LAPSE:2023.32057
Published Article

LAPSE:2023.32057
Probabilistic Flood Assessment Methodology for Nuclear Power Plants Considering Extreme Rainfall
April 19, 2023
Abstract
Abnormal weather conditions due to climate change are currently increasing on both global and local scales. It is therefore important to ensure the safety of the areas where major national facilities are located by analyzing risk quantitatively and re-evaluating the existing major facilities, such as nuclear power plants, considering the load and capacity of extreme flood conditions. In this study, a risk analysis method is developed that combines flood hazard curves with fragility curves using hydraulic and hydrological models by GIS tools and the @RISK model for the probabilistic flood analysis of nuclear power plant sites. A two-dimensional (2D) analysis is first carried out to estimate flood depths in various watershed scenarios, and a representative hazard curve for both external and internal flooding is made by applying a verified probability distribution type for the flood watersheds. For the analysis of flooding within buildings, an internal grid is constructed using GIS with related design drawings, and based on the flood depth results of the 2D analysis, a hazard curve for the representative internal inundation using a verified probability distribution type is presented. In the present study, walkdowns with nuclear experts are conducted around the nuclear power plant area to evaluate the fragile structures and facilities under possible flooding. After reviewing the 2D inundation analysis results based on the selected major equipment and facilities, the zones requiring risk assessment are re-assigned. A fragility curve applying probability distribution for the site’s major equipment and facilities is also presented. Failure risk analysis of the major facilities is then conducted by combining the proposed hazard and fragility curves. Results in the form of quantitative values are obtained, and the indicators for risks as well as the reliability and optimal measures to support decision-making are also presented. Through this study, it is confirmed that risk assessment based on the proposed probabilistic flood analysis technique is possible for flood events occurring at nuclear power plant sites.
Abnormal weather conditions due to climate change are currently increasing on both global and local scales. It is therefore important to ensure the safety of the areas where major national facilities are located by analyzing risk quantitatively and re-evaluating the existing major facilities, such as nuclear power plants, considering the load and capacity of extreme flood conditions. In this study, a risk analysis method is developed that combines flood hazard curves with fragility curves using hydraulic and hydrological models by GIS tools and the @RISK model for the probabilistic flood analysis of nuclear power plant sites. A two-dimensional (2D) analysis is first carried out to estimate flood depths in various watershed scenarios, and a representative hazard curve for both external and internal flooding is made by applying a verified probability distribution type for the flood watersheds. For the analysis of flooding within buildings, an internal grid is constructed using GIS with related design drawings, and based on the flood depth results of the 2D analysis, a hazard curve for the representative internal inundation using a verified probability distribution type is presented. In the present study, walkdowns with nuclear experts are conducted around the nuclear power plant area to evaluate the fragile structures and facilities under possible flooding. After reviewing the 2D inundation analysis results based on the selected major equipment and facilities, the zones requiring risk assessment are re-assigned. A fragility curve applying probability distribution for the site’s major equipment and facilities is also presented. Failure risk analysis of the major facilities is then conducted by combining the proposed hazard and fragility curves. Results in the form of quantitative values are obtained, and the indicators for risks as well as the reliability and optimal measures to support decision-making are also presented. Through this study, it is confirmed that risk assessment based on the proposed probabilistic flood analysis technique is possible for flood events occurring at nuclear power plant sites.
Record ID
Keywords
2D external flood analysis, 2D internal flood analysis, flood hazard curve, fragility curve, probabilistic flood analysis
Subject
Suggested Citation
Kim BJ, Kim M, Hahm D, Park J, Han KY. Probabilistic Flood Assessment Methodology for Nuclear Power Plants Considering Extreme Rainfall. (2023). LAPSE:2023.32057
Author Affiliations
Kim BJ: Smart Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute, Daejeon 34057, Korea [ORCID]
Kim M: Smart Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute, Daejeon 34057, Korea
Hahm D: Smart Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute, Daejeon 34057, Korea
Park J: Smart Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute, Daejeon 34057, Korea
Han KY: School of Architectural, Civil, Environmental and Energy Engineering, Kyungpook National University, Daegu 41566, Korea
Kim M: Smart Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute, Daejeon 34057, Korea
Hahm D: Smart Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute, Daejeon 34057, Korea
Park J: Smart Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute, Daejeon 34057, Korea
Han KY: School of Architectural, Civil, Environmental and Energy Engineering, Kyungpook National University, Daegu 41566, Korea
Journal Name
Energies
Volume
14
Issue
9
First Page
2600
Year
2021
Publication Date
2021-05-01
ISSN
1996-1073
Version Comments
Original Submission
Other Meta
PII: en14092600, Publication Type: Journal Article
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LAPSE:2023.32057
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https://doi.org/10.3390/en14092600
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Apr 19, 2023
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