| 多点源空气污染高斯扩散模式并行方法研究 |
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| 引用本文： | 徐丙立,林珲,胡亚,荆涛,朱刚,李媛州.多点源空气污染高斯扩散模式并行方法研究[J].北京理工大学学报,2014,34(11):1145-1149. |
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| 作者姓名： | 徐丙立 林珲 胡亚 荆涛 朱刚 李媛州 |
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| 作者单位： | 装甲兵工程学院信息工程系,北京100072;香港中文大学太空与地球信息科学研究所,香港,沙田;香港中文大学太空与地球信息科学研究所,香港,沙田;香港中文大学太空与地球信息科学研究所,香港,沙田;西南交通大学土木工程学院测量工程系,四川,成都610031;装甲兵工程学院信息工程系,北京100072 |
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| 基金项目： | 国家自然科学基金资助项目(41271402);省部共建黄河中下游数字地理技术教育部重点实验室开放基金项目(GTYR2011002);国家科技重大专项资助项目(2014ZX10003002) |
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| 摘 要： | 为提高基于高斯模式的空气污染扩散计算的效率,研究从污染源、研究区域空间分层与栅格划分等3个因子入手,设计单因子、双因子和三因子作用下的多种并行算法,同时采用PC机群对算法进行实现. 针对珠三角区域空气污染并行计算试验结果表明,并行算法能将计算时间减少90%,大大提高了模型计算效率,很大程度上满足了基于高斯模式的空气污染实时计算要求.
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| 关 键 词： | 并行处理 高斯模式 空气污染扩散 计算机群 珠三角 |
| 收稿时间： | 2013/2/17 0:00:00 |
Design and Implement a Parallel Algorithm of Gauss Plume Model for Air Pollution Dispersion |
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| XU Bing-li,LIN Hui,HU Y,JING Tao,ZHU Gang and LI Yuan-zhou.Design and Implement a Parallel Algorithm of Gauss Plume Model for Air Pollution Dispersion[J].Journal of Beijing Institute of Technology(Natural Science Edition),2014,34(11):1145-1149. |
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| Authors: | XU Bing-li LIN Hui HU Y JING Tao ZHU Gang and LI Yuan-zhou |
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| Institution: | Department of Information Engineering, the Academy of Armored Forces Engineering, Beijing 100072, China;Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, Hong Kong;Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, Hong Kong;Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Shatin, Hong Kong;Department of Surveying Engineering, School of Civil Engineering, Southwest Jiaotong University, Chengdu, Sichuan 610031, China;Department of Information Engineering, the Academy of Armored Forces Engineering, Beijing 100072, China;Department of Information Engineering, the Academy of Armored Forces Engineering, Beijing 100072, China;Department of Information Engineering, the Academy of Armored Forces Engineering, Beijing 100072, China |
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| Abstract: | To decrease computation time and consequently improve computation efficiency of GPM, parallel algorithms based on pollution sources, levels of study area and grids of each level were designed. These parallel algorithms were also implemented and run on computer cluster. Our efforts were tested with a case of air pollution dispersion in Pearl River Delta. The test result indicates that the parallel algorithms can decrease computation time vastly by ninety percent, which makes it is possible to apply GPM in emergence response modeling and computation. |
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| Keywords: | parallel processing Gauss plume model air pollution dispersion computer cluster Pearl River Delta |
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