Random Characteristics of Hydraulic Gradient through Three-Dimensional Multilayer Embankment

Xiaoming Zhao,Yulong Niu,Mingming Hu,Dongbin Cui,Yonghong Wang

doi:10.1155/2022/7044267

Abstract

The distribution characteristics of hydraulic gradient in embankment are closely related to seepage failure. Seepage failures such as flowing soil and piping will lead to serious damage and even the overall failure of embankment. The hydraulic conductivity has strong spatial variability, which changes the distribution of hydraulic gradient in embankment and increases the difficulty for predicting the embankment seepage instability. In this study, the distribution of soil hydraulic conductivity in a section of Shijiu Lake embankment was obtained by the permeability test. Based on Local Average Subdivision technique, a three-dimensional multilayer random field of embankment hydraulic conductivity was generated. Then, the mean and standard deviation of overflow point height and hydraulic gradient were calculated by the Monte Carlo method, which combined the generated three-dimensional random model and the deterministic analysis method of seepage field. Finally, the coefficient of variation (COV) of hydraulic conductivity (0.1, 0.3, 0.5, 0.7, 1.0, 2.0, and 3.0), the fluctuation scale in vertical direction (3 m) and the fluctuation scale in horizontal plane (3 m, 6 m, 12 m, 24 m, 36 m, and 48 m) were selected respectively for analyzing the random characteristics of embankment overflow point height and hydraulic gradient under the influence of different COV and fluctuation scale of embankment soil hydraulic conductivity.

Highlights

Academic Editor: Yonghong Wang e distribution characteristics of hydraulic gradient in embankment are closely related to seepage failure
Based on Local Average Subdivision technique, a three-dimensional multilayer random field of embankment hydraulic conductivity was generated. en, the mean and standard deviation of overflow point height and hydraulic gradient were calculated by the Monte Carlo method, which combined the generated three-dimensional random model and the deterministic analysis method of seepage field
Uncertainty analysis is closely related to random field theory, common random field generation methods include Fast Fourier Transform Method (FFT) [1], Turning Bands Method (TBM) [2, 3] and Local Average Subdivision Method (LAS) [4, 5]. e FFT method has the virtue of the high computational efficiency and calculates the effective random field quickly, while there is symmetry in the covariance in discrete random field, which causes significant error in some cases

Summary

Research Article

Random Characteristics of Hydraulic Gradient through Three-Dimensional Multilayer Embankment. En, the mean and standard deviation of overflow point height and hydraulic gradient were calculated by the Monte Carlo method, which combined the generated three-dimensional random model and the deterministic analysis method of seepage field. In this paper, considering the strong randomness of embankment soil hydraulic conductivity, a three-dimensional multimedia permeability random field of embankment based on LAS technique is generated, Monte Carlo simulation method is used to study the random characteristics of overflow point height and hydraulic gradient in embankment. Hoeksema and Kitanidis [27], Sudicky [28] and Huang et al [29] considered that the probability density function of soil hydraulic conductivity obeys lognormal distribution in space In these theories, it is assumed that the hydraulic conductivity follows a certain mathematical distribution in space, and the regression analysis is carried out, the spatial random characteristics of hydraulic conductivity is obtained. The hydraulic conductivity is regarded as a random field variable which obeying lognormal distribution, and the COV is taken as 0.1, 0.3, 0.5, 0.7, 1.0, 2.0 and 3.0 respectively. e vertical fluctuation scale is fixed to 3 m, and the horizontal fluctuation scale is 3 m, 6 m, 12 m, 24 m, 36 m and 48 m. e Anisotropy ratio ζ can be obtained using

Soil X

Results

Mean of the standard deviation of hydraulic gradient