• Journal of the Korean Society of Environmental Restoration Technology
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• v.2 no.3
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• pp.32-37
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• 1999

There is a need to suggest the standards of selection on the cuttings, because the selection of the willow(Salix) cuttings is very important, which will be used as the bioengineering revegetation material to protect the slope by strengthening soil and preventing soil erosion under the bad site conditions. In this study, we measured the lengths and the diameters of original willow cuttings, the total numbers and the lengths of the new shoots and roots after 15 months since the experimental construction of the slope revegetation technology of biological engineering was conducted, and analyzed the correlation between the lengths and the diameters of willow cuttings and the lengths of new roots using the SPSS program. The results are as follows; First, the lower the elevation of tested slope was, the more the number of new shoots and the average lengths of new roots increased. Secondly, the ratio of underground parts and aboveground parts was 4.24 ~ 5.93 proving the fact that the willow(Salix) is one of the species deep rooted with developed underground parts. Thirdly, there is a strong correlation between the diameters of willow cuttings and the total lengths of new roots, whereas, there is no correlation between the lengths of willow cuttings and the total lengths of new roots. In conclusion, it is more efficient for the early rapid revegetation and slope stabilization to select willow cuttings with the biggest possible diameters than with the longest lengths as the slope revegetation materials of biological engineering.

• Journal of the Mineralogical Society of Korea
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• v.23 no.2
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• pp.107-115
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• 2010

Removal and mineralization of dissolved uranium by bacteria in KURT (KAERI Underground Research Tunnel), Korea Atomic Energy Research Institute (KAERI) was investigated. Two different bacteria, IRB (iron-reducing bacteria) and SRB (sulfate-reducing bacteria) was used, and minerals formed by these bacteria were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). Compared to uranyl ions, ferric ions were preferentially reduced by IRB, showing that there is no significant reduction and removal of uranium. However, uranium concentration considerably decreased by addition of Mn(II). Results show that a sulfide mineral such as mackinawite (FeS) is formed by SRB respiration through combination of Fe(II) and S without manganese sulfide formation. In the presence of Mn(II), however, uranium is removed effectively, suggesting that the sorption and incorporation of uranium could be affected by Mn(II) onto the sulide minerals.

• Tunnel and Underground Space
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• v.20 no.5
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• pp.309-317
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• 2010

CCS (Carbon dioxide Capture and Storage) is a means of mitigating the contribution of $CO_2$ to the Greenhouse gas, from large point sources such as power plants and steel companies. CCS is a process whereby $CO_2$ is captured from gases produced by fossil fuel combustion, compressed, transported and injected into deep geologic formations for permanent storage. CCS applied to a conventional power plant can reduce $CO_2$ emissions to the atmosphere by approximately 80~90% compared to a plant without CCS. The IPCC estimates that the economic potential of CCS will be between 10% and 55% of the total carbon mitigation effort by year 2100. In this paper, overseas sites where CCS technology is being applied and technical development trends for CCS are briefly reviewed.

• Journal of the Korean Society for Railway
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• v.18 no.6
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• pp.513-521
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• 2015

When a GTX travels through a deep-level underground tunnel at a speed of 180km/h, ear-discomfort in passengers due to the pressure wave generated could be an issue due to the small cross-sectional area. Therefore, appropriate pressure-tightness values for GTX trains must be secured as a countermeasure. In this paper, a 1D numerical analysis was conducted to determine the pressure-tightness coefficient which allows a pressure change meet the criteria. The pressure transients in a tunnel and in a passenger car are predicted considering an A-line underground tunnel with a length of 37km and its operation schedule. The required pressure-tightness of the car is predicted to be three seconds and 6 seconds respectively for a single track and a double- track tunnel to prevent aural discomfort in passengers. The result of this study are expected to serve as useful information to those involved in the development of various solutions to improve air-tightness of GTX passenger cars.

• Tunnel and Underground Space
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• v.30 no.6
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• pp.519-539
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• 2020

We reviewed numerical approaches to assess a hydraulic properties of excavation-disturbed zone (EDZ)created in argillaceous sedimentary rocks. It has been reported that fractures in the sedimentary rocks containing expansive clays are gradually closing due to swelling and their permeabilities are evolving to the level of in-tact rock, which is known as a self-healing or self-sealing process. The numerical approaches introduced here are capable of simulating spatio-temporal variation of EDZ permeability during long-term operation of a repository by including the self-healing characteristics of fractures, which wa observed in laboratory as well as in-situ experiments, The applicability of the numerical approaches was verified from the comparison to in-situ measurements of EDZ permeability at underground research laboratories.

