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| 1 | Genetic Mechanism of Water-Rich Landslide Considering Antecedent Rainfalls:A Case Study of Pingyikou Landslide in Three Gorges Reservoir Area显示文摘Water-rich slope,which could easily fail after prolonged or heavy rain,is very sensitive to rainfall.Pingyikou Landslide is a typical water-rich slope located in the Three Gorges Reservoir area of China.It was unstable because of the continuous rainfall that occurred from September to October 2017.To understand the deformation process and genetic mechanism of the landslide,the geomorphological features,geological characteristics,hydrological conditions,and rainfall characteristics were systematically studied by a detailed field investigation of the slope and monitoring of rainfall,water level,and displacement.In addition,the influence of different initial conditions on the stability of the slope was also studied through numerical simulation using measured rainfall data on the basis of which,the effect of antecedent rainfall on slope stability was studied by unsaturated seepage analysis method.The results show that the deformation of slope is strongly correlated with the rainfall and groundwater level,and this landslide is a typical rainfall-induced landslide.In the analysis of genetic mechanism of the same type of landslide,a maximum initial pore water pressure of -25 kPa as the initial condition is reasonable.And the antecedent rainfall has a greater effect on the stability of the slope,more than 10 days of antecedent rainfall should be considered when designing and controling the slope. | Defu Tong Aijun Su Fei Tan Jiandong Tang Xiongwei Yi | 2023 | Journal of Earth Science2023，34，6： | 1 |
| 2 | Three-dimensional numerical manifold method for heat conduction problems with a simplex integral on the boundary显示文摘The three-dimensional numerical manifold method(3D-NMM),which is based on the derivation of Galerkin's variation,is a powerful calculation tool that uses two cover systems.The 3D-NMM can be used to handle continue-discontinue problems and extend to THM coupling.In this study,we extended the 3D-NMM to simulate both steady-state and transient heat conduction problems.The modelling was carried out using the raster methods(RSM).For the system equation,a variational method was employed to drive the discrete equations,and the crucial boundary conditions were solved using the penalty method.To solve the boundary integral problem,the face integral of scalar fields and two-dimensional simplex integration were used to accurately describe the integral on polygonal boundaries.Several numerical examples were used to verify the results of 3D steady-state and transient heat-conduction problems.The numerical results indicated that the 3D-NMM is effective for handling 3D both steadystate and transient heat conduction problems with high solution accuracy. | TONG DeFu YI XiongWei TAN Fei JIAO YuYong LIANG JiaWei | 2024 | Science China(Technological Sciences)2024，67，4： | 0 |
| 3 | Rock mass quality classification based on deep learning:A feasibility study for stacked autoencoders显示文摘Objective and accurate evaluation of rock mass quality classification is the prerequisite for reliable sta-bility assessment.To develop a tool that can deliver quick and accurate evaluation of rock mass quality,a deep learning approach is developed,which uses stacked autoencoders(SAEs)with several autoencoders and a softmax net layer.Ten rock parameters of rock mass rating(RMR)system are calibrated in this model.The model is trained using 75%of the total database for training sample data.The SAEs trained model achieves a nearly 100%prediction accuracy.For comparison,other different models are also trained with the same dataset,using artificial neural network(ANN)and radial basis function(RBF).The results show that the SAEs classify all test samples correctly while the rating accuracies of ANN and RBF are 97.5%and 98.7%,repectively,which are calculated from the confusion matrix.Moreover,this model is further employed to predict the slope risk level of an abandoned quarry.The proposed approach using SAEs,or deep learning in general,is more objective and more accurate and requires less human inter-vention.The findings presented here shall shed light for engineers/researchers interested in analyzing rock mass classification criteria or performing field investigation. | Danjie Sheng Jin Yu Fei Tan Defu Tong Tianjun Yan Jiahe Lv | 2023 | Journal of Rock Mechanics and Geotechnical Engineering2023，15，7： | 0 |
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