A design approach for determining the optimal flow pattern in a landscape lake is proposed based on FLUENT simulation, multiple objective optimization, and parallel computing. This paper formulates the design into a multi-objective optimization problem, with lake circulation effects and operation cost as two objectives, and solves the optimization problem with non-dominated sorting genetic algorithm II. The lake flow pattern is modelled in FLUENT. The parallelization aims at multiple FLUENT instance runs, which is different from the FLUENT internal parallel solver. This approach: (1) proposes lake flow pattern metrics, i.e. weighted average water flow velocity, water volume percentage of low flow velocity, and variance of flow velocity, (2) defines user defined functions for boundary setting, objective and constraints calculation, and (3) parallels the execution of multiple FLUENT instances runs to significantly reduce the optimization wall-clock time. The proposed approach is demonstrated through a case study for Meijiang Lake in Tianjin, China.
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Research Article|
June 21 2016
A landscape lake flow pattern design approach based on automated CFD simulation and parallel multiple objective optimization
Hao Guo;
1School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
E-mail: tjuguohao@163.com
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Yimei Tian;
Yimei Tian
1School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
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Hailiang Shen;
Hailiang Shen
2GHD, 651 Colby Drive, Waterloo, ON, Canada N2V 1C2
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Yi Wang;
Yi Wang
3University of Guelph, Guelph, ON, Canada N1G2W
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Mengxin Kang
Mengxin Kang
1School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, China
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Water Sci Technol (2016) 74 (5): 1155–1162.
Article history
Received:
February 04 2016
Accepted:
June 07 2016
Citation
Hao Guo, Yimei Tian, Hailiang Shen, Yi Wang, Mengxin Kang; A landscape lake flow pattern design approach based on automated CFD simulation and parallel multiple objective optimization. Water Sci Technol 19 September 2016; 74 (5): 1155–1162. doi: https://doi.org/10.2166/wst.2016.308
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