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| 1 | A new analytical solution for calculation the displacement and shear stress of fully grouted rock bolts and numerical verifications显示文摘In presence of difficult conditions in coal mining roadways, an adequate stabilization of the excavation boundary is required to ensure a safe progress of the construction. The stabilization of the roadways can be improved by fully grouted rock bolt, offering properties optimal to the purpose and versatility in use. Investigations of load transfer between the bolt and grout indicate that the bolt profile shape and spacing play an important role in improving the shear strength between the bolt and the surrounding strata. This study proposes a new analytical solution for calculation displacement and shear stress in a fully encapsulated rock bolt in jointed rocks. The main characteristics of the analytical solution consider the bolt profile and jump plane under pull test conditions. The performance of the proposed analytical solution, for three types of different bolt profile configurations, is validated by ANSYS software. The results show there is a good agreement between analytical and numerical methods. Studies indicate that the rate of displacement and shear stress from the bolt to the rock exponentially decayed. This exponential reduction in displacement and shear stress are dependent on the bolt characteristics such as: rib height, rib spacing, rib width and grout thickness, material and joint properties. | Ghadimi Mostafa Shariar Koroush Jalalifar Hossein | 2016 | International Journal of Mining Science and Technology2016，26，6： | 7 |
| 2 | A numerical investigation of the effect of thermoelectromagnetic convection (TEMC) on the Bridgman growth of Ge 1? x Si x显示文摘 | Serhat Yesilyurt Ljubomir Vujisic Shariar Motakef F.R Szofran Martin P Volz | 1999 | Journal of Crystal Growth1999，，4： | 2 |
| 3 | Laser-heating thermal modulation voltammetric determination of phosphate ion using a graphite-reinforced carbon electrode显示文摘 | Shariar S M Suga M Nishikawa | 2009 | Analytical Sciences2009，25，4： | 1 |
| 4 | Enhanced 3D Point Cloud Reconstruction for Light Field Microscopy Using U-Net-Based Convolutional Neural Networks显示文摘This article describes a novel approach for enhancing the three-dimensional(3D)point cloud reconstruction for light field microscopy(LFM)using U-net architecture-based fully convolutional neural network(CNN).Since the directional view of the LFM is limited,noise and artifacts make it difficult to reconstruct the exact shape of 3D point clouds.The existing methods suffer from these problems due to the self-occlusion of the model.This manuscript proposes a deep fusion learning(DL)method that combines a 3D CNN with a U-Net-based model as a feature extractor.The sub-aperture images obtained from the light field microscopy are aligned to form a light field data cube for preprocessing.A multi-stream 3D CNNs and U-net architecture are applied to obtain the depth feature fromthe directional sub-aperture LF data cube.For the enhancement of the depthmap,dual iteration-based weighted median filtering(WMF)is used to reduce surface noise and enhance the accuracy of the reconstruction.Generating a 3D point cloud involves combining two key elements:the enhanced depth map and the central view of the light field image.The proposed method is validated using synthesized Heidelberg Collaboratory for Image Processing(HCI)and real-world LFM datasets.The results are compared with different state-of-the-art methods.The structural similarity index(SSIM)gain for boxes,cotton,pillow,and pens are 0.9760,0.9806,0.9940,and 0.9907,respectively.Moreover,the discrete entropy(DE)value for LFM depth maps exhibited better performance than other existing methods. | Shariar Md Imtiaz Ki-Chul Kwon F.M.Fahmid Hossain MdBiddut Hossain Rupali Kiran Shinde Sang-Keun Gil Nam Kim | 2023 | Computer Systems Science & Engineering2023，47，12： | 0 |
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