• Title/Summary/Keyword: 지하

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Standard Procedures and Field Application Case of Constant Pressure Injection Test for Evaluating Hydrogeological Characteristics in Deep Fractured Rock Aquifer (고심도 균열암반대수층 수리지질특성 평가를 위한 정압주입시험 조사절차 및 현장적용사례 연구)

  • Hangbok Lee;Chan Park;Eui-Seob Park;Yong-Bok Jung;Dae-Sung Cheon;SeongHo Bae;Hyung-Mok Kim;Ki Seog Kim
    • Tunnel and Underground Space
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    • v.33 no.5
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    • pp.348-372
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    • 2023
  • In relation to the high-level radioactive waste disposal project in deep fractured rock aquifer environments, it is essential to evaluate hydrogeological characteristics for evaluating the suitability of the site and operational stability. Such subsurface hydrogeological data is obtained through in-situ tests using boreholes excavated at the target site. The accuracy and reliability of the investigation results are directly related to the selection of appropriate test methods, the performance of the investigation system, standardization of the investigation procedure. In this report, we introduce the detailed procedures for the representative test method, the constant pressure injection test (CPIT), which is used to determine the key hydrogeological parameters of the subsurface fractured rock aquifer, namely hydraulic conductivity and storativity. This report further refines the standard test method suggested by the KSRM in 2022 and includes practical field application case conducted in volcanic rock aquifers where this investigation procedure has been applied.

Assessment of potential carbon storage in North Korea based on forest restoration strategies (북한 산림복원 전략에 따른 탄소저장량 잠재성 평가)

  • Wonhee Cho;Inyoo Kim;Dongwook Ko
    • Korean Journal of Environmental Biology
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    • v.41 no.3
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    • pp.204-214
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    • 2023
  • This study aimed to conduct a comprehensive assessment of the potential impact of deforestation and forest restoration on carbon storage in North Korea until 2050, employing rigorous analyses of trends of land use change in the past periods and projecting future land use change scenarios. We utilized the CA-Markov model, which can reflect spatial trends in land use changes, and verified the impact of forest restoration strategies on carbon storage by creating land use change scenarios (reforestation and non-reforestation). We employed two distinct periods of land use maps (2000 to 2010 and 2010 to 2020). To verify the overall terrestrial carbon storage in North Korea, our evaluation included estimations of carbon storage for various elements such as above-ground, below-ground, soil, and debris (including litters) for settlement, forest, cultivated, grass, and bare areas. Our results demonstrated that effective forest restoration strategies in North Korea have the potential to increase carbon storage by 4.4% by the year 2050, relative to the carbon storage observed in 2020. In contrast, if deforestation continues without forest restoration efforts, we predict a concerning decrease in carbon storage by 11.5% by the year 2050, compared to the levels in 2020. Our findings underscore the significance of prioritizing and continuing forest restoration efforts to effectively increase carbon storage in North Korea. Furthermore, the implications presented in this study are expected to be used in the formulation and implementation of long-term forest restoration strategies in North Korea, while fostering international cooperation towards this common environmental goal.

Numerical Analysis of Fault Stability in Janggi Basin for Geological CO2 Storage (CO2 지중저장에 따른 장기분지 내 단층안정성 기초해석)

  • Jung-Wook Park;Hanna Kim;Hangbok Lee;Chan-Hee Park;Young Jae Shinn
    • Tunnel and Underground Space
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    • v.33 no.5
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    • pp.399-413
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    • 2023
  • The present study conducted a numerical modeling of CO2 injection at the Janggi Basin using the TOUGH-FLAC simulator, and examined the hydro-mechanical stability of the aquifer and the fault. Based on the site investigations and a 3D geological model of the target area, we simulated the injection of 32,850 tons of CO2 over a 3-year period. The analysis of CO2 plume with different values of the aquifer permeability revealed that assuming a permeability of 10-14 m2 the CO2 plume exhibited a radial flow and reached the fault after 2 years and 9 months. Conversely, a higher permeability of 10-13 m2 resulted in predominant westward flow along the reservoir, with negligible impact on the fault. The pressure changes around the injection well remained below 0.6 MPa over the period, and the influence on the hydro-mechanical stability of the reservoir and fault was found to be insignificant.

