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Probabilistic Safety Assessment and Management of Nuclear Facilities
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Probabilistic Safety Assessment and Management of Nuclear Facilities

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

Deadline for manuscript submissions: closed (15 September 2025) | Viewed by 7733

Special Issue Editors

Prof. Dr. Enrico Zio

grade E-Mail Website
Guest Editor
1. Centre de Recherce sur les Risques et les Crises (CRC), MINES Paris-PSL Université, 06904 Paris, France
2. Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milano, Italy
Interests: risk assessment; reliability analysis; simulation; artificial intelligence; nuclear systems
Special Issues, Collections and Topics in MDPI journals
Dr. Ibrahim Ahmed

E-Mail Website
Guest Editor
Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milano, Italy
Interests: nuclear systems
Special Issues, Collections and Topics in MDPI journals

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

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Nuclear Engineering is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

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

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Published Papers (8 papers)

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Research

14 pages, 3007 KB  
Article
Development of Importance Measures Reflecting the Risk Triplet in Dynamic Probabilistic Risk Assessment: The Concept and Measures of Risk Importance
by Takafumi Narukawa, Takashi Takata, Xiaoyu Zheng, Hitoshi Tamaki, Yasuteru Sibamoto, Yu Maruyama and Tsuyoshi Takada
J. Nucl. Eng. 2025, 6(4), 49; https://doi.org/10.3390/jne6040049 - 26 Nov 2025
Viewed by 141
Abstract
Although dynamic probabilistic risk assessment (PRA) techniques have advanced in their ability to represent the progression of events over time, the formulation of suitable risk importance measures for these methods still poses a substantial challenge. In particular, it is difficult to reflect the [...] Read more.
Although dynamic probabilistic risk assessment (PRA) techniques have advanced in their ability to represent the progression of events over time, the formulation of suitable risk importance measures for these methods still poses a substantial challenge. In particular, it is difficult to reflect the full breadth and multidimensional character of the risk information produced by dynamic PRA. In this study, we introduce a set of new importance measures derived from the risk triplet perspective: (i) Timing-Based Worth (TBW), which expresses diversity in scenario occurrence time; (ii) Frequency-Based Worth (FBW), which captures the probability of different scenarios; and (iii) Consequence-Based Worth (CBW), which characterizes scenario consequences. Formal definitions of these three indices are provided, and a conceptual scheme for integrated importance evaluation is proposed to support multidimensional analysis. As an initial demonstration, TBW and FBW are applied to a simplified reliability case using a dynamic PRA framework built on the continuous Markov chain Monte Carlo (CMMC) approach. This application is used to test their interpretability and the internal consistency of the proposed scheme. The findings suggest that TBW and FBW make it possible to conduct more holistic importance evaluations, taking into account resilience effects and temporal diversity in addition to conventional frequency-based perspectives. Such an extension is expected to increase the usefulness of dynamic PRA outputs for risk-informed decision-making. Full article
(This article belongs to the Special Issue Probabilistic Safety Assessment and Management of Nuclear Facilities)
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16 pages, 3310 KB  
Article
Study on the Influence of Ambient Temperature and RPV Temperature on Operation Performance of HTR-PM Reactor Cavity Cooling System
by Xinsheng Xu, Yiyang Ye, Yingjie Wu and Yanhua Zheng
J. Nucl. Eng. 2025, 6(4), 48; https://doi.org/10.3390/jne6040048 - 21 Nov 2025
Viewed by 265
Abstract
The High Temperature Gas-cooled Reactor (HTGR) is a Generation IV advanced nuclear reactor, which can realize inherent safety and prevent core melt. The Institute of Nuclear and New Energy Technology (INET) of Tsinghua University developed a commercial-scale 200 MWe High Temperature gas-cooled Reactor [...] Read more.
