• Tunnel and Underground Space
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• v.31 no.6
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• pp.593-609
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• 2021

We proposed a numerical method for the thermo-mechanical behavior of rock fracture using a grain-based distinct element model (GBDEM) and simulated thermally induced fracture slip. The present study is the benchmark simulation performed as part of DECOVALEX-2023 Task G, which aims to develop a numerical method to estimate the coupled thermo-hydro-mechanical processes within the crystalline rock fracture network. We represented the rock sample as an assembly of Voronoi grains and calculated the interaction of the grains (blocks) and their interfaces (contacts) using a distinct element code, 3DEC. Based on an equivalent continuum approach, the micro-parameters of grains and contacts were determined to reproduce rock as an elastic material. Then, the behavior of the fracture embedded in the rock was characterized by the contacts with Coulomb shear strength and tensile strength. In the benchmark simulation, we quantitatively examined the effects of the boundary stress and thermal stress due to heat conduction on fracture behavior, focusing on the mechanism of thermally induced fracture slip. The simulation results showed that the developed numerical model reasonably reproduced the thermal expansion and thermal stress increment, the fracture stress and displacement and the effect of boundary condition. We expect the numerical model to be enhanced by continuing collaboration and interaction with other research teams of DECOVALEX-2023 Task G and validated in further study experiments.

• Tunnel and Underground Space
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• v.32 no.2
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• pp.160-172
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• 2022

The design regulations for simple explosive storage in Korea only stipulate standards for the materials and thickness of the wall of the structure because the amount of explosives that can be stored is small. There is concern about secondary damage during an internal explosion in a simple storage facility, and it is necessary to reexamine the current standards. The numerical analysis for the TNT 15 kg explosion inside the simple storage was carried out by setting the factors using the robust experimental design method. The displacement of the structure generated under the same time condition was analyzed, and the contribution was evaluated. The contribution of concrete thickness was the highest, and the contribution of concrete strength and rebar arrangement was lower than that of concrete thickness. The reinforcement diameter contributed extremely little to the displacement. The structural standards of the simple storage that are currently applied are insufficient on blast resistance, and it is necessary to present new design standards. Therefore, the design factor to be applied later analysis and actual experiments were taken into consideration. For the design variables, the thickness of the concrete was 15 cm considering the displacement, the concrete strength was selected as general concrete considering the inlet discharge pressure, the factor with the lowest average displacement was selected for the reinforcement arrangement and the diameter of the reinforcement, the factor with the smallest level was selected in consideration of economic feasibility because the difference in displacement was low.

• Tunnel and Underground Space
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• v.32 no.1
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• pp.78-92
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• 2022

In this study, we proposed a diagnostics and assessment model for mining sites that can evaluate the smart mining technology level in a systematic and structured way. For this, the maturity of the smart mining was defined, and detailed assessment items of the diagnostics and assessment model for smart mining were derived by considering the smart factory diagnostics and assessment model (KS X 9001-3) used in the manufacturing industry. While maintaining the existing system, the existing 46 detailed assessment items were modified to be suitable for mining. As a result, a total of 29 detailed assessment items were derived in the areas of promotion strategy, process, information system and automation, and performance. Based on this, a questionnaire was designed to diagnose the level of smart mining technology, and assessment was performed by applying it to domestic iron mines. The level of smart mining technology in the study area was found to be level 2, and it could be inferred that it was about 40% lower than the average smart level of the general manufacturing industry. In addition, by using the developed model, it was possible to recognize the weak points of the mine at each stage of the introduction, operation, and advancement of smart mining, and to suggest investment and improvement directions.

• Tunnel and Underground Space
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• v.32 no.2
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• pp.131-143
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• 2022

The lunar exploration autonomous vehicle operates based on the lunar topography information obtained from real-time image characterization. For highly accurate topography characterization, a large number of training images with various background conditions are required. Since the real lunar topography images are difficult to obtain, it should be helpful to be able to generate mimic lunar image data artificially on the basis of the planetary analogs site images and real lunar images available. In this study, we aim to artificially create lunar topography images by using the location information-based style transfer algorithm known as Wavelet Correct Transform (WCT2). We conducted comparative experiments using lunar analog site images and real lunar topography images taken during China's and America's lunar-exploring projects (i.e., Chang'e and Apollo) to assess the efficacy of our suggested approach. The results show that the proposed techniques can create realistic images, which preserve the topography information of the analog site image while still showing the same condition as an image taken on lunar surface. The proposed algorithm also outperforms a conventional algorithm, Deep Photo Style Transfer (DPST) in terms of temporal and visual aspects. For future work, we intend to use the generated styled image data in combination with real image data for training lunar topography objects to be applied for topographic detection and segmentation. It is expected that this approach can significantly improve the performance of detection and segmentation models on real lunar topography images.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.494-507
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• 2021

With the increasing use of TBM, research has recently been conducted in Korea to analyze TBM data with machine learning techniques to predict the ground in front of TBM, predict the exchange cycle of disk cutters, and predict the advance rate of TBM. In this study, classification prediction of rock characteristics of slurry shield TBM sites was made by combining traditional rock classification techniques and machine learning techniques widely used in various fields with machine data during TBM excavation. The items of rock characteristic classification criteria were set as RQD, uniaxial compression strength, and elastic wave speed, and the rock conditions for each item were classified into three classes: class 0 (good), 1 (normal), and 2 (poor), and machine learning was performed on six class algorithms. As a result, the ensemble model showed good performance, and the LigthtGBM model, which showed excellent results in learning speed as well as learning performance, was found to be optimal in the target site ground. Using the classification model for the three rock characteristics set in this study, it is believed that it will be possible to provide rock conditions for sections where ground information is not provided, which will help during excavation work.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.534-548
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• 2021

