Simulation of Drainage Capacity in a Coastal Nuclear Power Plant under Extreme Rainfall and Tropical Storm

Abstract

To ensure the safety of coastal nuclear power plants, accurately simulating water depth due to flooding resulting from heavy rainfall and tropical storms is important. In this paper, a combined model is developed to analyze and simulate the drainage capacity in a coastal nuclear power plant under the combined action of extreme rainfall and wave overtopping. The combined model consist of a surface two-dimensional flood-routing model, a pipe network model, and an offshore wave model. The method of predictive correction calculation is adopted to calculate the node return flow. The inundated water depth varying with time for different design rainstorm return periods (p = 0.1 and 1%) was simulated and analyzed by the combined model. The maximum inundated water depth is calculated for the important entrances of the workshop. The model was validated and calibrated with the data of the rainfall, outflow discharge, and flow velocity measured on 23 June 2016 in plant. Modeling indicates that the simulated depths are consistent with the observed depths. The results show that the water depths in the left and right of the nuclear power plant are 0.2–0.4 m and 0.3–0.8 m, respectively. The water depth increases of Monitoring Point 22 are the largest in different design rainstorm return periods (p = 0.1 and 1%), which increase by 16% for a rainstorm once every thousand years compared to events occurring once in one hundred years. The main factor influencing water accumulation is wave overtopping, and the seawall, revetments, and pipe system play an important role in decreasing the inundated water depth. Through scientific analysis, a certain decision-making basis has been provided for flood disaster management and a certain security guarantee has also been provided for regional sustainable development.

Analysis of drainage efficiency under extreme precipitation events based on numerical simulation

“…Bai et al (2021) proposed a numerical simulation of surface hydrodynamics based on GPU acceleration to study the precipitation and runoff processes in drainage systems. Son and Jeong (2019) introduced 2D finite element models to analyse heavy precipitation and flooding caused by typhoons in coastal cities, and Wang, Zhang, and Chen (2019) proposed a combination model including surface road floods and drainage networks to precisely simulate the water depth brought by heavy rainfall in tropical storms. However, physical experiments were affected by the long period and experimental site, and solving capability of computers limited the numerical simulation and the grid precision of models.…”

A rainwater control optimization design approach for airports based on a self-organizing feature map neural network model

“…Their design uses the predictive correction calculation method to calculate the node return flow and simulates and analyzes the flooding depth of different design rainstorm regression periods through the combined model. Through scientific analysis, this model provides a certain decision-making basis for rainwater control and control during flood disasters and provides certain security for regional sustainable development [1]. HR Wallingford successfully built a hydraulic model of the Drogheda basin using Info Works CS software, thus effectively simulating the operation of the drainage system, optimizing the layout of the pipe network, and managing the rainwater properly [2].…”