The High Temperature Gas-cooled Reactor (HTGR) is a Generation IV advanced nuclear reactor, which can realize inherent safety and prevent core melt. The Institute of Nuclear and New Energy Technology (INET) of Tsinghua University developed a commercial-scale 200 MWe High Temperature gas-cooled Reactor Pebble bed Module project (HTR-PM), which entered commercial operation on 6 December 2023. A passive Reactor Cavity Cooling System (RCCS) was designed for HTR-PM to export heat from the reactor cavity during normal operation and also in accident conditions, keeping the safety of the reactor pressure vessel (RPV) and reactor cavity. The RCCS of HTR-PM has been designed as three independent sets; the normal operation of two sets of RCCS can guarantee the safety of the PRV and reactor activity. The heat can be transferred from the RPV to the final heat sink atmosphere through thermal radiation and natural convection in the reactor cavity, and the natural circulation of water and air in the RCCS. The CAVCO code was developed by the INET to simulate the behavior of an RCCS. In this paper, assuming different RPV temperatures and different ambient temperatures, as well as assuming all or parts of the RCCS sets work, the performances of RCCS are studied by CAVCO to evaluate its operational reliability, so as to provide a reference for further optimization. The analysis results indicate that even under hypothetically extremely RPV temperatures, two sets of RCCS could effectively remove heat without causing water boiling or system failure. However, during the winter when ambient temperatures are low, particularly when the reactor operates at a lower RPV temperature, additional attention must be given to the operational safety of the system. It is crucial to prevent system failure caused by the freezing of circulating water and the potential cracking of water-cooling pipes due to freezing. Depending on the reactor status and ambient conditions, one or all three sets of RCCS may need to be taken offline. In addition, the maximum heat removal capacity of the RCCS with only two sets operational exceeds the design requirement of 1.2 MW. When the ambient temperature fluctuates significantly, it may be advisable to increase the number of available RCCS sets to mitigate the effect of abrupt changes in cooling water temperature on pipeline thermal stress. Full article
(This article belongs to the Special Issue Probabilistic Safety Assessment and Management of Nuclear Facilities)
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14 pages, 2799 KB  
Article
Application of Dynamic PRA to Nuclear Power Plant Operation Support—Evaluation of Plant Operation Support Using a Simple Plant Model
by Nami Yamamoto, Mami Kagimoto, Yohei Ueno, Takafumi Narukawa and Takashi Takata
J. Nucl. Eng. 2025, 6(4), 46; https://doi.org/10.3390/jne6040046 - 4 Nov 2025
Viewed by 347
Abstract
Following the Great East Japan Earthquake in 2011, there has been an increased focus on risk assessment and the practical application of its findings to safety enhancement. In particular, dynamic probabilistic risk assessment (PRA) used in conjunction with plant dynamics analysis is being [...] Read more.
Following the Great East Japan Earthquake in 2011, there has been an increased focus on risk assessment and the practical application of its findings to safety enhancement. In particular, dynamic probabilistic risk assessment (PRA) used in conjunction with plant dynamics analysis is being considered for accident management (AM) and operational support. Determining countermeasure priorities in AM can be challenging due to the diversity of accident scenarios. In multi-unit operations, the complexity of scenarios increases in cases of simultaneous disasters, which makes establishing response operations priorities more difficult. Dynamic PRA methods can efficiently generate and assess complex scenarios by incorporating changes in plant state. This paper introduces the continuous Markov chain Monte Carlo (CMMC) method, a dynamic PRA approach, as a tool for prioritizing countermeasures to support nuclear power plant operations. The proposed method involves three steps: (1) generating exhaustive scenarios that include events, operator actions, and system responses; (2) classifying scenarios according to countermeasure patterns; and (3) assigning priority based on risk data for each pattern. An evaluation was conducted using a simple plant model to analyze event countermeasure patterns for addressing steam generator tube rupture during single-unit operation. The generated scenario patterns included depressurization by opening a pressurizer relief valve (DP), depressurization via heat removal through the steam generator (DSG), and both operations combined (DP + DSG). The timing of the response operations varied randomly, resulting in multiple scenarios. The assessment, based on reactor pressure vessel water level and the potential for core damage, showed that the time margin to core damage depended on the countermeasure pattern. The findings indicate that the effectiveness of each countermeasure can be evaluated and that it is feasible to identify which countermeasure should be prioritized. Full article
(This article belongs to the Special Issue Probabilistic Safety Assessment and Management of Nuclear Facilities)
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29 pages, 2690 KB  
Article
Initiating Event Frequencies for Internal Flooding and High-Energy Line Break PRAs
by Karl N. Fleming, Bengt O. Y. Lydell, Mary Presley, Ali Mosleh and Wadie Chalgham
J. Nucl. Eng. 2025, 6(3), 37; https://doi.org/10.3390/jne6030037 - 16 Sep 2025
