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Uncertainty and Sensitivity of Neutron Kinetic Parameters in the Dynamic Response of a PWR Rod Ejection Accident Coupled Simulation
Author(s) -
C. Mesado,
Andrés Soler,
T. Barrachina,
R. Miró,
J. Carlos Garcı́a-Dı́az,
Rafael MaciánJuan,
G. Verdú
Publication year - 2012
Publication title -
science and technology of nuclear installations
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.417
H-Index - 24
eISSN - 1687-6083
pISSN - 1687-6075
DOI - 10.1155/2012/625878
Subject(s) - sensitivity (control systems) , uncertainty analysis , nonparametric statistics , parametric statistics , nuclear data , nuclear power plant , engineering , computer science , nuclear engineering , reliability engineering , neutron , mathematics , simulation , statistics , physics , nuclear physics , electronic engineering
In nuclear safety analysis, it is very important to be able to simulate the different transients that can occur in a nuclear power plant with a very high accuracy. Although the best estimate codes can simulate the transients and provide realistic system responses, the use of nonexact models, together with assumptions and estimations, is a source of uncertainties which must be properly evaluated. This paper describes a Rod Ejection Accident (REA) simulated using the coupled code RELAP5/PARCSv2.7 with a perturbation on the cross-sectional sets in order to determine the uncertainties in the macroscopic neutronic information. The procedure to perform the uncertainty and sensitivity (U&S) analysis is a sampling-based method which is easy to implement and allows different procedures for the sensitivity analyses despite its high computational time. DAKOTA-Jaguar software package is the selected toolkit for the U&S analysis presented in this paper. The size of the sampling is determined by applying the Wilks’ formula for double tolerance limits with a 95% of uncertainty and with 95% of statistical confidence for the output variables. Each sample has a corresponding set of perturbations that will modify the cross-sectional sets used by PARCS. Finally, the intervals of tolerance of the output variables will be obtained by the use of nonparametric statistical methods

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