Application of Eddy Current Sensor for Measurement of TBM Disc Cutter Wear (TBM 디스크커터의 마모량 측정을 위한 와전류센서의 적용 연구)

  • Min-Sung Park;Min-Seok Ju;Jung-Joo Kim;Hoyoung Jeong
    • Tunnel and Underground Space
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    • v.33 no.6
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    • pp.534-546
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    • 2023
  • If the disc cutter is excessively worn or damaged, it becomes incapable of rotating and efficiently cutting rockmass. Therefore, it is important to appropriately manage the replacement cycle of the disc cutter based on its degree of wear. In general, the replacement cycle is determined based on the results of manual inspection. However, the manual measurements has issues related to worker safety and may lead to inaccurate measurement results. For these reasons, some foreign countries are developing the real-time measurement system of disc cutter wear by using different sensors. The ultrasonic sensors, eddy current sensors, magnetic sensors, and others are utilized for measuring the wear amount of disc cutters. In this study, the applicability of eddy current sensors for real-time measurement of wear amount in TBM disc cutters was evaluated. The distance measurement accuracy of the eddy current sensor was assessed through laboratory tests. In particular, the accuracy of eddy-current sensor was evaluated in various environmental conditions within the cutterhead chamber. In addition, the measurement accuracy of the eddy current sensor was validated using a 17-inch disc cutter.

Analysis on Design Change for Backfilling Solution of the Disposal Tunnel in the Deep Geological Repository for High-Level Radioactive Waste in Finland (핀란드 고준위방사성폐기물 심층처분시설 처분터널 뒤채움 설계 변경을 위한 연구사례 분석)

  • Heekwon Ku;Sukhoon Kim;Jeong-Hwan Lee
    • Tunnel and Underground Space
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    • v.33 no.6
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    • pp.435-444
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    • 2023
  • In the licensing application for the deep geological disposal system of high-level radioactive waste in Finland, the disposal tunnel backfilling has been changed from the block/pellet (for the construction) to the granular type (for the operation). Accordingly, for establishing the design concept for backfilling, it is necessary to examine applicability to the domestic facility through analyzing problems of the existing method and improvements in the alternative design. In this paper, we first reviewed the principal studies conducted for changing the backfill method in the licensing process of the Finnish facility, and identified the expected problems in applying the block/pellet backfill method. In addition, we derived the evaluation factors to be considered in terms of technical and operational aspects for the backfilling solution, and then conducted a comparative analysis for two types of backfill methods. This analysis confirmed the overall superiority of the design change. It is expected that these results could be utilized as the technical basis for deriving the optimum design plan in development process of the Korean-specific deep disposal facility. However, applicability should be reviewed in advance based on the latest technical data for the detailed evaluation factors that must be considered for selecting the backfilling method.

A Study on the Prediction of Uniaxial Compressive Strength Classification Using Slurry TBM Data and Random Forest (이수식 TBM 데이터와 랜덤포레스트를 이용한 일축압축강도 분류 예측에 관한 연구)

  • Tae-Ho Kang;Soon-Wook Choi;Chulho Lee;Soo-Ho Chang
    • Tunnel and Underground Space
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    • v.33 no.6
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    • pp.547-560
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    • 2023
  • Recently, research on predicting ground classification using machine learning techniques, TBM excavation data, and ground data is increasing. In this study, a multi-classification prediction study for uniaxial compressive strength (UCS) was conducted by applying random forest model based on a decision tree among machine learning techniques widely used in various fields to machine data and ground data acquired at three slurry shield TBM sites. For the classification prediction, the training and test data were divided into 7:3, and a grid search including 5-fold cross-validation was used to select the optimal parameter. As a result of classification learning for UCS using a random forest, the accuracy of the multi-classification prediction model was found to be high at both 0.983 and 0.982 in the training set and the test set, respectively. However, due to the imbalance in data distribution between classes, the recall was evaluated low in class 4. It is judged that additional research is needed to increase the amount of measured data of UCS acquired in various sites.

