Reliability And Probabilistic Safety Assessment In Multi Unit Nuclear Power Plants

Reliability and Probabilistic Safety Assessment in Multi-Unit Nuclear Power Plants presents the risk contributions from single and multi-unit Nuclear Power Plants to help aggregate the risks that may arise due to applicable hazards and operating states. The book combines the key features of multi-unit risk assessment in one resource, reviewing the practices adopted in various countries around the globe to exemplify the dependencies between units on a site. These dependencies include multi-unit interactions, environmental stresses, the sharing of systems, and the sharing of human resource in a control room, factors which can all introduce an increase potential for heightened accident conditions. This book helps readers systematically identify events and evaluate techniques of possible accident outcomes within multi-units. It serves as a ready reference for PSA analysts in identifying a suitable site and the sharing of resources, while carrying out multi-unit risk assessments to ensure the safety of the public and the environment. It will also be valuable for nuclear researchers, designers and regulators of nuclear power plants, nuclear regulatory agencies, PSA engineers and practicing safety professionals. Provides a framework for nuclear and PSA researchers and professionals on the design and operation of multi-unit risk assessments Reviews practices adopted in various regions around the globe to analyze dependencies between units Includes modeling techniques of inter-connections and shared resources, as well as risk aggregation

The accident at the Fukushima Daiichi Nuclear Power Plant underlined the need to assess the nuclear safety of multi-unit sites considering the accident sequences involving more than one reactor units on site. The objective of this Safety Report is to provide a methodology for the development of a Multi-unit Probabilistic Safety Assessment (MUPSA). It provides practical examples and an overview of the actual state of practice in this area. The publication provides a detailed description of Level 1 MUPSA methodology, the principles of development of Level 2 MUPSA models and the path forward for multi-unit consequence analysis (Level 3 MUPSA). In addition, it summarizes the experience available in Member States in the area of MUPSA. The scope of this Safety Report includes consideration of various hazards and plant operational states normally considered in PSA development in the multi-unit context.

Probabilistic Safety Assessment (PSA) is a structured, comprehensive, and logical analysis method aimed at identifying and assessing risks in complex technological systems, such as the nuclear power plants. It is also known as probabilistic risk assessment – PRA. This book presents the theoretical basis to understand the numerous and complex aspects that are covered by PSA and it will help the reader to better understand and to effectively manage risks. The book provides PSA methods and techniques and it includes recommended procedures that are based on the experience of the authors and applicable to different levels and types of PSA that are used for nuclear power plants applications. It can be used as extra reading for PSA courses for practitioners and it provides quantitative risk methodology documentation for PSA.

This publication outlines the generic methodology for probabilistic safety assessment (PSA) of nuclear power plants (NPPs) against external hazards. It integrates design, procedural, operational, human factors and both protection and mitigation aspects that are essential to model a NPP response to an external hazard and to assess the associated risk. It specifically addresses the identification and screening of external hazards considering the multi-unit impact.

The technical approach described in this publication builds on the use of a single unit probabilistic safety assessment (PSA) and identifies considerations that are needed from the multi-unit perspective. This is the first attempt to expand the current PSA process to take account of multi-unit issues, and has been done by distilling lessons learned from the Fukushima Daiichi accident and other multi-unit events, and by reviewing previous PSAs and supporting research that have addressed the risks of multi-unit accidents. The publication provides a roadmap and methodology for performing a multi-unit PSA, proposes a set of site level risk metrics, and presents examples of approaches to resolve specific issues.

The book has been developed in conjunction with NERS 462, a course offered every year to seniors and graduate students in the University of Michigan NERS program. The first half of the book covers the principles of risk analysis, the techniques used to develop and update a reliability data base, the reliability of multi-component systems, Markov methods used to analyze the unavailability of systems with repairs, fault trees and event trees used in probabilistic risk assessments (PRAs), and failure modes of systems. All of this material is general enough that it could be used in non-nuclear applications, although there is an emphasis placed on the analysis of nuclear systems. The second half of the book covers the safety analysis of nuclear energy systems, an analysis of major accidents and incidents that occurred in commercial nuclear plants, applications of PRA techniques to the safety analysis of nuclear power plants (focusing on a major PRA study for five nuclear power plants), practical PRA examples, and emerging techniques in the structure of dynamic event trees and fault trees that can provide a more realistic representation of complex sequences of events. The book concludes with a discussion on passive safety features of advanced nuclear energy systems under development and approaches taken for risk-informed regulations for nuclear plants.

Presents a practical approach for incorporating human reliability analysis (HRA) into probabilistic safety assessment (PSA). This document describes the steps needed and the documentation that should be provided both to support the PSA itself and to ensure effective communication of important information arising from the studies.