Research on the Deformation Mechanism of Outlet High Slope of Some Hydropower Station Diversion Tunnel

2011 ◽  
Vol 99-100 ◽  
pp. 862-865
Author(s):  
Hua Feng Deng ◽  
Min Zhu ◽  
Jing Guo ◽  
Tao Lu
Keyword(s):  
Deformation Mechanism ◽  
Slope Deformation ◽  
Hydropower Station ◽  
Long Term Effects ◽  
Reservoir Water ◽  
Diversion Tunnel ◽  
Reservoir Water Level ◽  
Reservoir Impounding ◽  
Deformation Law ◽  
Rock Mass Deformation

During the operation of outlet high slop of the hydropower station diversion tunnel, the monitoring data shown that the upper slope had an abnormal deformation tendency toward the upstream, which was different from the general slope deformation law. The paper analyzed the deformation mechanism of the high slop outside the hydropower station diversion tunnel in detail based on detailed analysis of the geological data. The analysis shown that the basic reasons of slope deformation were the upper hard and lower soft structure characteristics and the fully developed interlayer shear zone; the excavation unloading, reservoir impounding, reservoir water level change, rainfall, flood discharge atomization, rock weathering, water-rock long-term effects, and some other factors induce and aggravate the rock mass deformation.

Rock slope deformation mechanism in the Cihaxia Hydropower Station, Northwest China

2014 ◽  
Vol 74 (3) ◽  
pp. 943-958 ◽  
Author(s):  
Zelin Zhang ◽  
Gao Liu ◽  
Shuren Wu ◽  
Huiming Tang ◽  
Tao Wang ◽  
...  
Keyword(s):  
Deformation Mechanism ◽  
Rock Slope ◽  
Northwest China ◽  
Slope Deformation ◽  
Hydropower Station

Effect of Permeability Coefficient of Reservoir Bank Slope on Pile Displacement and Ground Deformation

2013 ◽  
Vol 275-277 ◽  
pp. 304-309
Author(s):  
Guo Dong Zhang ◽  
Peng Du ◽  
Qing Ling Yi ◽  
Wen Luo ◽  
Xiao Hu Yu
Keyword(s):  
Deformation Mechanism ◽  
Permeability Coefficient ◽  
Ground Deformation ◽  
Safety Evaluation ◽  
Horizontal Displacement ◽  
Deformation Characteristics ◽  
Reservoir Water ◽  
Reservoir Water Level ◽  
Bank Slope ◽  
Reservoir Bank Slope

Due to effect of reservoir water, the deformation mechanism of reservoir bank slope has a great of influence to the buildings which locate on the bank slope. Considering the changes of permeability coefficient of ground, the deformation characteristics of bank slope ground and pile are analyzed based on the method of pile-soil interaction under the condition that the reservoir water level changing speed is invariable. The results revealed that the larger horizontal displacement of the ground and piles happened when the ground has a smaller permeability coefficient, and the larger settlement of the ground and pile happened, especially the pile which has greater differential settlement when the permeability coefficient of ground is larger. The results have certain reference significance on the safety evaluation and design of buildings which locate on reservoir bank slope.

scholarly journals Deformation Process and Mechanism Analyses of a Rock Slope Based on Long-Term Monitoring at the Pubugou Hydropower Station, China

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Xuefeng Mei ◽  
Nengfeng Wang ◽  
Guotao Ma ◽  
Jie Wang ◽  
Yan Wang ◽  
...  
Keyword(s):  
Rock Mass ◽  
Rock Slope ◽  
Fractured Rock ◽  
Road Construction ◽  
Hydropower Station ◽  
Small Scale ◽  
Reservoir Water ◽  
Reservoir Water Level ◽  
Deformation And Failure ◽  
Concrete Frame

This paper presents a typical 450 m high rock slope in a highly jointed and fractured rock mass at Pubugou (PBG) hydropower station on the Dadu River. We established a set of multiphase field geological survey combined with GPS, inclinometers, and piezometer monitoring system to analyze the deformation and failure mechanism of rock slope. The results show that small-scale excavation in road construction disrupted the balance of the Pubugou rock slope (PBGRS), and several local retrogressive failures occurred at the toe. Monitoring data regarding surface and subsurface movements show that the PBGRS is stable as a whole. The deformation concentrated mainly in the loosened fractured zone, which was a feature with sliding-compression cracking. Highly loosened rock mass was the predominant factor affecting the stability of the PBGRS, while the role of reservoir water level fluctuation, though positive, was not significant. Overall, the PBGRS still has a high potential for further development, especially in the slope’s upper zone. To reinforce the slope, measurements mainly consist of the concrete frame combined with anchor cables constructed on the slope. In this study, the analysis was carried out of pre- and postreinforcement measure slope stability with numerical simulation, and safety factor increased from 1.09 to 1.21. This study’s findings have important implications to the analytical method and reinforcement design with geological settings like that of the PBGRS.

