Probabilistic Risk Assessment and Management for Engineers and Scientists
Completely updated and revised, this modern, computer-based text. helps develop synthesis and analysis methods for risk and reliability studies from fundamental principles, and apply them to realistic industrial-level problems. The full treatment of qualitative analysis methods includes: fault trees, FMEA, event trees, decision labels, cause-consequence charts and common-mode failures. In addition, quantitative system analysis techniques - kinetic tree theory, cut set and prime implicant analysis and Markov and Monte Carlo methods - are thoroughly covered and developed.
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ACCIDENT MECHANISMS AND RISK
PROBABILISTIC RISK ASSESSMENT
2 Chain Rule
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accident sequence analysis aperture Assume basic events Bayes theorem beta distribution calculated cause common-cause component failure conditional probability confidence interval Consider coolant denotes density device diagram distribution equation equipment event tree Example expected number fails failure intensity failure mode failure probability failure rate fatalities fault tree fault-tree Flow Rate frequency function gate HAZOPS human errors human reliability initiating event input likelihood log-normal distribution lower bound minimal cut sets module MOVs MTTF node normal normal distribution nuclear power plant number of failures obtained occurs offsite operation outcome parameters path sets population pressure probabilistic probabilistic risk assessment procedure pump quantification random variable reactor reliability risk profile safety systems sample semantic network sensor shown in Figure shutdown source-term standby structure function Student's t distribution switch system failure system unavailability Table tank task top event tree of Figure valve variance Venn diagram zero