A Synthesis-Component-Based GO-FLOW Modeling Paradigm for Automated Time-Dependent and Phased-Mission Reliability Model Generation and Analysis

被引:0
作者
He, Zhanyu [1 ]
Yang, Jun [1 ]
Chu, Yongyue [2 ]
机构
[1] South China Univ Technol, Sch Elect Power Engn, Guangzhou 510640, Peoples R China
[2] Nucl & Radiat Safety Ctr, Beijing 100082, Peoples R China
基金
中国国家自然科学基金;
关键词
Analytical models; Reliability; Fault trees; Mathematical models; Computational modeling; Data models; Safety; Risk management; Reliability engineering; Automata; Automata modeling; configuration risk management; GO-FLOW methodology; phased-mission system (PMS); piping and instrumentation diagram (P&ID); FAULT-TREE GENERATION; BLOCK DIAGRAMS; SYSTEM;
D O I
10.1109/TR.2024.3462451
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Automatic modeling is an efficient way to ensure the consistency and validity of system reliability and risk models. In this article, an innovative synthesis-component-based modeling paradigm is proposed for automated GO-FLOW model generation from piping and instrumentation diagrams. Within the automata modeling paradigm, a collection of componentized GO-FLOW models for general types and common failure modes of components is first developed to facilitate model transformation mapping. Then, an algorithmic procedure for automated GO-FLOW model generation is elaborated and extended for configuration risk management. Finally, the algorithmic paradigm is demonstrated and verified through comparisons among three different modeling strategies applying to a case study of a simplified safety injection system in pressurized water reactor designs. The comparison results show that the component-based GO-FLOW modeling paradigm is capable of efficient reliability modeling and analysis of time-dependent and phased-mission systems. The consistency, accuracy, and credibility of system reliability and risk models can be effectively guaranteed for configuration risk management with the unified and standardized component-based GO-FLOW modeling paradigm. The automated GO-FLOW model builder is also supportive for reliability-based system design optimization.
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页数:14
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