Parameter inversion and deformation mechanism of Sanmendong landslide in the Three Gorges Reservoir region under the combined effect of reservoir water level fluctuation and rainfall

Zhan

et al. 2018

Water

Instability of tailings dams may result in loss of life and property and serious environmental pollution. The position of the tailings dam's phreatic line varies due to continuously changing factors such as rainfall infiltration and discharge of tailings recycling water. Consequently, tailings dams undergo dry-wet (DW) cycles, accompanied by the appearance of a hydro-fluctuation belt. With dynamic development of the physical and chemical properties of tailings sand in the hydro-fluctuation belt, the stability of tailings dams is uncertain. In this study, direct shear tests were performed on the tailings sand collected from a tailings dam in Luonan, through which the shear strength parameters of tailings sand with DW cycles were obtained. Then, a method that efficiently calculates the phreatic line of the tailings dam under DW cycles was proposed. In addition, based on laboratory tests and the proposed phreatic line calculation method, we used a finite element program to evaluate the stability of the tailings dam that experienced different DW cycles. The calculated results showed that: (i) the damage effects of DW cycles gradually weakens as the number of DW cycles increases.(ii) With the increasing of DW cycles, the maximum displacement of the tailings dam increases from 0.5 mm to 22 mm, and the area of maximum displacement expanded mainly at the toe of the tailings dam and at the front edge of the hydro-fluctuation belt. (iii) The tailings dam safety factor decreases continuously with increasing DW cycles. This study may provide a novel method for analyzing the stability of tailings dams under different DW cycles as well as an important reference for improving tailings dam stability.

Section: Methods For Calculating the Tailings Dam's Phreatic Line Undementioning

confidence: 99%

The Stability of Tailings Dams under Dry-Wet Cycles: A Case Study in Luonan, China

Zhan

et al. 2018

Water

Num Anal Meth Geomechanics

“…Although the parameter values of engineering geological characteristics can be measured via in situ tests and laboratory experiments directly, the probability of construction work accidents may increase when the measured geological parameters are not very representative of reality . Field‐measured physical‐mechanical parameters have some drawbacks, including the representation of the sampling sites, the disturbance of the test samples, and the scale effect …”

Section: Introductionmentioning

confidence: 99%

“…9,10 Fieldmeasured physical-mechanical parameters have some drawbacks, including the representation of the sampling sites, the disturbance of the test samples, and the scale effect. [11][12][13] A more reasonable way to make up for the shortage of the field-measured parameters is to perform parameter identification using the back-analysis method based on field observations. [14][15][16][17][18][19] The purpose of inverse analysis is to determine the accurate values of physical-mechanical parameters.…”

Section: Introductionmentioning

confidence: 99%

Inverse analysis for geomaterial parameter identification using Pareto multiobjective optimization

Jiang

Sun

Yi³

et al. 2018

Summary An inverse analysis method that combines the back propagation neural network (BPNN) and vector evaluated genetic algorithm (VEGA) was proposed to identify mechanical geomaterial parameters for a more accurate prediction of deformation. The BPNN is used to replace the time‐consuming numerical calculations, thus enhancing the efficiency of the inverse analysis. The VEGA is used to find the Pareto‐optimal solutions to multiobjective functions. Unlike traditional back‐analysis methods which are based on only 1 type of field measurement and a single objective function, this proposed method can consider multiple field observations simultaneously. The proposed method was applied to the Shapingba foundation pit excavation located in Chongqing city, China. Two types of measurements are considered in the method simultaneously: the displacements in the x‐direction (north orientation) and those in the y‐direction (east orientation). Five deformation modulus parameters for artificial backfill soil, silty clay, siltstone, sandstone, and mudstone were selected as the inversion parameters. Compared with the weighted sum approach, the proposed method was demonstrated as an efficient multi‐objective optimization tool for back calculating undetermined parameters. After performing a forward‐calculation using the optimized parameters obtained by the inverse analysis, the predicted results were well consistent with the practical deformation in magnitude and trend.

“…Toc slope stability. Sun et al [8] simulated the hydraulic-mechanic coupling process of Sanmendong landslide by software product ABAQUS and confirmed that the combined result of reservoir water level fluctuation and rainfall could primarily account for the increase of displacement of this landslide. Vallet et al [9] studied the hydromechanical behavior and evolution of rainfall-induced landslides subjected to creep deformation.…”

Section: Introductionmentioning

confidence: 99%

The Coupling Effect of Rainfall and Reservoir Water Level Decline on the Baijiabao Landslide in the Three Gorges Reservoir Area, China

Zhao

et al. 2017

Geofluids

Rainfall and reservoir level fluctuation are two of the main factors contributing to reservoir landslides. However, in China's Three Gorges Reservoir Area, when the reservoir water level fluctuates significantly, it comes at a time of abundant rainfall, which makes it difficult to distinguish which factor dominates the deformation of the landslide. This study focuses on how rainfall and reservoir water level decline affect the seepage and displacement field of Baijiabao landslide spatially and temporally during drawdown of reservoir water level in the Three Gorges Reservoir Area, thus exploring its movement mechanism. The monitoring data of the landslide in the past 10 years were analyzed, and the correlation between rainfall, reservoir water level decline, and landslide displacement was clarified. By the numerical simulation method, the deformation evolution mechanism of this landslide during drawdown of reservoir water level was revealed, respectively, under three conditions, namely, rainfall, reservoir water level decline, and coupling of the above two conditions. The results showed that the deformation of the Baijiabao landslide was the coupling effect of rainfall and reservoir water level decline, while the latter effect is more pronounced.