IntroductionThe use of Top Coal Caving for exploiting the thick coal seam with shallow buried depth most likely has a strong negative impact on the stability.Case descriptionAnjialing No. 1 Underground Mine is located in Shuozhou City, Shanxi Province of China. The 4# Coal Seam of this coal mine is the thick coal seam with shallow buried depth, which has the thickness of 12 m and the depth of 180 m in average. This paper focuses on predicting the distribution of ground fissures and water-conducted fissures induced by the exploiting of the 4# Coal Seam.Discussion and evaluationWe first create a 3D computational model, and then use FLAC software to simulate the mining of coal seam. We then calculate the displacements and tensile strain of the ground surface and strata, and predict the distribution of the ground fissures and water-conducted fissures. Finally, we further analyze the possibility of the perviousness and air leakage of the coal mine on the basis of the predicted distribution of fissures.ConclusionsThe prediction results indicate that: (1) the water-conducted fissures are strongly developed and go through the Neogene aquifuge in some region; thus, it may lead to potential perviousness of coal mine; (2) part of these water-conducted fissures connect with the ground fissures; and this behavior may cause the risk of air leakage.
The flipping classroom as a new thing has been popular in China for many years, and has achieved certain results in teaching methods. The implementation of flipping classrooms still has problems such as insufficient student initiative. This article proposes some targeted measures to address these issues.
In numerical modeling, mesh quality is one of the decisive factors that strongly affects the accuracy of calculations and the convergence of iterations. To improve mesh quality, the Laplacian mesh smoothing method, which repositions nodes to the barycenter of adjacent nodes without changing the mesh topology, has been widely used. However, smoothing a large-scale three dimensional mesh is quite computationally expensive, and few studies have focused on accelerating the Laplacian mesh smoothing method by utilizing the graphics processing unit (GPU). This paper presents a GPU-accelerated parallel algorithm for Laplacian smoothing in three dimensions by considering the influence of different data layouts and iteration forms. To evaluate the efficiency of the GPU implementation, the parallel solution is compared with the original serial solution. Experimental results show that our parallel implementation is up to 46 times faster than the serial version.
The strategy of Divide-and-Conquer (D&C) is one of the frequently used programming patterns to design efficient algorithms in computer science, which has been parallelized on shared memory systems and distributed memory systems. Tzeng and Owens specifically developed a generic paradigm for parallelizing D&C algorithms on modern Graphics Processing Units (GPUs). In this paper, by following the generic paradigm proposed by Tzeng and Owens, we provide a new and publicly available GPU implementation of the famous D&C algorithm, QuickHull, to give a sample and guide for parallelizing D&C algorithms on the GPU. The experimental results demonstrate the practicality of our sample GPU implementation. Our research objective in this paper is to present a sample GPU implementation of a classical D&C algorithm to help interested readers to develop their own efficient GPU implementations with fewer efforts.
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