Glacier debris flow is one of the most critical categories of geological hazards in high-mountain regions. To reduce its potential negative effects, it needs to investigate the susceptibility of glacier debris flow. However, when evaluating the susceptibility of glacier debris flow, most research work considered the impact of existing glacier area, while ignoring the impact of changes in glacier ablation volume. In this paper, we considered the impact of the changes in the glacier ablation volume to investigate the susceptibility of glacier debris flow. We proposed to evaluate the susceptibility analysis in G217 gullies with frequent glacial debris flow on the Duku highway, Xinjiang Province. Specifically, by using the simple band ratio method with the manual correction to identify glacier outlines, we identified the ablation zone by comparing the glacier boundary in 2000 with that in 2015. We then calculated ablation volume by changes in glacier elevation and ablation area from 2000 to 2015. Finally, we used the volume of glacier melting in different watersheds as the main factor to evaluate the susceptibility based on the improved geomorphic information entropy (GIE) method. We found that, overall, the improved GIE method with a correction coefficient based on the glacier ablation volume is better than the previous method. Deglaciation can be adapted to analyze glacier debris flow susceptibility based on glaciology and geomorphology. Our presented work can be applied to other similar glacial debris flow events in high-mountain regions.

Mesh quality is a critical issue in numerical computing because it directly impacts both computational efficiency and accuracy. Tetrahedral meshes are widely used in various engineering and science applications. However, in large-scale and complicated application scenarios, there are a large number of tetrahedrons, and in this case, the improvement of mesh quality is computationally expensive. Laplacian mesh smoothing is a simple mesh optimization method that improves mesh quality by changing the locations of nodes. In this paper, by exploiting the parallelism features of the modern graphics processing unit (GPU), we specifically designed a parallel adaptive Laplacian smoothing algorithm for improving the quality of large-scale tetrahedral meshes. In the proposed adaptive algorithm, we defined the aspect ratio as a metric to judge the mesh quality after each iteration to ensure that every smoothing improves the mesh quality. The adaptive algorithm avoids the shortcoming of the ordinary Laplacian algorithm to create potential invalid elements in the concave area. We conducted 5 groups of comparative experimental tests to evaluate the performance of the proposed parallel algorithm. The results demonstrated that the proposed adaptive algorithm is up to 23 times faster than the serial algorithms; and the accuracy of the tetrahedral mesh is satisfactorily improved after adaptive Laplacian mesh smoothing. Compared with the ordinary Laplacian algorithm, the proposed adaptive Laplacian algorithm is more applicable, and can effectively deal with those tetrahedrons with extremely poor quality. This indicates that the proposed parallel algorithm can be applied to improve the mesh quality in large-scale and complicated application scenarios.

The discrete element method (DEM) can be effectively used in investigations of the deformations and failures of jointed rock slopes. However, when to appropriately terminate the DEM iterative process is not clear. Recently, a displacement-based discrete element modeling method for jointed rock slopes was proposed to determine when the DEM iterative process is terminated, and it considers displacements that come from rock blocks located near the potential sliding surface that needs to be determined before the DEM modeling. In this paper, an energy-based discrete element modeling method combined with time-series analysis is proposed to investigate the deformations and failures of jointed rock slopes. The proposed method defines an energy-based criterion to determine when to terminate the DEM iterative process in analyzing the deformations and failures of jointed rock slopes. The novelty of the proposed energy-based method is that, it is more applicable than the displacement-based method because it does not need to determine the position of the potential sliding surface before DEM modeling. The proposed energy-based method is a generalized form of the displacement-based discrete element modeling method, and the proposed method considers not only the displacement of each block but also the weight of each block. Moreover, the computational cost of the proposed method is approximately the same as that of the displacement-based discrete element modeling method. To validate that the proposed energy-based method is effective, the proposed method is used to analyze a simple jointed rock slope; the result is compared to that achieved by using the displacement-based method, and the comparative results are basically consistent. The proposed energy-based method can be commonly used to analyze the deformations and failures of general rock slopes where it is difficult to determine the obvious potential sliding surface.