scholarly journals Analysis of Deformation Characteristics of Reverse Slope Under The Influence of Reservoir Water Based On Community Detection

2021 ◽  
Author(s):  
Liangfu Xie ◽  
jianbin cui ◽  
Yongjun Qin ◽  
Liewang Qiu
Keyword(s):  
Community Detection ◽  
Geometric Characteristic ◽  
Deformation Characteristic ◽  
Detection Algorithm ◽  
Slope Deformation ◽  
Deformation Characteristics ◽  
Reservoir Water ◽  
Reservoir Water Level ◽  
Severe Deformation ◽  
Community Detection Algorithm

Abstract In order to study the deformation characteristics of reverse slope, this paper took the slope of Xiaodongcao as the research object, applied the Louvain community detection algorithm, considered the influence of reservoir water level change, partitioned the slope deformation characteristics. The deformation characteristic zoning result was superimposed with the slope displacement cloud map and three types of geological geometric characteristic factor zoning map obtained by ArcGIS. The results show that：Community detection can quickly identify the closely connected part of slope network, and the specific location of this part is affected by reservoir water. After the community detection result is superimposed with the displacement cloud map, the areas with large deformation and close connection in the slope can be identified. It is found that the community with severe deformation have at least 5% more displacement and up to 21% more displacement than that with slow deformation. In addition, the location of leader nodes can be identified, and the number of leader nodes does not exceed 20% of the total nodes in the community, and its average displacement is at least 10% more than that of ordinary nodes, up to 36%. After the community detection result is superimposed with the zoning map of slope grade, it can be concluded that the slope grade within the community with severe deformation is greater than 60°, indicating that the larger slope grade is more sensitive to the bank slope deformation.

scholarly journals The Monitoring-Based Analysis on Deformation-Controlling Factors and Slope Stability of Reservoir Landslide: Hongyanzi Landslide in the Southwest of China

Geofluids ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Bing Han ◽  
Bin Tong ◽  
Jinkai Yan ◽  
Chunrong Yin ◽  
Liang Chen ◽  
...  
Keyword(s):  
Water Level ◽  
Water Pressure ◽  
Monitoring Program ◽  
Significant Risk ◽  
Controlling Factors ◽  
Seepage Water ◽  
Reservoir Water ◽  
Reservoir Water Level ◽  
Reservoir Area ◽  
Reservoir Landslide

Reservoir landslide is a type of commonly seen geological hazards in reservoir area and could potentially cause significant risk to the routine operation of reservoir and hydropower station. It has been accepted that reservoir landslides are mainly induced by periodic variations of reservoir water level during the impoundment and drawdown process. In this study, to better understand the deformation characters and controlling factors of the reservoir landslide, a multiparameter-based monitoring program was conducted on a reservoir landslide—the Hongyanzi landslide located in Pubugou reservoir area in the southwest of China. The results indicated that significant deformation occurred to the landslide during the drawdown period; otherwise, the landslide remained stable. The major reason of reservoir landslide deformation is the generation of seepage water pressure caused by the rapidly growing water level difference inside and outside of the slope. The influences of precipitation and earthquake on the slope deformation of the Hongyanzi landslide were insignificant.

scholarly journals Application of Neural Network Models and ANFIS for Water Level Forecasting of the Salve Faccha Dam in the Andean Zone in Northern Ecuador

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2011
Author(s):  
Pablo Páliz Larrea ◽  
Xavier Zapata Ríos ◽  
Lenin Campozano Parra
Keyword(s):  
Neural Network ◽  
Water Level ◽  
Clustering Algorithm ◽  
Network Models ◽  
Water Levels ◽  
Subtractive Clustering ◽  
Neural Network Models ◽  
Reservoir Water ◽  
Reservoir Water Level ◽  
Maximum Delay

Despite the importance of dams for water distribution of various uses, adequate forecasting on a day-to-day scale is still in great need of intensive study worldwide. Machine learning models have had a wide application in water resource studies and have shown satisfactory results, including the time series forecasting of water levels and dam flows. In this study, neural network models (NN) and adaptive neuro-fuzzy inference systems (ANFIS) models were generated to forecast the water level of the Salve Faccha reservoir, which supplies water to Quito, the Capital of Ecuador. For NN, a non-linear input–output net with a maximum delay of 13 days was used with variation in the number of nodes and hidden layers. For ANFIS, after up to four days of delay, the subtractive clustering algorithm was used with a hyperparameter variation from 0.5 to 0.8. The results indicate that precipitation was not influencing input in the prediction of the reservoir water level. The best neural network and ANFIS models showed high performance, with a r > 0.95, a Nash index > 0.95, and a RMSE < 0.1. The best the neural network model was t + 4, and the best ANFIS model was model t + 6.

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