• Tunnel and Underground Space
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• v.34 no.3
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• pp.208-217
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• 2024

There is so much research effort for developing and implementing deep learning-based surveillance systems to manage health and safety issues in construction sites. Especially, the development of deep learning-based object detection in various environmental changes has been progressing because those affect decreasing searching performance of the model. Among the various environmental variables, the accuracy of the object detection model is significantly dropped under low illuminance, and consistent object detection accuracy cannot be secured even the model is trained using low-light images. Accordingly, there is a need of low-light enhancement to keep the performance under low illuminance. Therefore, this paper conducts a comparative study of various deep learning-based low-light image enhancement models (GLADNet, KinD, LLFlow, Zero-DCE) using the acquired construction site image data. The low-light enhanced image was visually verified, and it was quantitatively analyzed by adopting image quality evaluation metrics such as PSNR, SSIM, Delta-E. As a result of the experiment, the low-light image enhancement performance of GLADNet showed excellent results in quantitative and qualitative evaluation, and it was analyzed to be suitable as a low-light image enhancement model. If the low-light image enhancement technique is applied as an image preprocessing to the deep learning-based object detection model in the future, it is expected to secure consistent object detection performance in a low-light environment.

• Tunnel and Underground Space
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• v.34 no.3
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• pp.218-230
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• 2024

Recently, many studies have been conducted for safety management in construction sites by incorporating computer vision. Anchor box parameters are used in state-of-the-art deep learning-based object detection and segmentation, and the optimized parameters are critical in the training process to ensure consistent accuracy. Those parameters are generally tuned by fixing the shape and size by the user's heuristic method, and a single parameter controls the training rate in the model. However, the anchor box parameters are sensitive depending on the type of object and the size of the object, and as the number of training data increases. There is a limit to reflecting all the characteristics of the training data with a single parameter. Therefore, this paper suggests a method of applying multiple parameters optimized through data split to solve the above-mentioned problem. Criteria for efficiently segmenting integrated training data according to object size, number of objects, and shape of objects were established, and the effectiveness of the proposed data split method was verified through a comparative study of conventional scheme and proposed methods.

• Tunnel and Underground Space
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• v.34 no.3
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• pp.231-247
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• 2024

In the field of high-level radioactive waste disposal targeting deep rock environments, hydraulic characteristic information serves as the most important key factor in selecting relevant disposal sites, detailed design of disposal facilities, derivation of optimal construction plans, and safety evaluation during operation. Since various rock types are mixed and distributed in a small area in Korea, it is important to conduct preliminary work to analyze the hydrogeological characteristics of rock aquifers for various rock types and compile the resulting data into a database. In this paper, we obtained hydraulic conductivity data, which is the most representative field hydraulic characteristic of a high-depth volcanic bedrock aquifer, and also analyzed and evaluated the field data. To acquire field data, we used a high-performance hydraulic testing system developed in-house and applied standardized test methods and investigation procedures. In the process of hydraulic characteristic data analysis, hydraulic conductivity values were obtained for each depth, and the pattern of groundwater flow through permeable rock joints located in the test section was also evaluated. It is expected that the series of data acquisition methods, procedures, and analysis results proposed in this report can be used to build a database of hydraulic characteristics data for high-depth rock aquifers in Korea. In addition, it is expected that it will play a role in improving technical know-how to be applied to research on hydraulic characteristic according to various bedrock types in the future.

• Tunnel and Underground Space
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• v.34 no.1
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• pp.1-14
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• 2024

An image-reconstruction technology, involving the deployment of an unmanned mobility equipped with high-speed LiDAR (Light Detection And Ranging) has been proposed to reconstruct the shape of abandoned mine. Unmanned mobility operation is remarkably useful in abandoned mines fraught with operational difficulties including, but not limited to, obstacles, sludge, underwater and narrow tunnel with the diameter of 1.5 m or more. For cases of real abandoned mines, quadruped robots, quadcopter drones and underwater drones are respectively deployed on land, air, and water-filled sites. In addition to the advantage of scanning the abandoned mines with 2D solid-state lidar sensors, rotation of radiation at an inclination angle offers an increased efficiency for simultaneous reconstruction of mineshaft shapes and detecting obstacles. Sensor and robot posture were used for computing rotation matrices that helped compute geographical coordinates of the solid-state lidar data. Next, the quadruped robot scanned the actual site to reconstruct tunnel shape. Lastly, the optimal elements necessary to increase utility in actual fields were found and proposed.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.89-103
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• 2024

