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Locating Optimal Position of Pumping Wells in Aquifer Using Meta-Heuristic Algorithms and Finite Element Method

机译:基于元启发式算法和有限元方法的含水层抽水井最优定位

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摘要

An optimal pumping policy ensures the sustainability of groundwater resources when groundwater is extracted. In this paper, several simulation models (genetic algorithms, particle swarm optimization and firefly algorithm) are used to evaluate optimal pumping policy in an hypothetical aquifer. In this study, the level of groundwater in an unconfined hypothetical aquifer with a surface area of 1.5 km(2) and three different hydraulic conductivities with a thickness of 100 m, as well as four pumping wells were investigated. The finite element method was employed to estimate the groundwater level of the aquifer and the mentioned algorithms were used to optimize the position of the pumping wells. The position of the pumping wells with a specific discharge is optimized to minimize groundwater drawdown in the aquifer. The results indicated that with increasing number of iterations, there was little improvement in the results of the FA, and after five iterations, the algorithm entrapped in local optima. By investigating the values of the objective function of two other algorithms (PSO and GA), the results indicated that the GA has a better performance than the PSO in optimizing groundwater pumping well locations. As a result, the GA reduces the value of objective function by 31% compared to the PSO algorithm. With this value of objective function, the maximum drawdown groundwater was about 2.5 m in the southwest of aquifer. The results indicated that the optimum location of wells is on the western side of the aquifer where the aquifer boundary has a constant head on this side.
机译:最佳的抽水政策可确保抽取地下水时地下水资源的可持续性。在本文中,几种模拟模型(遗传算法,粒子群优化和萤火虫算法)用于评估假设含水层中的最佳抽水策略。在这项研究中,调查了表面积为1.5 km(2),三种不同的水力传导率为100 m的无限制假设含水层中的地下水位,以及四个抽水井。采用有限元方法估算了含水层的地下水位,并使用上述算法优化了抽水井的位置。优化了具有特定排放量的抽水井的位置,以最大程度减少含水层中的地下水渗入。结果表明,随着迭代次数的增加,FA的结果几乎没有改善,并且经过五次迭代,该算法陷入了局部最优。通过研究其他两种算法(PSO和GA)的目标函数值,结果表明,在优化地下水泵井位置方面,GA具有比PSO更好的性能。结果,与PSO算法相比,GA将目标函数的值减少了31%。利用该目标函数值,含水层西南部的最大回落地下水约为2.5 m。结果表明,井的最佳位置在含水层的西侧,其中含水层边界在这一侧具有恒定的水头。

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