Prediction techniques for passive systems' probability of failure

This work fits into the wider framework of the on-going debate centered on Passive System reliability. Its aim is to provide insights into the design of a dependable method to evaluate the reliability of Passive Systems. In order to achieve this, a method is proposed that focuses on the identification of the fundamental parameters that are critical in leading the system to failure. The selection of these parameters was done through the use of Latin Hypercube Sampling (LHS) combined with an analysis centered on the use of two statistical tools, Logistic Regression and the Classification Tree. The results yielded by this study, made it necessary to perform a systematic statistical evaluation of the efficiency of the LHS when used in the context of sensitivity analyses. The study was conducted via the visual and statistical investigation of the scatter-plots derived from the propagation of the uncertainties associated with the fundamental parameters of the plant. In order to validate the proposed method, two examples involving a Gas Fast Reactor (GFR) plant have been set up. The two examples differ, among other aspects, in the number of realizations, M, used to carry out the analyses. The first example - used to illustrate the method - is a representation of the core derived from the application of System Dynamics modeling. The second example is a RELAP5-3D model of a two-loop passive Decay Heat Removal system of the GFR. This case was designed in order to test the method in a more realistic scenario. Important findings about the applicability of the method as a function of M, are given by way of comparison between the results obtained from the two cases. The results reveal that the numbers of realizations, provided by LHS, are insufficient when used to predict and interpret the propagation of the failures in the plant.

Department dc:contributor.department

Massachusetts Institute of Technology. Dept. of Nuclear Science and Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2007

Author dc:creator

• Cavalieri d'Oro, Edoardo

Advisor dc:contributor.advisor

• Michael Golay.

• Nuclear Science and Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/44778

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/44778