Viewed by 778
Abstract
Utilities that operate nuclear power plants are increasingly using probabilistic risk assessments (PRAs) to make day-to-day decisions on design, operations, and maintenance and to support risk-informed applications. These applications require high-quality and complete PRAs to ensure that the decisions and proposed changes are [...] Read more.
Utilities that operate nuclear power plants are increasingly using probabilistic risk assessments (PRAs) to make day-to-day decisions on design, operations, and maintenance and to support risk-informed applications. These applications require high-quality and complete PRAs to ensure that the decisions and proposed changes are technically well-founded. Such PRAs include the modeling and quantification of PRA models for accident sequences initiated by internal floods and high-energy line breaks. To support PRA updates and upgrades for such sequences, the Electric Power Research Institute (EPRI) has sponsored ongoing research to develop and refine guidance and generic data that can be used to estimate initiating event frequencies for internal flood- and high-energy line break-induced accident sequences. In 2023, EPRI published the fifth revision of a generic database for these initiating event frequencies. This revision produced advancements in the methodology for passive component reliability, including the quantification of aging effects on pipe rupture frequencies and the capability to adjust these frequencies to account for enhancements to integrity management strategies associated with leak inspections and non-destructive examinations. The purpose of this paper is to present these enhancements and illustrate their application with selected examples. Full article
(This article belongs to the Special Issue Probabilistic Safety Assessment and Management of Nuclear Facilities)
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12 pages, 1642 KB  
Article
A Bayesian Approach for Designing Experiments Based on Information Criteria to Reduce Epistemic Uncertainty of Fuel Fracture During Loss-of-Coolant Accidents
by Shusuke Hamaguchi, Takafumi Narukawa and Takashi Takata
J. Nucl. Eng. 2025, 6(3), 35; https://doi.org/10.3390/jne6030035 - 1 Sep 2025
Viewed by 895
Abstract
In probabilistic risk assessment (PRA), the fracture limit of fuel cladding tubes under loss-of-coolant accident conditions plays a critical role in determining the core damage, highlighting the need for accurate modeling of cladding tube fracture behavior. However, for high-burnup cladding tubes, it is [...] Read more.
In probabilistic risk assessment (PRA), the fracture limit of fuel cladding tubes under loss-of-coolant accident conditions plays a critical role in determining the core damage, highlighting the need for accurate modeling of cladding tube fracture behavior. However, for high-burnup cladding tubes, it is often infeasible to conduct extensive experiments due to limited material availability, high costs, and technical constraints. These limitations make it difficult to acquire sufficient data, leading to substantial epistemic uncertainty in fracture modeling. To enhance the realism of PRA results under such constraints, it is essential to develop methods that can effectively reduce epistemic uncertainty using limited experimental data. In this study, we propose a Bayesian approach for designing experimental conditions based on a widely applicable information criterion (WAIC) in order to effectively reduce the uncertainty in the prediction of fuel cladding tube fracture with limited data. We conduct numerical experiments to evaluate the effectiveness of the proposed method in comparison with conventional approaches based on empirical loss and functional variance. Two cases are considered: one where the true and predictive models share the same mathematical structure (Case 1) and one where they differ (Case 2). In Case 1, the empirical loss-based design performs best when the number of added data points is fewer than approximately 10. In Case 2, the WAIC-based design consistently achieves the lowest Bayes generalization loss, demonstrating superior robustness in situations where the true model is unknown. These results indicate that the proposed method enables more informative experimental designs on average and contributes to the effective reduction in epistemic uncertainty in practical applications. Full article
(This article belongs to the Special Issue Probabilistic Safety Assessment and Management of Nuclear Facilities)
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18 pages, 2029 KB  
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
Cited by 1 | Viewed by 1195
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 KB  
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 1727
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 KB  
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 951
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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