• Geomechanics and Engineering
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• v.29 no.2
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• pp.99-111
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• 2022

Instability of bolted rock mass has been a major hazard in the underground coal mining industry for decades. Developing effective support guidelines requires understanding of complex bolted rock mass failure mechanisms. In this study, the dynamic failure behavior, mechanical behavior, and energy evolution of a laboratory-scale bolted specimens is studied by conducting laboratory static-dynamic coupled loading tests. The results showed that: (1) Under static-dynamic coupled loading, the stress-strain curve of the bolted rock mass has a significant impact velocity (strain rate) correlation, and the stress-strain curve shows rebound characteristics after the peak; (2) There is a critical strain rate in a rock mass under static-dynamic coupled loading, and it decreases exponentially with increasing pre-static load level. Bolting can significantly improve the critical strain rate of a rock mass; (3) Compared with a no-bolt rock mass, the dissipation energy ratio of the bolted rock mass decreases exponentially with increasing pre-static load level, the ultimate dynamic impact energy and dissipation energy of the bolted rock mass increase significantly, and the increasing index of the ratio of dissipation energy increases linearly with the pre-static load; (4) Based on laboratory testing and on-site microseismic and stress monitoring, a design method is proposed for a roadway bolt support against dynamic load disturbance, which provides guidance for the design of deep underground roadway anchorage supports. The research results provide new ideas for explaining the failure behavior of anchorage supports and adopting reasonable design and construction practices.

• Journal of the Korean association of regional geographers
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• v.14 no.3
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• pp.212-223
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• 2008

The rainfall partitioning in a monogenetic volcano has been analysed using the hydrological data of a small catchment on Eoseungsaeng-oreum of Mount Halla and the meterological data of Eorimok Automated Weather System. The experimental catchment extends from 965 m to 1,169 m in altitude, and has an catchment area of $51,000\;m^2$ Eoseungsaeng-oreum is the scoria cone predominantly covered with Carpinus laxiflora and Quercus serrata. The analyzed periods are April 30 to September 12 and October 7 to November 19, 2007. The experimental catchment exhibits the total precipitation of 2,296.5 mm. Surface runoff amounts to 465 mm that is equivalent to 20.2% of the precipitation. By contrast, evapotranspiration accounts for 25.9% of the precipitation, and the remnant of 1,236.5 mm deep1y percolates underground through a basement. The rainy summer season, in particular, shows the highest deep percolation ratio of 62.2%. The deep percolation ratio of the experimental catchment is at 1east more two times than the ratio of a gneiss basin in Korea Peninsular. It has suggested that the experimental catchment is characterized by the higher portion of deep percolation in rainfall partitioning which reflects the highly permeable lithology in Jeju Island.

• 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.

• Journal of Korea Water Resources Association
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• v.52 no.5
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• pp.313-323
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• 2019

Deep Tunnel system is a large-scale urban flood control facility installed underground in order to reinforce the lack of drainage systems in developed cities. In a structure like a deep tunnel system, the undular bore generated in the downstream causes a problem in the hydraulic stability of the tunnel. In this study, to investigate the influence of the undular bore on the hydraulic stability at the "Shinwol rainwater storage and drainage system", under construction for the first time in the country, a hydraulic model experiment was conducted on various flooding inflow scenarios. As a result of the hydraulic model experiment carried out in this study, the undular bore generated downstream is trapped in the pipe while moving to upstream, pushes the compressed air. It is judged that overflow occurred by choking the vertical drop shaft in the process when this compressed air is being exhaust through the upstream vertical drop shaft and blocking flood inflow. In addition, the analysis of velocity of undular bore shows that the undular bore transfers energy, and at this time, the pressure rose in the pipe and the velocity increment occurred of the undular bore. Further studies are needed to predict the size and velocity of undular bore, which plays an important role in the hydraulic stability of the tunnel in the deep tunnel system.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.508-518
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• 2023

This paper presents a new approach for the automatic mapping of discontinuities in a tunnel face based on its 3D digital model reconstructed by LiDAR scan or photogrammetry techniques. The main idea revolves around the identification of discontinuity areas in the 3D digital model of a tunnel face by segmenting its 2D projected images using a deep-learning semantic segmentation model called U-Net. The proposed deep learning model integrates various features including the projected RGB image, depth map image, and local surface properties-based images i.e., normal vector and curvature images to effectively segment areas of discontinuity in the images. Subsequently, the segmentation results are projected back onto the 3D model using depth maps and projection matrices to obtain an accurate representation of the location and extent of discontinuities within the 3D space. The performance of the segmentation model is evaluated by comparing the segmented results with their corresponding ground truths, which demonstrates the high accuracy of segmentation results with the intersection-over-union metric of approximately 0.8. Despite still being limited in training data, this method exhibits promising potential to address the limitations of conventional approaches, which only rely on normal vectors and unsupervised machine learning algorithms for grouping points in the 3D model into distinct sets of discontinuities.