A Novel Weakest t-Norm based Fuzzy Importance Measure for Fuzzy Fault Tree Analysis of Combustion Engineering Reactor Protection System

Abstract

Recently, a new fuzzy fault tree analysis (FFTA) has been developed to propagate and quantify the epistemic uncertainties occurring in qualitative data such as expert opinions or judgments. It is well known that the weakest triangular norm (Tw) based fuzzy arithmetic operations preserve the shape of the fuzzy numbers, provide more exact fuzzy results and effectively reduce uncertainty range. The objective of this paper is to develop a novel Tw-based fuzzy importance measure to identify the critical basic events in FFTA. The proposed approach has been demonstrated by applying it to a case study to identify the critical components of the Group 1 of the U.S. Combustion Engineering Reactor Protection System (CERPS). The obtained results are then compared to the results computed by the existing well-known importance measures of conventional as well as FFTA. The computed results confirm that the proposed Tw -based importance measure is feasible to identify the critical basic events in FFTA in more exact way.