The Experts below are selected from a list of 22710 Experts worldwide ranked by ideXlab platform
Yongtao Yang - One of the best experts on this subject based on the ideXlab platform.
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A Simplified Solution for Calculating the Phreatic Line and Slope Stability during a Sudden Drawdown of the Reservoir Water Level
Geofluids, 2018Co-Authors: Guanhua Sun, Lin Shan, Wei Jiang, Yongtao YangAbstract:On the basis of the Boussinesq unsteady seepage differential equation, a new simplified formula for the phreatic line of slopes under the condition of decreasing Reservoir Water Level is derived by means of the Laplacian matrix and its inverse transform. In this context, the expression of normal stress on the slip surface under seepage forces is deduced, and a procedure for obtaining the safety factors under hydrodynamic forces is proposed. A case study of the Three Gorges Reservoir is used to analyze the influences of the Water Level, decreasing velocity and the permeability coefficient on slope stability.
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Phreatic line calculation and stability analysis of slopes under the combined effect of Reservoir Water Level fluctuations and rainfall
Canadian Geotechnical Journal, 2017Co-Authors: Guanhua Sun, Yongtao Yang, Shengguo Cheng, Hong ZhengAbstract:Rainfall and Reservoir Water Level fluctuations are the main external factors of landslides in the Three Gorges Reservoir area. To improve the analysis of slope stability under the combined effect of Reservoir Water Level fluctuations and rainfall, a simplified method for phreatic line calculation of slopes is proposed in this study. Based on the obtained phreatic line, the expression of normal stress on the sliding surface of the slope under the hydrodynamic forces is deduced, and a global analysis method to solve the slope safety factor under hydrodynamic force is proposed. Finally, the safety evolution of a slope in the Three Gorges Reservoir area is studied under the combined effect of Reservoir Water Level fluctuations and rainfall.
Wan Hussain Wan Ishak - One of the best experts on this subject based on the ideXlab platform.
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Forecasting Reservoir Water Level based on the change in rainfall pattern using neural network
2018Co-Authors: Raja Nurul Mardhiah Raja Mohamad, Wan Hussain Wan IshakAbstract:Reservoir Water Level is a Level of storage space for Water.During heavy rainfall, Waterstorage space is used to hold excessive amount of Water. During less rainfall, Water storage maintains the Water supply for its major uses.The change in rainfall pattern may influence the Water storage. Thus, understanding the change in rainfall pattern can be used in gate opening decision.On top of that, the upstream precipitation is always not coincide with the consequences and the flood downstream usually cause expensive damages and great devastation as well.This study focus on the analysis of the upstream rainfall data in order to obtain the rainfall pattern.This study deployed basic steps in Artificial Neural Network (ANN) modeling which are data selection, data preparation, data pre-processing and finally Neural Network model development and evaluation. The performance of ANN was based on MAE (mean absolute error) and RMSE (root mean square error). In this study, three datasets have been formed that represent the change in upstream rainfall pattern. The findings show that the best RMSE achieve is 0.644 from the third dataset.
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Forecasting model for the change of Reservoir Water Level stage based on temporal pattern of Reservoir Water Level
2015Co-Authors: Nur Athirah Ashaary, Wan Hussain, Wan Hussain Wan IshakAbstract:Reservoir Water Level forecasting is vital in Reservoir opera- tion and management. The output of the forecasting model can be used in Reservoir decision support systems. This study demonstrates the application of Artificial Neural Network (ANN) in developing the forecasting model for the change of Reservoir Water Level stage. In this study, sliding window tech- nique has been used to extract the temporal pattern that represents time de- lays in the Reservoir Water Level. The patterns are used as input to the ANN model. The results show that a model with 4 days of time delay has pro- duced the acceptable performance with both low error rate and high accura- cy.
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Neural network application in the change of Reservoir Water Level stage forecasting
Indian Journal of Science and Technology, 2015Co-Authors: Nur Athirah Ashaary, Wan Hussain Wan Ishak, Ku Ruhana Ku-mahamudAbstract:Artificial Neural Network is one of the computational algorithms that can be applied in developing a forecasting model for the change of Reservoir Water Level stage. Forecasting of the change of Reservoir Water Level stage is vital as the change of the Reservoir Water Level can affect the Reservoir operator’s decision. The decision of Water release is very critical in both flood and drought seasons where the Reservoir should maintain high volume of Water during less rainfall and enough space for incoming heavy rainfall. The changes of Reservoir Water Level which provides insights on the increase or decrease Water Level that affects Water Level stage. In this study, neural network model for forecasting the change of Reservoir Water Level stage is studied. Six neural network models based on standard back propagation algorithm have been developed and tested. Sliding windows have been used to segment the data into various ranges. The finding shows that 2 days of delay have affected the change in stage of the Reservoir Water Level. The finding was achieved through 4-17-1 neural network architecture.
