Expert Insights into Challenges in the Probabilistic Risk Assessment for Advanced Nuclear Power Technologies

The nuclear industry is advancing the design and deployment of new reactor technologies that incorporate safety-enhancing features. Meanwhile, weather-driven natural hazards can disrupt the operation of nuclear power plants (NPPs). Studies have indicated that the intensity, persistence, and frequency of these hazards are likely to increase over time. Given the limited operational experience with advanced nuclear technologies, it is essential to develop strategies to evaluate their safety and potential vulnerabilities under natural hazard conditions.To address these issues, we conducted a literature review and distributed a questionnaire to practitioners to gather insights into the effects of weather-related hazards on NPPs and the challenges of performing probabilistic risk assessments (PRAs) for advanced reactors. The collected responses were analyzed and synthesized to provide a consolidated perspective from the PRA community.Based on the respondents’ judgments, natural hazards capable of inundating NPP systems (e.g. flooding, severe storms, and hurricanes) are generally considered most significant for the safety of NPPs. These findings suggest respondents view the primary difficulties in developing a PRA for advanced reactors stemming from evolving designs and emerging technologies, rather than from limitations in the current PRA tools, techniques, standards, or guidance. Ultimately, these expert insights can inform research and development efforts aimed at enhancing PRA methods for advanced reactors.

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Publication Details

Journal
Nuclear Science and Engineering
Published
2026-07-17
DOI
https://doi.org/10.1080/00295639.2026.2690569
Primary Topic
Risk and Safety Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Expert Insights into Challenges in the Probabilistic Risk Assessment for Advanced Nuclear Power Technologies

Michelle Bensi, Jennifer L. Irish, Kaveh Faraji Najarkolaie, Mohammad Modarres et al.
Nuclear Science and Engineering
Risk and Safety Analysis
article

Expert Insights into Challenges in the Probabilistic Risk Assessment for Advanced Nuclear Power Technologies

Michelle Bensi, Jennifer L. Irish, Kaveh Faraji Najarkolaie, Mohammad Modarres, Yunfei Zhao
article en

Abstract

The nuclear industry is advancing the design and deployment of new reactor technologies that incorporate safety-enhancing features. Meanwhile, weather-driven natural hazards can disrupt the operation of nuclear power plants (NPPs). Studies have indicated that the intensity, persistence, and frequency of these hazards are likely to increase over time. Given the limited operational experience with advanced nuclear technologies, it is essential to develop strategies to evaluate their safety and potential vulnerabilities under natural hazard conditions.To address these issues, we conducted a literature review and distributed a questionnaire to practitioners to gather insights into the effects of weather-related hazards on NPPs and the challenges of performing probabilistic risk assessments (PRAs) for advanced reactors. The collected responses were analyzed and synthesized to provide a consolidated perspective from the PRA community.Based on the respondents’ judgments, natural hazards capable of inundating NPP systems (e.g. flooding, severe storms, and hurricanes) are generally considered most significant for the safety of NPPs. These findings suggest respondents view the primary difficulties in developing a PRA for advanced reactors stemming from evolving designs and emerging technologies, rather than from limitations in the current PRA tools, techniques, standards, or guidance. Ultimately, these expert insights can inform research and development efforts aimed at enhancing PRA methods for advanced reactors.

Nuclear Science and Engineering
University of Maryland, College Park (US), Virginia Tech (US)
U.S. Nuclear Regulatory Commission
Industry, innovation and infrastructure
Openalex Percentile: Top 7%
Risk and Safety Analysis
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