Research on seepage field of concrete dam foundation based on artificial neural network

Zhang, Hongyang; Song, Ziyi; Peng, Peng; Yi, Sun; Ding, Zelin; Zhang, Xianqi

doi:10.1016/j.aej.2020.03.041

Cited by 25 publications

(9 citation statements)

References 14 publications

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“…The accuracy of the original solution of the Dirichlet problem proposed in Figure 1 obtained in Section 3 can be improved by replacing the linear interpolation, at least with Spline functions whose analytical form can be used. Other studies, such as ( [18]), are made using artificial neural networks instead of BEM ( [19]).…”

Section: Discussionmentioning

confidence: 99%

Analysis of Water Infiltration under Impermeable Dams by Analytical and Boundary Element Methods in Complex

Cipu

2023

Axioms

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The boundary element method (BEM) is used by applying Cauchy’s formula to the boundary of the water movement domain under a dam. By approximating the border with a polygon through linear interpolation, the relationships between the complex velocities on each edge of the polygon are analytically deduced. For the case of the flow domain described by a semi- circular closed contours, the numerical values of the velocity are computed and compared with those obtained only analytically. Conclusions on the analytical and numerical context are drawn.

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Section: Discussionmentioning

confidence: 99%

Analysis of Water Infiltration under Impermeable Dams by Analytical and Boundary Element Methods in Complex

Cipu

2023

Axioms

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“…To determine the evolution of the aperture of the interface, a sensitivity analysis was applied. Zhang et al [67] developed a framework integrating a 3D finite element model of complex geological bodies with FFNN to model the seepage through the base of a dam. In this way, seepage properties in five groups of representative grouting schemes were investigated.…”

Section: Artificial Neural Network (Ann) For Seepage Modelingmentioning

confidence: 99%

The Applications of Soft Computing Methods for Seepage Modeling: A Review

Nourani

Behfar

Dąbrowska

et al. 2021

Water

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In recent times, significant research has been carried out into developing and applying soft computing techniques for modeling hydro-climatic processes such as seepage modeling. It is necessary to properly model seepage, which creates groundwater sources, to ensure adequate management of scarce water resources. On the other hand, excessive seepage can threaten the stability of earthfill dams and infrastructures. Furthermore, it could result in severe soil erosion and consequently cause environmental damage. Considering the complex and nonlinear nature of the seepage process, employing soft computing techniques, especially applying pre-post processing techniques as hybrid methods, such as wavelet analysis, could be appropriate to enhance modeling efficiency. This review paper summarizes standard soft computing techniques and reviews their seepage modeling and simulation applications in the last two decades. Accordingly, 48 research papers from 2002 to 2021 were reviewed. According to the reviewed papers, it could be understood that regardless of some limitations, soft computing techniques could simulate the seepage successfully either through groundwater or earthfill dam and hydraulic structures. Moreover, some suggestions for future research are presented. This review was conducted employing preferred reporting items for systematic reviews and meta-analyses (PRISMA) method.

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“…Kang [25] proposed a response surface model for the parameter inversion of concrete dams based on the kernel extreme learning machine. Zhang [26] developed a seepage field inversion model for concrete dams by combining a finite element model with an artificial neural network. Because the material partitioning and anti-seepage structures of different dam types vary, the seepage parameters that need to be inverted are diverse.…”

Section: Introductionmentioning

confidence: 99%

A Novel Inversion Method for Permeability Coefficients of Concrete Face Rockfill Dam Based on Sobol-IDBO-SVR Fusion Surrogate Model

Xiong,

Shen,

et al. 2024

Mathematics

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The accurate and efficient inversion of permeability coefficients is significant for the scientific assessment of seepage safety in concrete face rockfill dams. In addressing the optimization challenge of permeability coefficients with few samples, multiple parameters, and strong nonlinearity, this paper proposes a novel intelligent inversion method based on the Sobol-IDBO-SVR fusion surrogate model. Firstly, the Sobol sequence sampling method is introduced to extract high-quality combined samples of permeability coefficients, and the equivalent continuum seepage model is utilized for the forward simulation to obtain the theoretical hydraulic heads at the seepage monitoring points. Subsequently, the support vector regression surrogate model is used to establish the complex mapping relationship between the permeability coefficients and hydraulic heads, and the convergence performance of the dung beetle optimization algorithm is effectively enhanced by fusing multiple strategies. On this basis, we successfully achieve the precise inversion of permeability coefficients driven by multi-intelligence technologies. The engineering application results show that the permeability coefficients determined based on the inversion of the Sobol-IDBO-SVR model can reasonably reflect the seepage characteristics of the concrete face rockfill dam. The maximum relative error between the measured and the inversion values of the hydraulic heads at each monitoring point is only 0.63%, indicating that the inversion accuracy meets the engineering requirements. The method proposed in this study may also provide a beneficial reference for similar parameter inversion problems in engineering projects such as bridges, embankments, and pumping stations.

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Research on seepage field of concrete dam foundation based on artificial neural network

Cited by 25 publications

References 14 publications

Analysis of Water Infiltration under Impermeable Dams by Analytical and Boundary Element Methods in Complex

Analysis of Water Infiltration under Impermeable Dams by Analytical and Boundary Element Methods in Complex

The Applications of Soft Computing Methods for Seepage Modeling: A Review

A Novel Inversion Method for Permeability Coefficients of Concrete Face Rockfill Dam Based on Sobol-IDBO-SVR Fusion Surrogate Model

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