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Modelling of Reservoir Water Release Decision Using Neural Network and Temporal Pattern of Reservoir Water Level
2014 5th International Conference on Intelligent Systems Modelling and Simulation, 2014Co-Authors: Suriyati Abdul Mokhtar, Wan Hussain Wan Ishak, Norita Md NorwawiAbstract:The Reservoir is one of flood mitigation methods that aim to reduce the effect of flood at downstream flood prone areas. At the same time the Reservoir also serves other purposes. Through modelling, how the Reservoir operator made decisions in the past can be revealed. Consequently, the information can be used to guide Reservoir operator making present decision especially during emergency situations such as flood and drought. This paper discussed modelling of Reservoir Water release decision using Neural Network (NN) and the temporal pattern of Reservoir Water Level. Temporal pattern is used to represent the time delay as the rainfall upstream may not directly raise the Reservoir Water Level. The flow of Water may take some time to reach the Reservoir due to the location. Seven NN models have been developed and tested. The findings show that the NN model with 5-25-1 architecture demonstrate the best performance compare to the other models.
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Neural Network Application in Reservoir Water Level Forecasting and Release Decision
International journal of new computer architectures and their applications, 2011Co-Authors: Wan Hussain Wan Ishak, Ku Ruhana Ku-mahamud, Norita Md NorwawiAbstract:Reservoir dam is one of the defense mechanism for both flood and drought disasters.During flood, the opening of the dam's spillway gate must be adequate to ensure that the Reservoir capacity will not over its limits and the discharges will not cause overflow downstream. While, during drought the Reservoir needs to impound Water and release adequately to fulfil its purposes.Modelling of the Reservoir Water release is vital to support the Reservoir operator to make fast and accurate decision when dealing with both disasters.In this paper, intelligent decision support niodel based on neural network (NN) is proposed. The proposed model consists of situation assessment, forecasting and decision models.Situation assessment utilized temporal data mining technique to extract relevant data and attribute froni the Reservoir operation record.The forecasting model utilize NN to perform forecasting of the Reservoir Water Level, while in the decision model, NN is applied to perform classification of the current and changes of Reservoir Water Level. The simulations have shown that the performances of NN for both forecasting and decision models are acceptably good.
Guanhua Sun - One of the best experts on this subject based on the ideXlab platform.
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A Simplified Solution for Calculating the Phreatic Line and Slope Stability during a Sudden Drawdown of the Reservoir Water Level
Geofluids, 2018Co-Authors: Guanhua Sun, Lin Shan, Wei Jiang, Yongtao YangAbstract:On the basis of the Boussinesq unsteady seepage differential equation, a new simplified formula for the phreatic line of slopes under the condition of decreasing Reservoir Water Level is derived by means of the Laplacian matrix and its inverse transform. In this context, the expression of normal stress on the slip surface under seepage forces is deduced, and a procedure for obtaining the safety factors under hydrodynamic forces is proposed. A case study of the Three Gorges Reservoir is used to analyze the influences of the Water Level, decreasing velocity and the permeability coefficient on slope stability.
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Phreatic line calculation and stability analysis of slopes under the combined effect of Reservoir Water Level fluctuations and rainfall
Canadian Geotechnical Journal, 2017Co-Authors: Guanhua Sun, Yongtao Yang, Shengguo Cheng, Hong ZhengAbstract:Rainfall and Reservoir Water Level fluctuations are the main external factors of landslides in the Three Gorges Reservoir area. To improve the analysis of slope stability under the combined effect of Reservoir Water Level fluctuations and rainfall, a simplified method for phreatic line calculation of slopes is proposed in this study. Based on the obtained phreatic line, the expression of normal stress on the sliding surface of the slope under the hydrodynamic forces is deduced, and a global analysis method to solve the slope safety factor under hydrodynamic force is proposed. Finally, the safety evolution of a slope in the Three Gorges Reservoir area is studied under the combined effect of Reservoir Water Level fluctuations and rainfall.
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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
Engineering Geology, 2016Co-Authors: Guanhua Sun, Hong Zheng, Yaoying HuangAbstract:Abstract Previous studies suggested that the Qianjiangping landslide was caused by the combined effect of rainfall and Reservoir Water after the first Water storage of the Three Gorges Reservoir. The Sanmendong landslide with a length of 830 m, an area of 2.49 × 105 m2, an average thickness of 22 m and a volume of 5.48 × 105 m3, which is located by the Qinggan river, a tributary of the Yangtze River, is only 4 km away from another famous landslide along the same river: the Qianjiangping landslide. Based on the experimental data of mechanical parameters of the landslide and displacement monitoring, a nonlinear mapping relationship between mechanical parameters of the failure mass and the displacement of landslide were established by using genetic algorithms by means of uniform design, numerical calculation and artificial neural networks. The mechanical parameters of the failure mass are obtained by the global minimization of the deviation between the calculated displacements and the monitored displacements. On this basis, the deformation mechanism of the Sanmendong landslide under the combined effect of rainfall and Reservoir Water Level fluctuations was analyzed in detail. The results indicated that the increase of displacement of Sanmendong landslide can be primarily attributed to the combined result of Reservoir Water Level fluctuation and rainfall.
Elena Kozyreva - One of the best experts on this subject based on the ideXlab platform.
