• Journal of the Korean Geosynthetics Society
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• v.20 no.1
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• pp.9-19
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• 2021

This paper deals with the reinforcement performance of acrylate for reinforcing the settled railway roadbed. Concrete tracks have the advantage of reducing track maintenance costs and high resistance to track destruction. However, roadbed settlement is occurring in some construction sections, and the safety of railways is a serious concern because of difficulties in maintenance. Currently, maintenance through the track restoration method is being carried out in Korea as a way of roadbed settlement in concrete tracks, but continuous re-settlement can occur because the roadbed itself cannot be reinforced, and there are very few cases of reinforcement of railway roadbeds and field application. So the development of reinforcement materials and construction methods to reinforce railway roadbeds is required. Therefore, in this paper, acrylate was selected as reinforcement material for railway roadbed, and the reinforcement performance of acrylate was analyzed through experiment. As a result, it was analyzed that the acrylate can penetrate into a permeability coefficient of 1×10^-4 cm/sec, and secure uniaxial compression strength of 0.5 MPa/30min or more and stiffness of 80 MPa or more.

• 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.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.539-544
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• 2023

The subject of this study is the Maae Buddha statue in granodiorite of the Mesozoic Cretaceous period, which is concerned about stability as a standing stone cultural property located in ◯◯-dong, Gyeongsangbuk-do. For stability analysis, three-dimensional face mapping, geological properties of joints, three-dimensional scanning, ultrasonic velocity, polarization microscopy, electron microscopy analysis and XRD analysis were performed. In addition, the safety factor of the Maaebul was calculated by analyzing the damage status investigation, stereographic projection analysis, rock classification, and limit equilibrium analysis. The types and scales of damage and possible collapse by section depend on the degree of weathering of the rock and the orientation and characteristics of the joints, but wedge-failure and toppling-failure are expected to be small-scale. The safety factor of Maaebul in dry and wet conditions is less than 1.2, so stability is concerned. The types of damage were mainly observed, such as exfoliation, cracking, granular decomposition, and vegetation growth. The Maaebul rock is granodiorite, and the surface discoloration materials are K, Fe, and Mg. The 4 sets of joints are developed, J1 is tensile joint and the others are shear joint. The uniaxial compressive strength estimated by ultrasonic exploration is 514kgf/cm2, which corresponds to most soft rocks and some weathered rocks. Rock classification(RMR) is estimated to be grade 5, very poor rock mass. These technique along with the existing methods of safety diagnosis of cultural properties are expected to be a reasonable tool for objective interpretation and stability review of stone cultural properties.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.594-609
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• 2023

TBM (Tunnel Boring Machine) method is gaining popularity in urban and underwater tunneling projects due to its ability to ensure excavation face stability and minimize environmental impact. Among the prominent models for predicting disc cutter life, the NTNU model uses the Cutter Life Index(CLI) as a key parameter, but the complexity of testing procedures and rarity of equipment make measurement challenging. In this study, CLI was predicted using multiple linear regression analysis and tree-based machine learning techniques, utilizing rock properties. Through literature review, a database including rock uniaxial compressive strength, Brazilian tensile strength, equivalent quartz content, and Cerchar abrasivity index was built, and derived variables were added. The multiple linear regression analysis selected input variables based on statistical significance and multicollinearity, while the machine learning prediction model chose variables based on their importance. Dividing the data into 80% for training and 20% for testing, a comparative analysis of the predictive performance was conducted, and XGBoost was identified as the optimal model. The validity of the multiple linear regression and XGBoost models derived in this study was confirmed by comparing their predictive performance with prior research.

