• Journal of Korean Tunnelling and Underground Space Association
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• v.21 no.6
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• pp.763-778
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• 2019

Abrasive waterjet cutting technology has been used for rock excavation of tunnels and underground structures due to various advantages. In order to cut rocks by using the abrasive waterjet system, abrasive is essential to enhance impact energies for fracturing the target rock. Since garnet abrasives are not produced in Korea, alternative abrasives, instead of garnets, are needed to achieve the economical waterjet cutting. This study is to analyze cutting performance for rocks with sandy particles as alternative abrasive. Cutting tests were carried out on granite specimens at the constant waterjet energy (e.g., water pressure or water flow rate). The five kinds of sands, sampled by construction fields and natural sites, were prepared to perform the experimental tests. When sea sand was used as an alternative abrasive, cutting performance was secured to be 60~70% compared to the commercial garnet abrasive. Thus, it is expected that sand abrasives can be applied on the waterjet cutting process for the economical excavation construction.

• Journal of Korean Tunnelling and Underground Space Association
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• v.17 no.5
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• pp.533-551
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• 2015

The rock fracturing during waterjet cutting is very complicated because rock is inhomogeneous and anisotropic, compared with artificial materials (e.g., metal or glass). Thus, it is very important to verify the effects of rock properties on waterjet rock cutting performance. Properties affecting the rock cutting efficiency have been variously described in the literature, depending on the experimental conditions (e.g., water pressure, abrasive feed rate, or standoff distance) and rock-types studied. In this study, a rock-property-related literature review was performed to determine the key properties important for waterjet rock cutting. Porosity, uniaxial compressive strength, and hardness of the rock were determined to be the key properties affecting waterjet rock cutting. The results of this analysis can provide the basic knowledge to determine the cutting efficiency of waterjet rock cutting technology for rock excavation-related construction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.4
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• pp.409-415
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• 2020

Low-flow mortar injection method grouting technology was selected and the traffic area was preserved as much as possible in order to secure safety for road traffic when the outflow and subsidence of landfill occurred due to ground-water, and etc. In particular, the current existing method was newly improved since there are risks of damage such as hydraulic fracturing at the lower part of the road, spilling of soil particles on steep slopes, and bumps on the road due to excessive injection pressure during construction. This study was carried out at the site of reinforcement work on the road as a maintenance work for the danger zone for collapse of the steep slope of the 00 hill, which was ordered from the 00 city 00 province. The improved low-flow mortar type grouting method adopted a new automated grouting management system and especially, it composites the method for grouting conditions decision by high-pressure pre-grouting test and injection technology by AGS-controlled and studied about grouting effect analysis by using new technology. By applying the improved low-flow mortar type grouting method, it was possible to lay the groundwork for road maintenance work such as the prevention of subsidence of old roads, uneven subsidence of buildings and civil engineering structures, and of soil leakage of ground-water spills. Furthermore, the possibility of application on future grouting work not only for just construction that prevents subsidence of old roads but also for various buildings and civil engineering structures such as railroads, subways, bridges, underground structures, and boulder stone and limestone areas was confirmed.

• Tunnel and Underground Space
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• v.29 no.3
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• pp.184-196
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• 2019

This study aims to extract a 3D image of micro-cracks generated by hydraulic fracturing tests, using the deep learning method and X-ray computed tomography images. The pixel-level cracks are difficult to be detected via conventional image processing methods, such as global thresholding, canny edge detection, and the region growing method. Thus, the convolutional neural network-based encoder-decoder network is adapted to extract and analyze the micro-crack quantitatively. The number of training data can be acquired by dividing, rotating, and flipping images and the optimum combination for the image augmentation method is verified. Application of the optimal image augmentation method shows enhanced performance for not only the validation dataset but also the test dataset. In addition, the influence of the original number of training data to the performance of the deep learning-based neural network is confirmed, and it leads to succeed the pixel-level crack detection.