Identification of Hydraulic Conductivity in Aquifer for Coupled FEM and Adaptive Genetic Algorithm
Joint Authors
Chen, Jianxun
Deng, Xianghui
Fang, Haibo
Kou, Junshu
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-10-19
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
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 Y was the minimum in the same aquifer.
Therefore, the established hydraulic conductivity inversion analysis method was effective.
American Psychological Association (APA)
Deng, Xianghui& Fang, Haibo& Chen, Jianxun& Kou, Junshu. 2015. Identification of Hydraulic Conductivity in Aquifer for Coupled FEM and Adaptive Genetic Algorithm. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1075027
Modern Language Association (MLA)
Deng, Xianghui…[et al.]. Identification of Hydraulic Conductivity in Aquifer for Coupled FEM and Adaptive Genetic Algorithm. Mathematical Problems in Engineering No. 2015 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-1075027
American Medical Association (AMA)
Deng, Xianghui& Fang, Haibo& Chen, Jianxun& Kou, Junshu. Identification of Hydraulic Conductivity in Aquifer for Coupled FEM and Adaptive Genetic Algorithm. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-9.
https://search.emarefa.net/detail/BIM-1075027
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1075027