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作 者:王忠慧 贡力[1,2] 康春涛 王鸿 杨轶群 WANG Zhonghui;GONG Li;KANG Chuntao;WANG Hong;YANG Yiqun(Department of Civil Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China;Institute of Water Diversion Engineering and Water Security,Lanzhou Jiaotong University,Lanzhou 730070,China)
机构地区:[1]兰州交通大学土木工程学院,甘肃兰州730070 [2]兰州交通大学调水工程及输水安全研究所,甘肃兰州730070
出 处:《水资源保护》2020年第5期87-92,共6页Water Resources Protection
基 金:国家自然科学基金(51969011,51669010)。
摘 要:为了在河渠突发水污染事件发生后快速识别污染物的源项信息,结合正向的质量浓度过程与逆向位置信息之间的关系,实现污染物源项的解耦,确定了质量浓度与位置概率密度函数之间的相关关系以及质量浓度与正向质量浓度概率密度函数之间的关系,构建了水力学模型,并利用天牛须搜索(BAS)算法对水污染源项进行求解。数值模型仿真结果表明:该水力学模型与BAS算法的结合有效地降低了计算量,计算得到的源项信息与实际情况基本符合,精度较高;与粒子群算法相比,BAS算法收敛速度快,运算量小。To identify the pollutant source term information rapidly after a sudden water pollution event in rivers and canals,combined with the relationship between the forward mass concentration process and the reverse location information,we realized the decoupling of the pollutant source terms,determined the relationships between the mass concentration and the probability density function of position,and between the mass concentration and the probability density function of forward mass concentration.According to these relationships the hydraulics model is built,and the information of water pollution source term is solved using beetle antennae search(BAS)algorithm.The results show that the combination of the hydraulics model and BAS algorithm can effectively reduce the amount of computations.The calculated source term information basically matches the actual situation and has a high accuracy.Compared with the particle swarm optimization algorithm,it is found that BAS algorithm is faster in search and smaller in computation.
分 类 号:TV133[水利工程—水力学及河流动力学] X522[环境科学与工程—环境工程]
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