Back analysis of the 3D seepage problem and its engineering applications

Ren, Jie; Shen, Zhenzhong; Yu, Chong-zhen

doi:10.1007/s12665-015-4837-1

Cited by 30 publications

(19 citation statements)

References 16 publications

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“…Assuming that seepage in unsaturated soil obeys generalized Darcy's law, and the hydraulic conductivity tensor is introduced to describe the permeability of rock and soil. The basic differential equation for the heterogeneous anisotropic saturation-unsaturated soil seepage is written as follows [23].…”

Section: Mathematical Modelmentioning

confidence: 99%

“…The residual of a finite element calculation head and observation head is the weighted sum of squares in the objective function of a parameter inverse optimization problem, which is used to find matching parameters closer to the actual basic parameters. The objective function adopted to optimize the parameter inversion can be expressed by the equation below [23,27].…”

Section: Objective Function Of Back Analysismentioning

confidence: 99%

“…He et al (2011) proposed a new approach to determine the equivalent permeability tensor of fractured rock masses by combining the geological method, the packer test method, and ANN [10]. Ren et al (2016) applied the flexible tolerance inversion method to obtain the seepage parameters of rock masses and faults in the dam foundation of the Maerdang dam [23].Existing research is usually based on the field water pressure test to calculate the permeability parameters of the rock masses near the test area, but its determination object is usually hard or semi-hard rock mass [24,25]. Scholars have also adopted the stable seepage theory to assess the seepage parameters of the rock masses by an inversion method on the basis of the groundwater level monitoring data.…”

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A New Approach to Permeability Inversion of Fractured Rock Masses and Its Engineering Application

Gan

Chen

Shen

2020

Water

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This paper presents a new seepage inversion technique to predict the permeability coefficient of the rock mass with developed fracture or fault. With the measured data of flow and water head of boreholes, the permeability coefficient of the rock masses near the boreholes are obtained by inverse calculation on the basis of unsteady seepage tests. Then, a flexible tolerance method is proposed to invert the permeability coefficient of rock masses in different zones of the reservoir area. This comprehensive inversion analysis method is applied in one actual project of the water supply reservoir. The equivalent permeability coefficient of the rock masses in the range of 0 m to 16.0 m below the road surface near the dam axis on the left bank of the mountain is 1.12 × 10 −3 cm/s. The root mean squared error and coefficient of determination of the measured and calculated values are 1.33 × 10 −4 m 3 /s and 0.9976 m 3 /s, respectively. The rock masses in the reservoir site area have high permeability. The groundwater level in the junction area and the mountains on both sides of Shangmo reservoir is low, and the hydraulic gradient is small. The maximum error between the calculated value of the groundwater level and the measured values is −0.41 m, and the relative error is −4.36%. The recommended anti-seepage scheme can effectively solve the problem of large leakage in the reservoir area. The results show that the innovative approach is appropriate for the seepage analysis of the field with the fractured rock masses and more meaningful from an engineering point of view.Water 2020, 12, 734 2 of 17 Currently, the most direct method to determine the permeability coefficient of fractured rock mass is the field measurement method based on statistics and cubic law [10,12]. This method is simple, but it is difficult to obtain representative fracture parameters by outcrop measurement or borehole measurement. The permeability parameters of the aquifer are obtained by an analytical or a semi-analytical method on the basis of the water pressure test [13,14]. The cross-hole tests and isotopic tracer methods are developed to determine the permeability tensor of the rock masses [15][16][17][18]. This permeability tensor can only represent the seepage characteristics of medium near the test area. In recent decades, the inversion methods, such as the Pulse Spectrum method, the Numerical Optimization method, the Artificial Neural Network method (ANN), and the Genetic Algorithm (GA), are widely used in the seepage parameters inversion of fractured rock masses [19][20][21][22]. He et al. (2011) proposed a new approach to determine the equivalent permeability tensor of fractured rock masses by combining the geological method, the packer test method, and ANN [10]. Ren et al. (2016) applied the flexible tolerance inversion method to obtain the seepage parameters of rock masses and faults in the dam foundation of the Maerdang dam [23].Existing research is usually based on the field water pressure test to calculate the permeability parameters of th...

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Section: Mathematical Modelmentioning

confidence: 99%

Section: Objective Function Of Back Analysismentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A New Approach to Permeability Inversion of Fractured Rock Masses and Its Engineering Application

Gan

Chen

Shen

2020

Water

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“…A comparison of the calculated and measured values obtained from the osmometers revealed that core wall failure causes the abnormal seepage behavior of the dam. Ren et al [9] conducted an inversion of dam seepage parameters based on the finite element model of an earth dam and the monitoring data from the osmometers. The seepage field of a dam was simulated under normal water levels.…”

Section: Introductionmentioning

confidence: 99%

Detection Model for Seepage Behavior of Earth Dams Based on Data Mining

Jiang

2018

Mathematical Problems in Engineering

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Seepage behavior detecting is an important tool for ensuring the safety of earth dams. However, traditional seepage behavior detection methods have used insufficient monitoring data and have mainly focused on single-point measures and local seepage behavior. The seepage behavior of dams is not quantitatively detected based on the monitoring data with multiple measuring points. Therefore, this study uses data mining techniques to analyze the monitoring data and overcome the above-mentioned shortcomings. The massive seepage monitoring data with multiple points are used as the research object. The key information on seepage behavior is extracted using principal component analysis. The correlation between seepage behavior and upstream water level is described as mutual information. A detection model for overall seepage behavior is established. Result shows that the model can completely extract the seepage monitoring data with multiple points and quantitatively detect the overall seepage behavior of earth dams. The proposed method can provide a new and reasonable means of quantitatively detecting the overall seepage behavior of earth dams.

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