Author(s): Jin Yan; Shanshan Sun; Yanlin Wang

Linked Author(s):

Keywords: Nuclear power intake; Sea ice accumulation; Risk prediction; Risk grading standard; Discrete element method; Virtual simulation

Abstract: Nuclear power plants located in coastal regions rely on large amounts of seawater for cooling, yet sea ice accumulation near intakes during winter poses a significant operational hazard. To address this, a virtual simulation teaching system was developed based on a self-service platform, employing the Discrete Element Method (DEM) to dynamically simulate ice accumulation processes in front of an offshore nuclear water intake. The system allows users to set key parameters such as ice thickness, velocity, and concentration to simulate various risk scenarios. A core contribution of this work is the integrated multi-level risk prediction and early-warning module, which moves beyond conventional geometric assessments. By combining real-time simulation data with a dynamic risk grading framework—incorporating ice flux, accumulation rate, and blockage elevation—the system provides quantitative risk evaluation and proactive warning outputs across graded threat levels (e.g., low to severe). This predictive capability supports operational decision-making under extreme ice conditions. The virtual platform effectively overcomes the limitations and potential dangers of field practice, serving as an interactive educational tool that bridges theoretical knowledge with practical risk-aware engineering skills.

DOI:

Year: 2026