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久保 光太郎; Zheng, X.; 田中 洋一; 玉置 等史; 杉山 智之; Jang, S.*; 高田 孝*; 山口 彰*
Proceedings of 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL 2020 and PSAM-15) (Internet), p.2279 - 2286, 2020/11
確率論的リスク評価(PRA)は巨大かつ複雑なシステムをリスクを評価する手法の1つである。従来のPRA手法を用いて外部事象のリスクを評価する場合、構造物、系統及び機器の機能喪失時刻の取扱いが困難である。この解決策として、熱水力解析と外部事象評価シミュレーションをRAPID (Risk Assessment with Plant Interactive Dynamics)コードを用いて結合した。外部事象としてPWRプラントにおけるタービン建屋内での内部溢水を選定し、溢水進展評価にはベルヌーイ則に式を用いた。また、溢水源の流量及び緩和設備の没水基準に関する不確実さを考慮した。回復操作については、運転員による溢水源の隔離とポンプによる排水を仮定とともにモデル化した。結果として、隔離操作が排水と組み合わせることによりより有効になることが示された。
Zheng, X.; Mandelli, D.*; Alfonsi, A.*; Smith, C.*; 杉山 智之
Proceedings of 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL 2020 and PSAM-15) (Internet), p.2176 - 2183, 2020/11
The paper introduces a simulation-based Level 2 probabilistic risk assessment (PRA) of a multi-unit nuclear power plant. We propose the methodology by quantifying risk for a station-blackout accident scenario, initialized by a loss-of-offsite-power event. Contrary to classical PRA that applies static models such as event-tree/fault-tree, the analysis is seamlessly integrated with mechanistic simulation and PRA models, including: (1) a simplified thermal-hydraulic code for simulating system behaviors; (2) a Markovian model for the failure mechanism of decay-heat-removal systems, to investigate the interaction between mechanistic simulation and reliability analysis; and (3) classical containment event trees for evaluating containment performances and hydrogen-explosion risk under severe accident conditions. All dynamic and static models, including plant dependencies, are unified within the RAVEN computational framework, applying RAVEN components, External Model, Ensemble Model, and PRA Plugins. The study demonstrates an integrated assessment of risks by considering accident progression and inter-unit system interactions, both time dependent. Statistical data analysis is used to quantifying risk metrics, including core damage frequencies, large early release frequencies and plant damage status. The methodology pertains to modern risk-analysis methodologies such as risk-informed safety margin characterization (RISMC) and dynamic PRA.
田中 洋一; 玉置 等史; Zheng, X.; 杉山 智之
Proceedings of 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference (ESREL 2020 and PSAM-15) (Internet), p.2195 - 2201, 2020/11
One advantage of dynamic probabilistic risk assessment (PRA) is that it can take into account the timing and ordering of event occurrences based on more explicit simulation of system dynamics. It is expected that dynamic PRA can lead us into a more realistic risk assessment, overcoming some limitations of conventional PRA. Multiple dynamic PRA tools have been developed worldwide, and applied to risk assessment of large industrial facilities such as nuclear power plants and crewed spacecrafts. Japan Atomic Energy Agency has developed the dynamic PRA tool, RAPID (Risk Assessment with Plant Interactive Dynamics), considering the interaction between accident simulation and dysfunctional models of safety-related systems. This paper introduces a recent enhancement of RAPID to treat more complicated simulation interactions from the outside of severe accident codes. It is designed to feed back and forth plant information from simulators to the accident sequence generator. It discusses how the enhancement affects the results of risk assessment, with an example analyzing thermal failure of a safety relief valve in a station blackout accident occurred at a boiling water reactor plant.
