Identification of Hydraulic Conductivity in Aquifer for Coupled FEM and Adaptive Genetic Algorithm

Xianghui Deng, Haibo Fang, Jianxun Chen and Junshu Kou

Mathematical Problems in Engineering, 2015, vol. 2015, 1-9

Abstract:

The hydraulic conductivity of a natural rock mass was difficult to determine because of the complex structure and the significant influence of uncertain factors. In this paper, hydraulic conductivity was adopted to conduct an inversion analysis according to the measurement of head materials by combining the finite element method with the adaptive genetic algorithm. The results showed that the maximum relative error of the measuring and computation groundwater levels at the measuring points was 5.3%, and the average head error was 1.41%; the effective hydraulic conductivity of intensively weathered layer, moderately weathered layer, and fresh bedrock layer in riverbed formation tended to decline gradually; the effective permeability coefficient in direction was the minimum in the same aquifer. Therefore, the established hydraulic conductivity inversion analysis method was effective.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:909465

DOI: 10.1155/2015/909465

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