In the disposal environment, gases can be generated at the interface between canister and buffer due to various factors such as anaerobic corrosion, radiolysis, and microbial degradation. If the gas generation rate exceeds the diffusion rate, the gas within the buffer may compress, resulting in physical damage to the buffer due to the increased pore pressure. In particular, the rapid movement of gases, known as gas breakthroughs, through the dilatancy pathway formed during this process may lead to releasing radionuclide. Therefore, understanding these gas generation and movement mechanism is essential for the safety assessment of the disposal systems. In this study, an experimental apparatus for investigating gas migration within buffer was constructed based on a literature review. Subsequently, a gas injection experiment was conducted on a compacted bentonite block made of Bentonile WRK (Clariant Ltd.) powder. The results clearly demonstrated a sharp increase in stress and pressure typically observed at the onset of gas breakthrough within the buffer. Additionally, the range of stresses induced by the swelling phenomenon of the buffer, was 4.7 to 9.1 MPa. The apparent gas entry pressure was determined to be approximately 7.8 MPa. The equipment established in this study is expected to be utilized for various experiments aimed at building a database on the initial properties of buffer and the conditions during gas injection, contributing to understanding the gas migration phenomena.

• Tunnel and Underground Space
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• v.34 no.2
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• pp.104-126
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• 2024

Buffer and backfill play an essential role in isolating high-level radioactive waste and retard the migration of leaked radionuclides in deep geological disposal system. A bentonite mixture, which exhibits a swelling property, is considered for buffer and backfill materials, and excessive groundwater inflow from surrounding rock mass may affect stability and efficiency of their role as an engineered barrier. Therefore, stringent quality control as well as in-situ installation management and inflow water constrol for buffer and backfill are required to ensure the safety of deep disposal facilities. In this study, we analyzed the design requirements of buffer and backfill by examining various laboratory tests and a field study of the Steel Tunnel Test at the Äspö Hard Rock Laboratory in Sweden. We introduced how to control the quality of buffer and backfill construction in-field, and also presented how to handle excessive groundwater inflow into disposal caverns, validating the groundwater retention capacity of bentonite pellets and the effectiveness of geotexile use.

• Tunnel and Underground Space
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• v.13 no.1
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• pp.52-63
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• 2003

Discontinuities such as faults, fractures and joints in rock mass play the dominant role in the mechanical and hydraulic properties of the rock mass. The key factors that influence on the flow of groundwater are hydraulic and geometric characteristics of discontinuities and their connectivity. In this study, a program that analyzes groundwater flow in the 3D discontinuity network was developed on the assumption that the discontinuity characteristics such as density, trace length, orientation and aperture have particular distribution functions. This program generates discontinuities in a three-dimensional space and analyzes their connectivity and groundwater flow. Due to the limited computing capacity In this study, REV was not exactly determined, but it was inferred to be greater than 25$\times$25$\times$25 ㎥. By calculating the extent of aperture that influences on the groundwater flow, it was found that the discontinuities with the aperture smaller than 30% of the mean aperture had little influence on the groundwater flow. In addition, there was little difference in the equivalent hydraulic conductivity for the the two cases when considering and not considering the boundary effect. It was because the groundwater flow was mostly influenced by the discontinuities with large aperture. Among the parameters considered in this study, the length, aperture, and orientation of discontinuities had the greatest influence on the equivalent hydraulic conductivity of rock mass in their order. In case of existence of a fault in rock mass, elements of the equivalent hydraulic conductivity tensor parallel to the fault fairly increased in their magnitude but those perpendicular to the fault were increased in a very small amount at the first stage and then converged.

