PSAM 16 Conference Paper Overview
Welcome to the PSAM 16 Conference paper and speaker overview page.
Lead Author: Xiaoyu Zheng Co-author(s): Hitoshi Tamaki, tamaki.hitoshi@jaea.go.jp
Shogo Takahara, takahara.shogo@jaea.go.jp
Tomoyuki Sugiyama, sugiyama.tomoyuki@jaea.go.jp
Yu Maruyama, maruyama.yu@jaea.go.jp
| Uncertainty Analysis of Dynamic PRA Using Nested Monte Carlo Simulations and Multi-Fidelity Models |
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| Uncertainty gives rise to the risk. For nuclear power plants, probabilistic risk assessment (PRA) systematically concludes what people know to estimate the uncertainty, e.g. in the form of risk triplet. However, epistemic uncertainty exists because of a lack of knowledge and simplification. Capable of developing a definite risk profile for decision making under uncertainty, dynamic PRA widely uses more explicit modeling techniques such as simulation to generate scenarios, estimate likelihood/probability and evaluate consequences. The paper tries to analyze the uncertainties in PRA using iterative Monte Carlo simulation of a boiling water reactor (BWR) plant. To alleviate the computational burden of Monte Carlo simulation, multi-fidelity models are introduced to the dynamic PRA. Authors propose to use a multi-fidelity Monte Carlo method with adaptive model selection between high-fidelity model (MELCOR 2.2) and low-fidelity model (machine learning). As a result, the analysis is expected to provide uncertainty information from the perspectives of neglected accident scenarios, probability distribution estimation, and variations of key results such as timings of core damage and source term release. |
Paper ZH9 Preview
Author and Presentation Info
Lead Author Name: Xiaoyu Zheng (zheng.xiaoyu@jaea.go.jp)
Bio: Xiaoyu Zheng got his PhD degree from Osaka University of Japan in 2013. Since then, he has been participating in nuclear safety researches at JAEA. He specializes in severe accident source term analysis and probabilistic risk assessment. In recent years, he focuses on investigating dynamic PRA approaches and developing tools to support risk-informed decision making for Nuclear Regulation Authority (NRA) of Japan.
Country: Japan
Company: Japan Atomic Energy Agency
Job Title: Assistant Principal Researcher
Bio: Xiaoyu Zheng got his PhD degree from Osaka University of Japan in 2013. Since then, he has been participating in nuclear safety researches at JAEA. He specializes in severe accident source term analysis and probabilistic risk assessment. In recent years, he focuses on investigating dynamic PRA approaches and developing tools to support risk-informed decision making for Nuclear Regulation Authority (NRA) of Japan.
Country: Japan
Company: Japan Atomic Energy Agency
Job Title: Assistant Principal Researcher