AN OVERVIEW OF RISK QUANTIFICATION ISSUES FOR DIGITALIZED NUCLEAR POWER PLANTS USING A STATIC FAULT TREE

Risk caused by safety-critical instrumentation and control (I&C) systems considerably affects overall plant risk. As digitalization of safety-critical systems in nuclear power plants progresses, a risk model of a digitalized safety system is required and must be included in a plant safety model...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Nuclear engineering and technology 2009, Vol.41 (6), p.849-858
Hauptverfasser: Kang, Hyun-Gook, Kim, Man-Cheol, Lee, Seung-Jun, Lee, Ho-Jung, Eom, Heung-Seop, Choi, Jong-Gyun, Jang, Seung-Cheol
Format: Artikel
Sprache:kor
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Risk caused by safety-critical instrumentation and control (I&C) systems considerably affects overall plant risk. As digitalization of safety-critical systems in nuclear power plants progresses, a risk model of a digitalized safety system is required and must be included in a plant safety model in order to assess this risk effect on the plant. Unique features of a digital system cause some challenges in risk modeling. This article aims at providing an overview of the issues related to the development of a static fault-tree-based risk model. We categorize the complicated issues of digital system probabilistic risk assessment (PRA) into four groups based on their characteristics: hardware module issues, software issues, system issues, and safety function issues. Quantification of the effect of these issues dominates the quality of a developed risk model. Recent research activities for addressing various issues, such as the modeling framework of a software-based system, the software failure probability and the fault coverage of a self monitoring mechanism, are discussed. Although these issues are interrelated and affect each other, the categorized and systematic approach suggested here will provide a proper insight for analyzing risk from a digital system.
ISSN:1738-5733
2234-358X