Unavailability estimation of shutdown system of a fast reactor by Monte Carlo simulation. (April 2016)

• Record Type: Journal Article
• Authors: Ramakrishnan, M.
• Is Part Of: Annals of nuclear energy. Volume 90(2016:Apr.)
• Page Start: 264
• Page End: 274
• Publication Date: 2016-04
• Subjects: AR absorber rods -- AS actuation system -- BFB balanced failure biasing -- BRE bounded relative error -- CTMC continuous time markov chain -- DBE design basis event -- DIS dynamic importance sampling -- DSL design safety limit -- DTMC discrete time markov chain -- IFB inverse failure biasing -- iid independent identically distributed -- MTTF Mean Time To Failure -- RBD reliability block diagram -- RPS reactor protection system -- SDS shutdown system -- TDCE time dependent cut set evaluation; Unavailability -- Importance sampling -- Markovian systems -- Simple failure biasing -- Balanced failure biasing -- Monte Carlo random walk simulation; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2015.11.031
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: Unavailability estimation of shutdown system through Monte Carlo simulation. Comparison of different Monte Carlo simulation schemes. Integrated process and system hardware simulation of a simple example. Comparison of results of the example system by different methods. Abstract: The safety systems of fast breeder reactors are designed to be highly reliable and have small failure probabilities. Traditionally fault tree technique is employed to analyse such systems. However fault tree approach has limitations in analyzing dependence between components and phased mission objectives. In this paper the application of Monte Carlo simulation technique to estimate the unavailability and Mean Time To Failure of shutdown system of a fast reactor is studied. Different biasing schemes are also compared for performance. Balanced failure biasing scheme gives better variance reduction as compared to simple failure biasing and direct Monte Carlo simulation. The balanced failure biasing scheme for system hardware evolution is integrated with physical process for a simple example system. The probability of crossing the safety limits on temperature is estimated.