Development of probabilistic risk assessment methodology using artificial intelligence technology, 2; Automatic fault detection method for building reliability database

Ujita, Hiroshi*; Morimoto, Tatsuya*; Futagami, Satoshi; Yamano, Hidemasa; Kurisaka, Kenichi

Proceedings of PSAM 2023 Topical Conference AI & Risk Analysis for Probabilistic Safety/Security Assessment & Management, 8 Pages, 2023/10

This study is intended to develop PRA methodology using the AI technology. For this purpose, as a first step, the authors have been conducting a three-year program including the development of AI tools for automatic fault tree (FT) creation and automatic fault detection methodology for building reliability database. These AI tools are intended to enable any users to easily perform PRA with the same quality without user effect. For the automatic fault detection method, The AI tool is developed for extracting failure occurrence locations (system/equipment), failure modes, and causes from Japanese reliability databases of NUCIA(for light water reactors) and CORDS(for sodium-cooled fast reactors), and transforming them into a database using AI technologies.