In this paper, the feasibility of generating solar power near an abandoned quarry is examined with the objectives of resolving the essential problems that quarries encounter, such as rockfalls and space usage issues. On an abandoned quarry site in Sadang, Seoul, Republic of Korea, two different PV installation methods were analyzed. The first is attaching PV directly on the quarry slope. Since there are no corresponding safety standards and precedents for installing solar panels directly on slopes, the power generation potential was calculated by using topographic data and reasonable assumptions. The surface area of cut slope section was extracted from the Digital Elevation Model(DEM) via ArcGIS and Python programming to calculate the tilt and power capacity of installable panels. The other approach is installing PV as a rockfall barrier, and the power generation potential was analyzed with the assumption that the panel is installed in the direction of facing solar irradiation. For the derivation of power generation, the renewable energy generation analysis program SAM(System Advisor Model) was used for both methods. According to the result, quarries that have terminated resource extraction and remain devastated have the potential to be transformed into renewable energy generation sites.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.623-646
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• 2021

As the demand for electric power increases with acceleration of electrification at home and abroad, the needs for coal-fired electrical power plant are accordingly increased. However, these coal-fired electrical power plants induce also many environmental problems such as increase of air pollutants, increase of possibility of land contamination by reclamation of coal ash, even though these power plants have a good economical efficiency. In case of a by-product of coal-fired electrical power plants, only 70% of them are recycled and the remaining 30% of by-product are fully buried in surrounding ground. Consequently, this study deals with coal ash backfilling mechanism in abandoned mine openings for the purposes of increasing the coal ash recycling rate as well as securing the mine area stability. In order to analyze the backfill and ground reinforcement by interaction between rock mass and backfills, the copying samples of discontinuous surface with different roughnesses were produced for bond strength tests and direct shear tests. And statistical analysis was also conducted to decide the characteristics of bond and shear behavior with joint roughness and their curing day. Numerical simulations were also analyzed for examining the effect of interface behavior on ground stability.

• Tunnel and Underground Space
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• v.31 no.6
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• pp.400-414
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• 2021

Under high-level radioactive waste repository conditions, bentonite as an engineered barrier material undergoes thermal, hydrological, mechanical, and chemical processes. We report the applications of X-ray Computed Tomography (CT) imaging technique on the characterization and analysis of bentonite over the past decade to provide a reference of the utilization of this technique and the recent research trends. This overview of the X-ray CT technique applications includes the characterization of the bentonite either in pellets or powder form. X-ray imaging has provided a means to extract grain information at the microscale and identify crack networks responsible for the pellets' heterogeneity. Regarding samples of pellets-powder mixtures under hydration, X-ray CT allowed the identification and monitoring of heterogeneous zones throughout the test. Some results showed how zones with pellets only swell faster compared to others composed of pellets and powder. Moreover, the behavior of fissures between grains and bentonite matrix was observed to change under drying and hydrating conditions, tending to close during the former and open during the latter. The development of specializing software has allowed obtaining strain fields from a sequence of images. In more recent works, X-ray CT technique has served to estimate the dry density, water content, and particle displacement at different testing times. Also, when temperature was added to the hydration process of a sample, CT technology offered a way to observe localized and global density changes over time.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.373-385
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• 2022

The drum cutter, which is used in the form of an attachment of a excavator, is very useful in that it can be used in connection with a excavator that can perform various tasks in the field. This study estimated the load and torque acting on the drum cutter attachment by measuring the hydraulic pressure and strain that appear during excavation on the exposed rock slope using the drum cutter installed in the excavator. Working conditions such as the operation angle between the boom and arm of the excavator were divided into eight working modes. And as a result of analyzing the variations in hydraulic pressure and action force according to the working mode, it was confirmed that the hydraulic pressure and flow rate can be driven without any problems within the range considered in the manufacturing specifications of the drum cutter. The average load and torque acting on the drum cutter were within the range of the manufacturing specifications, but the maximum load was up to four times the specification. Because sumping was not properly performed due to the high ground strength and the ground included discontinuous surfaces in some locations, no trend of load and torque was found depending on the angle between the boom and arm of the excavator. However, it is believed that this result can be used to determine the range of loads and torques that appear on the drum cutter when excavating a high-intensity rock.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.502-517
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• 2022

As the use of TBM increases, research has recently increased to to analyze TBM data with machine learning techniques to predict the exchange cycle of disc cutters, and predict the advance rate of TBM. In this study, a regression prediction of disc cutte wear of slurry shield TBM site was made by combining machine learning based on the machine data and the geotechnical data obtained during the excavation. The data were divided into 7:3 for training and testing the prediction of disc cutter wear, and the hyper-parameters are optimized by cross-validated grid-search over a parameter grid. As a result, gradient boosting based on the ensemble model showed good performance with a determination coefficient of 0.852 and a root-mean-square-error of 3.111 and especially excellent results in fit times along with learning performance. Based on the results, it is judged that the suitability of the prediction model using data including mechanical data and geotechnical information is high. In addition, research is needed to increase the diversity of ground conditions and the amount of disc cutter data.