Study of the Static Shear Behaviors of Artificial Jointed Rock Specimens Utilizing a Compact CNS Shear Box (Compact CNS shear box를 활용한 모의 절리암석시료의 정적 전단 거동에 관한 연구)

  • Hanlim Kim;Gyeongjo Min;Gyeonggyu Kim;Youngjun Kim;Kyungjae Yun;Jusuk Yang;Sangho Bae;Sangho Cho
    • Tunnel and Underground Space
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    • v.33 no.6
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    • pp.574-593
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    • 2023
  • In this study, the effectiveness and applicability of a newly designed Compact CNS shear box for conducting direct shear tests on jointed rock specimens were investigated. CNS joint shear tests were conducted on jointed rocks with Artificially generated roughness while varying the fracture surface roughness coefficient and initial normal stress conditions. In addition, displacement data were validated by Digital image correlation analysis, fracture patterns were observed, and comparative analysis was conducted with previously studied shear behavior prediction models. Furthermore, the accuracy of the displacement data was confirmed through DIC analysis, the fracture patterns were observed, and the shear properties obtained from the tests were compared with existing models that predict shear behavior. The findings exhibited a strong correlation with specific established empirical models for predicting shear behavior. Furthermore, the potential linkage between the characteristics of shear behavior and fracture patterns was deliberated. In conclusion, the CNS shear box was shown to be applicable and effective in providing data on the shear characteristics of the joint.

Application of Multiple Linear Regression Analysis and Tree-Based Machine Learning Techniques for Cutter Life Index(CLI) Prediction (커터수명지수 예측을 위한 다중선형회귀분석과 트리 기반 머신러닝 기법 적용)

  • Ju-Pyo Hong;Tae Young Ko
    • 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.

Deep Learning Approach for Automatic Discontinuity Mapping on 3D Model of Tunnel Face (터널 막장 3차원 지형모델 상에서의 불연속면 자동 매핑을 위한 딥러닝 기법 적용 방안)

  • Chuyen Pham;Hyu-Soung Shin
    • 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.

Correlation Analysis of Cutter Acting Force and Temperature During the Linear Cutting Test Accompanied by Infrared Thermography (선형절삭시험과 적외선 열화상 측정을 통한 픽커터 작용력과 발생 온도의 상관관계 분석)

  • Soo-Ho Chang;Tae-Ho Kang;Chulho Lee;Hoyoung Jeong;Soon-Wook Choi
    • Tunnel and Underground Space
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    • v.33 no.6
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    • pp.519-533
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    • 2023
  • In this study, the linear cutting tests of pick cutters were carried out on a granitic rock with the average compressive strength over 100 MPa. From the tests, the correlation between the cutter acting force and the temperature measured by infrared thermal imaging camera during rock cutting was analyzed. In every experimental condition, the maximum temperature was measured at the rock surface where the chipping occurred, and the temperature generated in the rock was closely correlated with the cutter acting force. On the other hand, the temperature of a pick cutter increased up to only 36℃ above the ambient temperature, and the correlation with the cutter force was not obvious. This can be attributed to the short cutting distance under laboratory conditions and the high thermal conductivity of the tungsten carbide inserts. However, the relatively high temperature of the tungsten carbide inserts was found to be maintained. Therefore, it is recommended that a reinforcement between the insert and the head of a pick cutter or the quality improvement of silvering brazing in the production of a cutter is necessary to maintain the high cutting performance of a pick cutter.