A System Coupled GIS and CFD for Atmospheric Pollution Dispersion Simulation in Urban Blocks

被引:2
|
作者
Wu, Qunyong [1 ,2 ,3 ]
Wang, Yuhang [1 ,2 ,3 ]
Sun, Haoyu [1 ,2 ,3 ,4 ]
Lin, Han [1 ,2 ,3 ]
Zhao, Zhiyuan [1 ,2 ,3 ]
机构
[1] Fuzhou Univ, Acad Digital China Fujian, Fuzhou 350108, Peoples R China
[2] Fuzhou Univ, Key Lab Spatial Data Min & Informat Sharing, Minist Educ, Fuzhou 350108, Peoples R China
[3] Fuzhou Univ, Natl Engn Res Ctr Geospatial Informat Technol, Fuzhou 350108, Peoples R China
[4] Xiaomi Inc, Nanjing 210019, Peoples R China
基金
中国国家自然科学基金;
关键词
CFD; 3DGIS; urban blocks; atmospheric pollution dispersion simulation; GIS-coupled; COMPUTATIONAL FLUID-DYNAMICS; SHORT-TERM-MEMORY; GAS DISPERSION; NEURAL-NETWORK; MODEL;
D O I
10.3390/atmos14050832
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Atmospheric pollution is a critical issue in public health systems. The simulation of atmospheric pollution dispersion in urban blocks, using CFD, faces several challenges, including the complexity and inefficiency of existing CFD software, time-consuming construction of CFD urban block geometry, and limited visualization and analysis capabilities of simulation outputs. To address these challenges, we have developed a prototype system that couples 3DGIS and CFD for simulating, visualizing, and analyzing atmospheric pollution dispersion. Specifically, a parallel algorithm for coordinate transformation was designed, and the relevant commands were encapsulated to automate the construction of geometry and meshing required for CFD simulations of urban blocks. Additionally, the Fluent-based command flow was parameterized and encapsulated, enabling the automatic generation of model calculation command flow files to simulate atmospheric pollution dispersion. Moreover, multi-angle spatial partitioning and spatiotemporal multidimensional visualization analysis were introduced to achieve an intuitive expression and analysis of CFD simulation results. The result shows that the constructed geometry is correct, and the mesh quality meets requirements with all values above 0.45. CPU and GPU parallel algorithms are 13.3x and 25x faster than serial. Furthermore, our case study demonstrates the developed system's effectiveness in simulating, visualizing, and analyzing atmospheric pollution dispersion in urban blocks.
引用
收藏
页数:26
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