现象识别与排序方法的发展与创新
Development and Innovation of Phenomena Identification and Ranking Table Methodology
DOI: 10.12677/NST.2023.111001, PDF,    科研立项经费支持
作者: 姚 垚, 邓程程, 杨 军*：华中科技大学能源与动力工程学院核工程与核技术系，湖北 武汉；陈 伟：中国核动力研究设计院核反应堆系统设计技术国家级重点实验室，四川 成都；宫厚军：国防科技工业核动力技术创新中心，四川 成都
关键词: 现象识别与排序表；CSAU；反应堆安全；事故分析；PIRT； CSAU； Reactor Safety； Accident Analysis
摘要: 现象识别与排序表(PIRT)是一种通过信息整理和专家判断，对核电站工况所涉及的现象按照其重要程度进行识别与排序的分析方法，该方法可让研究侧重于分析较重要的现象，提高安全分析效率。PIRT方法自创立以来不断得到完善与创新，本文基于对PIRT的调研学习，阐述了PIRT的发展历史和其指导意义。同时，针对文本表格形式的PIRT冗长、不够直观等问题，提出了一种以三维阵列图为表现形式的M-PIRT，可以实现可视化和直观查阅。之后，基于M-PIRT从不同角度对重要现象进行了分析，结合华龙一号尝试提出M-PIRT的示范性应用，提出了可能存在的挑战和发展方向。本研究可为今后自主化反应堆设计如华龙一号、国和一号、玲珑一号等PIRT的建立，以及PIRT方法的进一步改进创新提供一定参考。
Abstract: Phenomena Identification and Ranking Table (PIRT) technology is a decision-making methodology by collecting information and expert experience. It can determine the rank of each phenomenon involved in the nuclear power plant accident process according to its importance. PIRT can help researchers focus on more important phenomena to increase the efficiency of safety analysis. PIRT has been improved and innovated continuously since its establishment. Based on the investigation and study of PIRT, this paper expounds the development history of PIRT and its guiding significance. Meanwhile, this paper proposes a form of 3D array diagram called M-PIRT due to the problems of PIRT in the form of text table, such as lengthy and not intuitive, which can realize visualization and intuitive consultation. Afterwards, the important phenomena are analyzed from different angles based on M-PIRT, and possible challenges and development directions are proposed in the context of HPR1000’s attempt to propose a demonstration application of the M-PIRT. This research can provide references for the future design of facilities, the code verification, the establishment of PIRT for domestic reactors such as CAP1400, HPR1000 and ACP100, and the improvement and innovation of PIRT method.
文章引用：姚垚, 陈伟, 宫厚军, 邓程程, 杨军. 现象识别与排序方法的发展与创新[J]. 核科学与技术, 2023, 11(1): 1-13. https://doi.org/10.12677/NST.2023.111001

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