Probabilistic Safety Assessment and Management of Nuclear Facilities

A special issue of Journal of Nuclear Engineering (ISSN 2673-4362).

Deadline for manuscript submissions: 15 September 2025 | Viewed by 1795

Special Issue Editors

Special Issue Information

Dear Colleagues,

The probabilistic safety assessment and management of nuclear facilities must be rigorous and reliable to support robust design practices and informed decision-making. This Special Issue aims to present recent advancements in the methodologies and techniques used in reliability and safety analyses and the quantitative risk assessment and management of nuclear facilities and systems. Topics of interest include, but are not limited to, the following:

  • Risk assessment methods;
  • Internal-event risk assessments;
  • External- and natural-hazard risk assessments;
  • Climate change risk assessments;
  • Uncertainty and sensitivity analyses;
  • Active and passive system reliability;
  • Structural reliability and health management;
  • Disaster management;
  • Resilience engineering;
  • Physical and cyber security;
  • Risk-based decision-making processes.

This Special Issue is inspired by the works presented at the PSAM17&ASRAM2024 Conference held in Sendai, Japan, from October 7 to 11, 2024. Extended versions of selected works presented at that conference will be considered. Contributions from other researchers and practitioners beyond the conference participants are also welcome.

Prof. Dr. Enrico Zio
Dr. Ibrahim Ahmed
Guest Editors

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Keywords

  • probabilistic safety assessment
  • risk management
  • reliability
  • safety
  • nuclear facilities
  • nuclear systems

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Published Papers (3 papers)

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Research

18 pages, 2029 KiB  
Article
Development of Importance Measures Reflecting the Risk Triplet in Dynamic Probabilistic Risk Assessment: A Case Study Using MELCOR and RAPID
by Xiaoyu Zheng, Hitoshi Tamaki, Yasuteru Sibamoto, Yu Maruyama, Tsuyoshi Takada, Takafumi Narukawa and Takashi Takata
J. Nucl. Eng. 2025, 6(3), 21; https://doi.org/10.3390/jne6030021 - 28 Jun 2025
Viewed by 112
Abstract
While traditional risk importance measures in probabilistic risk assessment are effective for ranking safety-significant components, they often overlook critical aspects such as the timing of accident progression and consequences. Dynamic probabilistic risk assessment offers a framework to quantify such risk information, but standardized [...] Read more.
While traditional risk importance measures in probabilistic risk assessment are effective for ranking safety-significant components, they often overlook critical aspects such as the timing of accident progression and consequences. Dynamic probabilistic risk assessment offers a framework to quantify such risk information, but standardized approaches for estimating risk importance measures remain underdeveloped. This study addresses this gap by: (1) reviewing traditional risk importance measures and their regulatory applications, highlighting their limitations, and introducing newly proposed risk-triplet-based risk importance measures, consisting of timing-based worth, frequency-based worth, and consequence-based worth; (2) conducting a case study of Level 2 dynamic probabilistic risk assessment using the Japan Atomic Energy Agency’s RAPID tool coupled with the severe accident code of MELCOR 2.2 to simulate a station blackout scenario in a boiling water reactor, generating probabilistically sampled sequences with quantified timing, frequency, and consequence of source term release; (3) demonstrating that the new risk importance measures provide differentiated insights into risk significance, enabling multidimensional prioritization of systems and mitigation strategies; for example, the timing-based worth quantifies the delay effect of mitigation systems, and the consequence-based worth evaluates consequence-mitigating potential. This study underscores the potential of dynamic probabilistic risk assessment and risk-triplet-based risk importance measures to support risk-informed and performance-based regulatory decision-making, particularly in contexts where the timing and severity of accident consequences are critical. Full article
(This article belongs to the Special Issue Probabilistic Safety Assessment and Management of Nuclear Facilities)
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14 pages, 2534 KiB  
Article
Dynamic Probabilistic Risk Assessment of Passive Safety Systems for LOCA Analysis Using EMRALD
by Saikat Basak and Lixuan Lu
J. Nucl. Eng. 2025, 6(2), 18; https://doi.org/10.3390/jne6020018 - 13 Jun 2025
Viewed by 300
Abstract
This research explores Dynamic Probabilistic Risk Assessment (DPRA) using EMRALD to evaluate the reliability and safety of passive safety systems in nuclear reactors, with a focus on mitigating Loss of Coolant Accidents (LOCAs). The BWRX-300 Small Modular Reactor (SMR) is used as an [...] Read more.
This research explores Dynamic Probabilistic Risk Assessment (DPRA) using EMRALD to evaluate the reliability and safety of passive safety systems in nuclear reactors, with a focus on mitigating Loss of Coolant Accidents (LOCAs). The BWRX-300 Small Modular Reactor (SMR) is used as an example to illustrate the proposed DPRA methodology, which is broadly applicable for enhancing traditional Probabilistic Safety Assessment (PSA). Unlike static PSA, DPRA incorporates time-dependent interactions and system dynamics, allowing for a more realistic assessment of accident progression. EMRALD enables the modelling of system failures and interactions in real time using dynamic event trees and Monte Carlo simulations. This study identifies critical vulnerabilities in passive safety systems and quantifies the Core Damage Frequency (CDF) under LOCA scenarios. The findings demonstrate the advantages of DPRA over traditional PSA in capturing complex failure mechanisms and providing a more comprehensive and accurate risk assessment. The insights gained from this research contribute to improving passive safety system designs and enhancing nuclear reactor safety strategies for next-generation reactors. Full article
(This article belongs to the Special Issue Probabilistic Safety Assessment and Management of Nuclear Facilities)
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12 pages, 1640 KiB  
Article
Probabilistic Approach for Best Estimate of Fuel Rod Fracture During Loss-of-Coolant Accident
by Hiroki Tanaka, Takafumi Narukawa and Takashi Takata
J. Nucl. Eng. 2025, 6(1), 6; https://doi.org/10.3390/jne6010006 - 28 Feb 2025
Viewed by 609
Abstract
Nuclear power plant risk assessments rely on conservative deterministic criteria for core-damage determination despite significant advancements in plant response and system analyses. This study proposes a probabilistic approach to determine fuel rod fracture during loss-of-coolant accidents (LOCAs) in light-water reactors, addressing the need [...] Read more.
Nuclear power plant risk assessments rely on conservative deterministic criteria for core-damage determination despite significant advancements in plant response and system analyses. This study proposes a probabilistic approach to determine fuel rod fracture during loss-of-coolant accidents (LOCAs) in light-water reactors, addressing the need for more rational and realistic assessments. The methodology integrates a fuel rod fracture probability estimation model with best-estimate-plus-uncertainty analysis of plant response, utilizing the stress–strength model and Monte Carlo simulations. Both stress and strength distributions are estimated through Bayesian statistical modeling, with numerical integration techniques implemented to enhance accuracy for low-frequency events. The application of this approach to a virtual dataset demonstrated that while conventional deterministic methods indicated definitive rod fracture, our probabilistic analysis revealed a more realistic fracture probability of 15.1%. This significant finding highlights the potential reduction in assessment conservatism. The proposed methodology enables a transition from conservative binary evaluations to more realistic probabilistic assessments of core damage, providing more accurate risk insights for decision-making. Full article
(This article belongs to the Special Issue Probabilistic Safety Assessment and Management of Nuclear Facilities)
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