• Tunnel and Underground Space
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• v.34 no.4
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• pp.330-354
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• 2024

In site characterization of high-level radioactive waste, discontinuity(joint) distribution and rock mass classification, which are key evaluation parameters in the rock engineering field, were evaluated using deep boreholes in the Wonju granite and Chuncheon granite, which belong to Mesozoic Jurassic era. To evaluate joint distribution characteristics, fracture zones and joint surfaces extracted from ATV data were used, and major joint sets were evaluated along with joint frequency according to depth, dip direction, and dip. Both the Wonju and Chuncheon granites that were studied showed a tendency for the frequency of joints to increase linearly with depth, and joints with high angles were relatively widely distributed. In addition, relatively large amounts of weathering tended to occur even in deep depth due to groundwater inflow through high-angle joints. RQD values remained consistently low even at considerable depth. Meanwhile, joint groups with low angles showed different joint characteristics from joint sets with high angles. Rock mass classification was performed based on RMR system, and along with rock mass classification for 50 m intervals where uniaxial compressive strength was performed, continuous rock mass classification according to depth was performed using velocity log data and geostatistical techniques. The Wonju granite exhibited a superior rock mass class compared to the Chuncheon granite. In the 50 m interval and continuous rock mass classification, the shallow part of the Wonju granite showed a higher class than the deep part, and the deep part of the Chuncheon granite showed a higher class than the shallow part.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.17 no.2
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• pp.183-202
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• 2019

For design and performance assessment of a high-level radioactive waste (HLW) disposal system, it is necessary to understand the characteristics of coupled thermo-hydro-mechanical (THM) behavior. However, in previous studies for the Korean Reference HLW Disposal System (KRS), thermal analysis was performed to determine the spacing of disposal tunnels and interval of disposition holes without consideration of the coupled THM behavior. Therefore, in this study, TOUGH2-MP/FLAC3D is used to conduct THM modeling for performance assessment of the Korean Reference HLW Disposal System (KRS). The peak temperature remains below the temperature limit of $100^{\circ}C$ for the whole period. A rapid rise of temperature caused by decay heat occurs in the early years, and then temperature begins to decrease as decay heat from the waste decreases. The peak temperature at the bentonite buffer is around $96.2^{\circ}C$ after about 3 years, and peak temperature at the rockmass is $68.2^{\circ}C$ after about 17 years. Saturation of the bentonite block near the canister decreases in the early stage, because water evaporation occurs owing to temperature increase. Then, saturation of the bentonite buffer and backfill increases because of water intake from the rockmass, and bentonite buffer and backfill are fully saturated after about 266 years. The stress is calculated to investigate the effect of thermal stress and swelling pressure on the mechanical behavior of the rockmass. The calculated stress is compared to a spalling criterion and the Mohr-Coulumb criterion for investigation of potential failure. The stress at the rockmass remains below the spalling strength and Mohr-Coulumb criterion for the whole period. The methodology of using the TOUGH2-MP/FLAC3D simulator can be applied to predict the long-term behavior of the KRS under various conditions; these methods will be useful for the design and performance assessment of alternative concepts such as multi-layer and multi-canister concepts for geological spent fuel repositories.

• Proceedings of the Korean Society for Rock Mechanics Conference
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• 2000.09a
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• pp.183-193
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• 2000

A series of studies such as geological logging data analysis, detailed geological survey, rock mass evaluation, in-situ and laboratory tests, rock strength and mechanical properties of the rock were concerned. The stability of the slope were carried out inorder to design the pit slope and individual benches using the stereographic projection analysis and numerical methods in Roto Pit of Pasir coal fetid. The bedding plane was one of the major discontinuities in the Roto Pit and the dip of which is about $60^{\circ}$in the northern part and $83^{\circ}$in the southern part. The dip of bedding becomes steeper from north to south. The plane and toppling failures are presented in many slopes. In laboratory test the average uniaxial compressive strength of mudstone was 9 MPa and that of weak sandstone was 10 MPa. In-situ test showed that the rocks of Roto north mining area are mostly weak enough to be classified in grade from R2(weak) to R3(medium strong weak) and the coal is classified in grades from R1(Very weak) to R2(Weak). The detailed stability analysis were carried out on 4 areas of Roto north(east, west, south and north), and 2 areas of Roto south(east and west). In this paper, the minimum factor of safety was set to 1.2 which is a general criterion for open pit mines. Using the stereographic projection analysis and the limit equilibrium method, slope angles were calculated as 30~$36^{\circ}$for a factor of safety greater than 1.2. Then these results were re-evaluated by numerical analysis using FLAC. The final slope angles were determined by rational described abode. A final slope of 34 degrees can guarantee the stability for the eastern part of the Roto north area, 33 degrees for the western part, 35 degrees for the northern part and 35 degrees for the southern part. For the Roto south area, 36 degrees was suggested for both sides of the pit. Once the pit slope is designed based on the stability analysis and the safety measures. the stability of 니ope should be checked periodically during the mining operations. Because the slope face will be exposed long time to the rain fall, a study such aspreventive measures against weathering and erosion is highly recommended to be implemented.

