the parametric tolerance intervals can be sensitive, in terms of the coverage and confidence level, to the model misspecification. In this paper a generalized lambda distribution is used to fit the data and estimate a parametric tolerance interval. The Wilk's method and the parametric method are applied in the uncertainty analysis of a Large-Break Loss of Coolant Accident in the cold leg of a Pressurized Water Reactor using the thermal-hydraulic system code TRACE. The results obtained are compared with respect to (a) the average coverage probability, (b) coefficient of Variation, and c) bias.