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model of erosion landslide interaction in the context of the Reservoir Water Level variations east siberia russia factors environment and mechanisms
Journal of Earth System Science, 2013Co-Authors: Oksana Mazaeva, Viktoria Khak, Elena KozyrevaAbstract:A comprehensive investigation of landslide–erosion interactions has been carried out in the local shore geosystem of the Bykovo site located on the left shore of the Bratsk Reservoir. The landslide process develops in the Mid-Quaternary grounds (aQ 3 ) of the erosion-accumulative terrace’s fragment that comprises sand, sand with pebbles, sandy loams and loams. This study aims to assess the environmental factors of interacting landslide and gully erosion processes, to estimate their temporal dynamics by comparative analysis of cartographic models based on the data of repeated theodolite surveys, and to find out what Level regime of the Reservoir stimulates the activation of the landslide process. The authors propose two-stage descriptive model of erosion–landslide interaction and development mechanisms in the context of the Reservoir Water Level variations in the Bratsk Reservoir. The activation of landslide processes in the Reservoir shores follows the periods of high Water Level stands. Shore slope stability is disturbed by abrasion of slope foot and inundation of the slide zone. The soils subject to landslide, erosion–landslide and erosion processes differ in their microstructure and properties. Largest erosion susceptibility is typical of soils with skeleton-aggregated microstructure, fine- and coarse-silt sandy loams and loams of high porosity, whose interstructural bonds are attributed to Water-soluble salts (Sws = 0.4–0.5%) and high carbonate contents (Scr = 34–66%). High dispersion and aggregation of clay fractions is typical of the loams of the slide zone. The structure of soils subject to deformation slide is represented primarily by fine-sand particles and aggregates with smaller cohesion and strength properties.
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Model of erosion–landslide interaction in the context of the Reservoir Water Level variations (East Siberia, Russia): Factors, environment and mechanisms
Journal of Earth System Science, 2013Co-Authors: Oksana Mazaeva, Viktoria Khak, Elena KozyrevaAbstract:A comprehensive investigation of landslide–erosion interactions has been carried out in the local shore geosystem of the Bykovo site located on the left shore of the Bratsk Reservoir. The landslide process develops in the Mid-Quaternary grounds (aQ $_{\rm II}^{3})$ of the erosion-accumulative terrace’s fragment that comprises sand, sand with pebbles, sandy loams and loams. This study aims to assess the environmental factors of interacting landslide and gully erosion processes, to estimate their temporal dynamics by comparative analysis of cartographic models based on the data of repeated theodolite surveys, and to find out what Level regime of the Reservoir stimulates the activation of the landslide process. The authors propose two-stage descriptive model of erosion–landslide interaction and development mechanisms in the context of the Reservoir Water Level variations in the Bratsk Reservoir. The activation of landslide processes in the Reservoir shores follows the periods of high Water Level stands. Shore slope stability is disturbed by abrasion of slope foot and inundation of the slide zone. The soils subject to landslide, erosion–landslide and erosion processes differ in their microstructure and properties. Largest erosion susceptibility is typical of soils with skeleton-aggregated microstructure, fine- and coarse-silt sandy loams and loams of high porosity, whose interstructural bonds are attributed to Water-soluble salts (Sws = 0.4–0.5%) and high carbonate contents (Scr = 34–66%). High dispersion and aggregation of clay fractions is typical of the loams of the slide zone. The structure of soils subject to deformation slide is represented primarily by fine-sand particles and aggregates with smaller cohesion and strength properties.
Yong Wei - One of the best experts on this subject based on the ideXlab platform.
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Centrifuge Modeling and the Analysis of Ancient Landslides Subjected to Reservoir Water Level Fluctuation
Sustainability, 2020Co-Authors: Xu Qiang, Tang Minggao, He Yang, Yong WeiAbstract:Landslides are among the most severe natural hazards with significant impacts in human life and infrastructure. The Three Gorges Reservoir Area (TGRA) is vulnerable to landslides because of the geological environment and human activities. A centrifuge model test of a landslide with a planar sliding surface in the TGRA was conducted. Based on the multiple monitoring systems composed of a 3D laser scanner, pore Water pressure transducers, particle image velocimetry and earth pressure sensors, multiphysical data were obtained. The work described here had the objective of researching the long-term deformation pattern of this kind of landslide that was subjected to periodic fluctuations in the Reservoir Water Level. The results indicated that the failure processes were characterized by progressive retrogression and cracks caused by the Reservoir drawdown. Transverse tensile cracks first appeared in the submerged zone of the slope. The front part of the slope was dominated by horizontal displacement, while the consolidation and compaction deformation in the vertical direction dominated at the mid-rear part of the slope. When the Water Level dropped again, the front part slid down and fell into the river, but the mid-rear part had no obvious deformation and exhibited a phenomenon of self-stabilization. Moreover, the phreatic line is a concave shape directed into the slope during Reservoir filling and converts to a convex shape pointing out of the slope during Reservoir drawdown. The earth pressures in the slope vary with the failure process of the landslide. Good agreement is obtained for the deformation characteristics between the experimental results and those of prototype landslides.