• Tunnel and Underground Space
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• v.10 no.3
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• pp.430-440
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• 2000

A series of studies such as geological logging data analysis, detailed geological survey, rock mass evaluation, in-situ and laboratory tests, rock strength and mechanical properties of the rock were concerned. The stability of the slope were carried out inorder to design the pit slope and individual benches using the stereographic projection analysis and numerical methods in Roto Pit of Pasir coal field. The bedding plane was one of the major discontinuities in the Roto Pit and the dip of which is about 60$^{\circ}$ in the northern part and 83$^{\circ}$ in the southern part. The dip of bedding becomes steeper from north to south. The plane and toppling failures are presented in many slopes. In laboratory test the average uniaxial compressive strength of mudstone was 9MPa and that of weak sandstone was 10MPa. In-situ test showed that the rocks of Roto north mining area are mostly weak enough to be classified in grade from R2(weak) to R3(medium strong weak) and the coal is classified in grades from R1(Very weak) to R2(Weak). The detailed stability analysis were carried out on 4 areas of Roto north (east, west, south and north), and 2 areas of Roto south(east and west). In this paper, the minimum factor of safety was set to 1.2 which is a general criterion for open pit mines. Using the stereographic projection analysis and the limit equilibrium method, slope angles were calculated as 30∼36$^{\circ}$ for a factor of safety greater than 1.2. Then these results were re-evaluated by numerical analysis using FLAC. The final slope angles were determined by rational described above. A final slope of 34 degrees can guarantee the stability for the eastern part of the Roto north area, 33 degrees for the western part, 35 degrees for the northern part and 35 degrees for the southern part. For the Roto south area, 36 degrees was suggested for both sides of the pit. Once the pit slope is designed based on the stability analysis and the safety measures, the stability of slope should be checked periodically during the mining operations. Because the slope face will be exposed long time to the rain fall, a study such aspreventive measures against weathering and erosion is highly recommended to be implemented.

• Journal of the Korean Geosynthetics Society
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• v.10 no.2
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• pp.73-79
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• 2011

Based on the results of Part 1 of our two-parts paper, the possibility on field applicability of CMDS(Coal Mine Drainage Sludge) mixed with bentonite and cement as a liner in landfill sites was investigated. The optimum moisture content that met the landfill liner condition was obtained when the ratio of CMDS: bentonite: cement was 1: 0.5: 0.3 in a lab-scale. The relative compaction was measured in 90.1%, which results for construction field have been generally acceptable. In this study, a large-scale Lysimeter($1.0m{\times}1.5m{\times}2.0m$) was used to simulate the effects of the layer on the freeze/thaw by -20 average temperature. The mixture after freezing/thawing showed compressive strength more than $5kg/cm^2$, which was satisfied with EPA standards. Initial permeability of CMDS was $7.10{\times}10^{-7}cm/s$ and permeability its mixture after freezing/thawing was increased to $9.80{\times}10^{-7}cm/s$. The change of temperature in the layers rises and falls with linear and temperature gradient keep maintain the present state. Moisture contents in the layers have not been radically changed. Through the leaching test determined by KSLT method, it was found that heavy metals excluding Zn and Ni were not leached out or leached out less than the standards during 7 cycles of freezing/thawing process. Since it shows the increased permeability about 1.5 times and slight change in moisture content, but it was satisfied with EPA standar through 7 cycles of freezing/thawing process, this mixture can be applied as a liner in landfill final cover system.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.469-484
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• 2021

Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, V_p, V_s, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.