Combining Lattice Boltzmann method and genetic algorithm to optimize the layout of artificial floating islands in river network in China
How to solve the pollution problem of water environment in river network is a hot issue in the world. Artificial floating island is an efficient way to deal with water pollution. Taking Jiashan, Zhejiang, China, as an example, Lattice Boltzmann method (LBM) is used to simulate the law of hydrodynami...
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          | Published in | Environmental science and pollution research international Vol. 30; no. 9; pp. 22520 - 22531 | 
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| Main Authors | , , , , , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        Berlin/Heidelberg
          Springer Berlin Heidelberg
    
        01.02.2023
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| Subjects | |
| Online Access | Get full text | 
| ISSN | 1614-7499 1614-7499  | 
| DOI | 10.1007/s11356-022-23785-0 | 
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| Summary: | How to solve the pollution problem of water environment in river network is a hot issue in the world. Artificial floating island is an efficient way to deal with water pollution. Taking Jiashan, Zhejiang, China, as an example, Lattice Boltzmann method (LBM) is used to simulate the law of hydrodynamics and pollutant transport in river network. Lattice Boltzmann equations are established in both artificial floating island and non-artificial floating island sections, and the river network boundary is automatically identified. The simulation results have high accuracy and are more suitable for the establishment of complex boundaries. On this basis, combined with the genetic algorithm (GA) module, the location of the artificial floating island is optimized, and the retention ratio of the pollution in optimized layout of artificial floating island is between and 2.4 and 7.2%. The research results of this paper can provide theoretical reference for the selection and location of artificial floating island in practical engineering. | 
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23  | 
| ISSN: | 1614-7499 1614-7499  | 
| DOI: | 10.1007/s11356-022-23785-0 |