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Updated: May 5, 2026

Experimental Multiscale Methodology for Predicting Material Fouling Resistance
[Identification and evaluation of cold source risk organisms in close areas of a coastal nuclear power plant]
Xin-Yue Hu1, Meng Cui2, Yuan Jin3,4
1College of Construction Engineering, Dalian University of Technology, Dalian 116081, Liaoning, China.
Abstract:
Species invasion in marine has increased the frequency of security incidents at coastal nuclear power plants, posing serious threats to the cooling water intake. To systematically identify the risk organisms in nuclear power cooling water sources and clarify their distribution pattern, we established a risk identification and assessment framework for marine organisms in cooling water intake areas. Based on field investigation conducted in the summer of 2024 in the adjacent waters of a nuclear power plant in northern China, we categorized marine organisms into five types: phytoplankton, zooplankton, swimming animals, benthic animals, and selected intertidal organisms. Trophic level, habitat layer, body size, body length, and density were used as evaluation criteria. These indices were combined with type-specific traits (e.g., migratory behavior and reproduction mode) to develop a scoring system, with each indicator being assigned a maximum score of 10 points. Scores were determined based on the potential risk of each biological trait to clogging the water intake, and a spatial weight based on the distance from sampling points to the intake was incorporated to calculate the total risk score for each species. We classified risk levels into low, medium, and high according to thresholds set at 30% and 80% of the total possible score. Results showed that a total of 40 phytoplankton, 28 zooplankton, 27 swimming animals, 62 benthic animals, and 43 intertidal species were recorded. Through multi-indicator integration and spatial weighting analysis-balancing field data authenticity and theoretical traits of species, Loligo sp., Charybdis japonica, and Konosirus punctatus were identified as high-risk species. Moreover, there was a higher density of high-risk organisms in the northern area near the water intake. By integrating functional traits and measured data into a comprehensive evaluation framework, this study could provide a scientific basis for risk organism identification, early warning, and the development of prevention and control strategies for cooling water systems near nuclear power plants.
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