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RESULTS OF A PHENOMENA IDENTIFICATION AND RANKING TABLE (PIRT) EXERCISE FOR A SEVERE ACCIDENT IN A SMALL MODULAR HIGH-TEMPERATURE GAS-COOLED REACTOR
Author(s) -
David Hummel,
Yu-Shan Chin,
Andrew A. Prudil,
Anthony Williams,
Eugene Masala,
Geoffrey Waddington,
Matthew Edwards,
Pamela Yakabuskie,
Tariq Jafri,
Thuy Duong Tran,
Xianmin Huang,
Zhe Liang
Publication year - 2019
Publication title -
cnl nuclear review
Language(s) - English
Resource type - Journals
eISSN - 2369-6931
pISSN - 2369-6923
DOI - 10.12943/cnr.2019.00006
Subject(s) - ranking (information retrieval) , modular design , identification (biology) , process (computing) , limiting , table (database) , computer science , nuclear engineering , risk analysis (engineering) , operations research , engineering , data mining , mechanical engineering , business , machine learning , botany , biology , operating system
Canada has attracted specific interest from developers of nonwater-cooled small modular reactor (SMR) technologies, including concepts based on high-temperature gas-cooled reactors (HTGRs). It is anticipated that some research and development (R&D) will be necessary to support safety analysis and licensing of these reactors in Canada. The Phenomena Identification and Ranking Table (PIRT) process is a formalized method in which a panel of experts identifies which physical phenomena are most relevant to the reactor safety analysis and how well understood these phenomena are. The PIRT process is thus a tool to assess current knowledge levels and (or) predictive capabilities of models, thus providing direction to a focused R&D program. This paper summarizes the results of a PIRT process performed by a panel of experts at Canadian Nuclear Laboratories for a limiting or “worst-case” accident scenario at a generic HTGR-type SMR. Suggestions are given regarding the highest priority R&D items to support severe accidents analysis of these reactors.

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