CSAU methodology and results for an ATWS event in a BWR using information theory methods

Highlights: • We apply the CSAU methodology to an ATWS in a BWR using information theory methods. • We show how to perform the selection of the most influential inputs on the critical safety parameter. • We apply the maximum entropy principle to get the input parameter distribution. • We examine the maximum relative entropy principle to update the input parameter PDF. • We quantify the uncertainty of the critical safety parameter using order statistics and information theory. - Abstract: This paper shows an application of the CSAU methodology to an ATWS in a BWR reactor, when the temperature of the suppression pool is taken as the critical safety parameter. The method combines CSAU methodology with recent techniques of information theory. In this paper we use auxiliary tools to help in the evaluation and improvement of the parameters distribution that enter in the elements II and III of CSAU based methodologies. These tools have been implemented in two FORTRAN programs: GEDIPA (Generation of the Parameter Distribution) and UNTHERCO (Uncertainty in Thermal Hydraulic Codes). The first one analyzes the information data available on a given parameter or parameters with the goal to know all the information about the probability distribution function of these parameters. The second apply information theory methods, as the maximum entropy principle (MEP) and the maximum relative entropy Principle (MREP), in order to build conservative distribution functions for the parameters from the available data. Also, the distribution function of a given parameter can be updated using the MREP principle when new information is provided. UNTHERCO performs the MONTECARLO sampling for a given set of parameters when the distribution function of these parameters is previously known. If the distribution of a parameter is unknown, then, the MEP is applied to deduce the distribution function for this parameter