Hao Han, Jingming Hou, Zhao Jin, Pingping Luo, Guodong Li, Ye Zhang, Jiahui Gong, Da Luo, Siqi Yang
{"title":"基于 GPU 的城市暴雨淹没模拟流体力学数值模型","authors":"Hao Han, Jingming Hou, Zhao Jin, Pingping Luo, Guodong Li, Ye Zhang, Jiahui Gong, Da Luo, Siqi Yang","doi":"10.2166/hydro.2023.152","DOIUrl":null,"url":null,"abstract":"The response capacities of urban flood forecasting and risk control can be improved by strengthening the computational abilities of urban flood numerical models. In this work, a GPU-based hydrodynamic model is developed to simulate urban rainstorm inundations. By simulating rainstorm floods in a certain area of Xixian New City, the established model can implement high-resolution urban rainstorm inundation simulations with significantly accelerated computing performances. The accelerated computation efficiencies of the different rainstorm event simulations under resolutions of 5 and 2 m are quantitatively analysed, showing that the absolute and relative speedup ratios for all scenarios of applying two GPUs range from 10.8 to 12.6 and 1.32 to 1.68 times as much as those of a CPU and a single GPU, respectively. The application of a large-scale rainstorm inundation simulation shows the excellent acceleration performance of the model compared to previous research. In addition, the greater the number of computational grids included in the simulation, the more significant the effect on the acceleration computing performance. The proposed model efficiently predicts the spatial variation in the inundation water depth. The simulation results provide guidance for urban rainstorm inundation management, and it improves the time and efficiency of urban flood emergency decision-making.","PeriodicalId":507813,"journal":{"name":"Journal of Hydroinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A GPU-based hydrodynamic numerical model for urban rainstorm inundation simulations\",\"authors\":\"Hao Han, Jingming Hou, Zhao Jin, Pingping Luo, Guodong Li, Ye Zhang, Jiahui Gong, Da Luo, Siqi Yang\",\"doi\":\"10.2166/hydro.2023.152\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The response capacities of urban flood forecasting and risk control can be improved by strengthening the computational abilities of urban flood numerical models. In this work, a GPU-based hydrodynamic model is developed to simulate urban rainstorm inundations. By simulating rainstorm floods in a certain area of Xixian New City, the established model can implement high-resolution urban rainstorm inundation simulations with significantly accelerated computing performances. The accelerated computation efficiencies of the different rainstorm event simulations under resolutions of 5 and 2 m are quantitatively analysed, showing that the absolute and relative speedup ratios for all scenarios of applying two GPUs range from 10.8 to 12.6 and 1.32 to 1.68 times as much as those of a CPU and a single GPU, respectively. The application of a large-scale rainstorm inundation simulation shows the excellent acceleration performance of the model compared to previous research. In addition, the greater the number of computational grids included in the simulation, the more significant the effect on the acceleration computing performance. The proposed model efficiently predicts the spatial variation in the inundation water depth. The simulation results provide guidance for urban rainstorm inundation management, and it improves the time and efficiency of urban flood emergency decision-making.\",\"PeriodicalId\":507813,\"journal\":{\"name\":\"Journal of Hydroinformatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-11-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Hydroinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2166/hydro.2023.152\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Hydroinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2166/hydro.2023.152","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A GPU-based hydrodynamic numerical model for urban rainstorm inundation simulations
The response capacities of urban flood forecasting and risk control can be improved by strengthening the computational abilities of urban flood numerical models. In this work, a GPU-based hydrodynamic model is developed to simulate urban rainstorm inundations. By simulating rainstorm floods in a certain area of Xixian New City, the established model can implement high-resolution urban rainstorm inundation simulations with significantly accelerated computing performances. The accelerated computation efficiencies of the different rainstorm event simulations under resolutions of 5 and 2 m are quantitatively analysed, showing that the absolute and relative speedup ratios for all scenarios of applying two GPUs range from 10.8 to 12.6 and 1.32 to 1.68 times as much as those of a CPU and a single GPU, respectively. The application of a large-scale rainstorm inundation simulation shows the excellent acceleration performance of the model compared to previous research. In addition, the greater the number of computational grids included in the simulation, the more significant the effect on the acceleration computing performance. The proposed model efficiently predicts the spatial variation in the inundation water depth. The simulation results provide guidance for urban rainstorm inundation management, and it improves the time and efficiency of urban flood emergency decision-making.