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Often when rock discontinuities with complex distributions occur in steep terrain, it is difficult to rapidly survey and accurately measure their spatial distribution by traditional surveying and mapping methods. This paper presents a methodology for automated extraction of rock discontinuities from a point cloud and the resulting 3D digital surface model of the rock mass. First, feature planes of rock discontinuities are identified and classified using both their orientation and position in a double-nested Mean-shift Clustering Algorithm. Second, the points corresponding to feature planes are extracted using a Region Growth Algorithm and seed points. Finally, geological information is acquired by analysing the geometric features of the extracted sub-set of points from the point cloud. This approach can directly extract planar features associated with joints and it eliminates spurious points in a point cloud associated with objected such as vegetation. A case study of a rock slope along a highway is presented using the proposed method. A sensitivity analysis of relevant clustering parameters in the Mean-shift Clustering Algorithm is conducted to acquire their optimal values and to assess their robustness. The proposed method produces results that agree with the traditional survey methods and greatly improves the survey efficiency.

Purely empirical and numerical methods are widely used in landslide movement prediction because they can forecast the failure time and consider influence factors, respectively. However, the combination of these two methods for prediction is rare. This paper develops an integrated landslide movement prediction model that can fully consider landslide kinematics and external influence factors using the Verhulst inverse function (VIF) and the random forest (RF) algorithm. The VIF is applied to describe the kinematic behavior of landslides using the rationale of three-stage creep deformation. The RF algorithm is to quantify the response of landslide displacement to the influence of external factors such as reservoir water level and rainfall intensities. The novelty of the VIF-RF model is illustrated by applying to a reservoir landslide, Gapa Landslide, in Southwestern China. The results show that the VIF-RF model shows significant improvement in predicting landslide movement compared with the VIF or RF model. The error analysis confirms that the root mean square error of the VIF-RF decreases by more than 20% compared with the VIF and RF models. In addition, the mean absolute percentage error of the VIF-RF models is less than 5%, a decrease by 2.3% and 10.1% compared to the VIF and RF models, respectively. The feasibility of the VIF-RF model for predicting movement of other reservoir landslides was successfully verified by the Majiagou landslide in the TGRA. The developed VIF-RF model indicates the Gapa landslide deformation is at the primary stage over the monitoring period. The displacement at the G1 and G2 monitoring locations of the Gapa landslide is projected to increase to 2719.8 and 2438.8 mm in January 2021, respectively, and the average rate in the accelerated deformation periods is projected to be 67.8 mm/month. The presented VIF-RF model provides an effective approach for predicting the long-term landslide deformation and identifying its deformation stage.

The geometric shape and size of sand grains are key factors that affect the mechanical and hydraulic properties of sandy soils. These morphological properties are commonly quantified via analysis of two-dimensional microscopy photos while three-dimensional measurements, such as using X-ray micro-computed tomography, are being adopted to understand and characterize the behaviours of granular materials. This study explores the relationship between two- and three-dimensional morphological properties for fragmented sand grains. Three-dimensional morphological properties of representative grains with different combinations of elongation and flatness were measured with X-ray micro-computed tomography. A framework that integrates discrete element modelling and sand grain imaging is introduced for obtaining the two-dimensional vertical projections of these grains after freefalls onto a horizontal surface. Matlab code was developed to extract the 2D silhouette outline of each grain for measuring 2D morphological properties. The relationships between 2D and 3D morphological properties were quantified, and useful empirical equations were developed. The results show that five 3D morphological properties (length, breadth, volume, surface area, and elongation) can be estimated from the 2D morphological properties of length2D, breadth2D, projection area, and aspect ratio. Estimates of 3D morphological properties including sphericity, volume, and surface area can be improved when flatness is known. A practical approach to obtain flatness from the 2D morphological analysis results is provided. The newly developed equations were evaluated using virtual soil samples and compared with previously published data for natural grains. Use of the developed equations to estimate specific surface area and permeability of soils was demonstrated.

Current dominant methods for slope stability analysis are the limit equilibrium method and the strength reduction method. Both methods are based on the limit equilibrium conditions. However, the limit equilibrium methods are limited to the rigid body assumption, while the strength reduction method is computationally expensive and has convergence issues due to the non-linear iterative computations. In this paper, we propose a current stress-based search algorithm to directly obtain the critical slip surface and the safety factor. The numerical manifold method, which unifies the continuum and discontinuum analysis problems, is used for stress analysis to obtain the stress distribution of soil slopes or rock slopes cut by joints. Based on the stress results obtained, a graph theory is used to convert the solution of the critical slip surface to a shortest path problem, which can be directly solved by the Bellman–Ford algorithm. The proposed method couples the numerical manifold method and the graph theory allowing for stability analyses of both rock and soil slopes within the same framework. The method completely removes the computational effort needed for iterations in the strength reduction method as well as eliminating the rigid body assumptions in the limit equilibrium method.