UAV-based emergency treatment plan for flood disasters at the Hongyanhe nuclear power plant

This paper explores the potential of the joint application of unmanned aerial vehicle(UAV)-based the belief -desire-intention (BDI) algorithm constructed for rescue by NetLogo and the flood model of the Hongyanhe Nuclear Power Plant based on the Global Surface Water (GSW) dataset. The study revealed the high potential of the GSW dataset provides useful data for detecting the occurrence of flood events about the Hongyanhe Nuclear Power Plant, the major features are as: the areas affected by the floods in the grid system for emergency treatment at the nuclear power station were: grid area718, 758, 759, 798, 799, and 839;the most affected grid areas were grid areas 758-759 and 798-799; these were the important areas, incorporating the storage area for wastewater, waste liquid and waste solids, the comprehensive office building, and No. 6 shelter. The study also reveals that the success rate of UAV rescue using a single drone was 59.8% (standard deviation 0.1657, standard error 0.0166, 95% Confidence Interval),and there was no significant difference in the results between the two groups(significance of the one-way analysis of variance P = 0.662 > 0.05); the success rate of UAV rescue using two drones was 58.8% (standard deviation 0.1572, standard error 0.0157, 95% Confidence Interval); the simulated time of completing the rescue task using a single drone was 5484.09 (standard deviation 2447.7519, standard error 244.7752, 95% Confidence Interval); and the simulated time of completing the rescue task using two drones was 4679.22 (standard deviation 3109.4676, standard error 310.9468, 95% Confidence Interval). Thus, the rescue efficiency was higher using two drones than using one drone (level of significance from the one-way analysis of variance P = 0.043 < 0.05).