• Economic and Environmental Geology
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• v.39 no.2 s.177
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• pp.163-171
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• 2006

This study is the case of groundwater development based on the geometrical fracture model of target area established only through geological fracture mapping technique. A fracture mapping of $9km^2$, eastern Munsan, has been conducted to determine geological and hydrological factors for new water well placement in the Gyeonggi gneiss complex. Geophysical exploration was not applicable because of small restricted area and dense underground utilities at the site. Form line mapping on the basis of foliation orientation and rock type revealed a synform of NS fold axis bearing to the south. An EW geological cross-section passed through the site area shows a F2 synform as a double-wall ice cream spoon shape. Three regional faults of $N20^{\circ}E,\;N30^{\circ}W$, and NS have been dragged into the site to help understand extensional fault paths. The $N20^{\circ}E$ fault with dextral sense is geometrically interpreted as a western fault of two flexural conjugate type-P shear faults in the F2 synformal fold. The NE cross-section reveals that a possible groundwater belt in the western limb of super-posed fold area is formed as a trigonal prism within 100 m depth of the intersectional space between the $N20^{\circ}E$ fault plane and the weakly sheared plane of transposed foliation. Another possible fault for water resource strikes $N40^{\circ}E$. Recommended sites for new water well placement are along the $N20^{\circ}E\;and\;N40^{\circ}E$ faults. As a result of fracture mapping, 145 ton/day of water can be produced at one well along the $N20^{\circ}E$ fault line. Exploration of groundwater in the area is succeeded only using with geological fracture mapping and interpretation of geological cross-section, without any geophysical survey. Intersection of fault generated with the F2 synformal fold and foliation supply space of groundwater reserver.

• Tunnel and Underground Space
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• v.31 no.5
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• pp.374-384
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• 2021

In this study, we propose a new approach for automatic fracture detection in CT scan images of rock specimens. This approach is built on top of two-stage object detection deep learning algorithm called Faster R-CNN with a major modification of using rotated bounding box. The use of rotated bounding box plays a key role in the future work to overcome several inherent difficulties of fracture segmentation relating to the heterogeneity of uninterested background (i.e., minerals) and the variation in size and shape of fracture. Comparing to the commonly used bounding box (i.e., axis-align bounding box), rotated bounding box shows a greater adaptability to fit with the elongated shape of fracture, such that minimizing the ratio of background within the bounding box. Besides, an additional benefit of rotated bounding box is that it can provide relative information on the orientation and length of fracture without the further segmentation and measurement step. To validate the applicability of the proposed approach, we train and test our approach with a number of CT image sets of fractured granite specimens with highly heterogeneous background and other rocks such as sandstone and shale. The result demonstrates that our approach can lead to the encouraging results on fracture detection with the mean average precision (mAP) up to 0.89 and also outperform the conventional approach in terms of background-to-object ratio within the bounding box.

• Economic and Environmental Geology
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• v.55 no.5
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• pp.551-561
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• 2022

Geophysical exploration methods are very useful for generating high-resolution images of underground structures, and such methods can be applied to investigation of buried cultural properties and for determining their exact locations. In this study, image feature extraction and image segmentation methods were applied to automatically distinguish the structures of buried relics from the high-resolution ground-penetrating radar (GPR) images obtained at the center of Silla Kingdom, Gyeongju, South Korea. The major purpose for image feature extraction analyses is identifying the circular features from building remains and the linear features from ancient roads and fences. Feature extraction is implemented by applying the Canny edge detection and Hough transform algorithms. We applied the Hough transforms to the edge image resulted from the Canny algorithm in order to determine the locations the target features. However, the Hough transform requires different parameter settings for each survey sector. As for image segmentation, we applied the connected element labeling algorithm and object-based image analysis using Orfeo Toolbox (OTB) in QGIS. The connected components labeled image shows the signals associated with the target buried relics are effectively connected and labeled. However, we often find multiple labels are assigned to a single structure on the given GPR data. Object-based image analysis was conducted by using a Large-Scale Mean-Shift (LSMS) image segmentation. In this analysis, a vector layer containing pixel values for each segmented polygon was estimated first and then used to build a train-validation dataset by assigning the polygons to one class associated with the buried relics and another class for the background field. With the Random Forest Classifier, we find that the polygons on the LSMS image segmentation layer can be successfully classified into the polygons of the buried relics and those of the background. Thus, we propose that these automatic classification methods applied to the GPR images of buried cultural heritage in this study can be useful to obtain consistent analyses results for planning excavation processes.