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This paper presents a comprehensive review of Probabilistic Safety Assessment (PSA), emphasizing its recent advancement and prospective research topics. The study explores the historical evolution and recent progress of PSA within the domain of nuclear safety. Key methodologies are reviewed, including approaches such as Dynamic Probabilistic Risk Assessment (DPRA) and Living Probabilistic Safety Assessment (LPSA), which aim to enhance system reliability and adaptability. Finally, the paper evaluates the challenges confronting PSA and delineates its ongoing and future development with intelligent algorithms, such as CNN, LSTM. DPRA would play an increasingly pivotal role in the real-time monitoring and risk assessment of nuclear safety systems.

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Review of Dynamic Probabilistic Risk Assessment with Intelligence Algorithms for Nuclear Safety Analysis

  • 会议论文

  • 发表日期：

    2026年

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  • Zihan Zhou,
  • Anqi Xu,
  • Xiaomeng Dong,
  • Ming Yang,
  • Linfeng Li,
  • Ting Wen,
  • Ziwei Weng,
  • Guoming Yin

摘要

This paper presents a comprehensive review of Probabilistic Safety Assessment (PSA), emphasizing its recent advancement and prospective research topics. The study explores the historical evolution and recent progress of PSA within the domain of nuclear safety. Key methodologies are reviewed, including approaches such as Dynamic Probabilistic Risk Assessment (DPRA) and Living Probabilistic Safety Assessment (LPSA), which aim to enhance system reliability and adaptability. Finally, the paper evaluates the challenges confronting PSA and delineates its ongoing and future development with intelligent algorithms, such as CNN, LSTM. DPRA would play an increasingly pivotal role in the real-time monitoring and risk assessment of nuclear safety systems.