• Tunnel and Underground Space
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• v.33 no.1
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• pp.57-69
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• 2023

In this study, we simulated induced seismicity in the Groningen natural gas reservoir using 2D hydro-mechanical coupled discrete element modelling (DEM). The code used is PFC2D (Particle Flow Code 2D), a commercial software developed by Itasca, and in order to apply to this study we further developed 1)initialization of inhomogeneous reservoir pressure distribution, 2)a non-linear pressure-time history boundary condition, 3)local stress field monitoring logic. We generated a 2D reservoir model with a size of 40 × 50 km² and a complex fault system, and simulated years of pressure depletion with a time range between 1960 and 2020. We simulated fault system failure induced by pressure depletion and reproduced the spatiotemporal distribution of induced seismicity and assessed its failure mechanism. Also, we estimated the ground subsidence distribution and confirmed its similarity to the field measurements in the Groningen region. Through this study, we confirm the feasibility of the presented 2D hydro-mechanical coupled DEM in simulating the deformation of a complex fault system by hydro-mechanical coupled processes.

• Tunnel and Underground Space
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• v.33 no.4
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• pp.209-227
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• 2023

The government continues to announce measures to revitalize smart construction technology based on BIM for productivity innovation in the construction industry. In the design phase, the goal is design automation and optimization by converging BIM Data and other advanced technologies. Accordingly, in the basic design of the Namhae Seomyeon-Yeosu Sindeok National Road Construction Project, a domestic undersea tunnel project, BIM-based design was carried out by developing tunnel design automation technology using 3D spatial information according to the tunnel design process. In order to derive the optimal alignment, more than 10,000 alignment cases were generated in 36hr using the generative design technique and a quantitative evaluation of the objective functions defined by the designer was performed. AI-based ground classification and 3D Geo Model were established to evaluate the economic feasibility and stability of the optimal alignment. AI-based ground classification has improved its precision by performing about 30 types of ground classification per borehole, and in the case of the 3D Geo Model, its utilization can be expected in that it can accumulate ground data added during construction. In the case of 3D blasting design, the optimal charge weight was derived in 5 minutes by reviewing all security objects on the project range on Dynamo, and the design result was visualized in 3D space for intuitive and convenient construction management so that it could be used directly during construction.

• Journal of the Korean Geotechnical Society
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• v.39 no.3
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• pp.29-40
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• 2023

In this study, we investigated the reinforcing effects of waveform micropiles in a stratigraphic setting comprising buried soil, weathered soil, and weathered rock. We conducted a series of field load tests and determined that waveform micropiles exhibited sufficient bearing capacity through frictional resistance in the soil layer and demonstrated favorable constructability in conditions with deep bedrock layers. Moreover, the vertical stiffness of waveform micropiles was approximately 2.2 times higher than that of conventional micropiles when subjected to the same design load. Pile group load tests comprising conventional and waveform micropiles showed that micropiles with higher stiffness carried a greater proportion of the load. Although there was no significant difference in the bearing capacity between conventional and waveform micropiles under the same design load, waveform micropiles with higher stiffness showed a load-carrying capacity 1.7 to 3.2 times greater than that of conventional micropiles. These findings suggest that waveform micropiles can be effectively used for foundation reinforcement and reduce the risk of foundation failure when increased loads due to modifications such as expansion remodeling are expected.

• Journal of the Korean Geotechnical Society
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• v.26 no.7
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• pp.17-24
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• 2010

Load Resistance Factor Design method is used increasingly in geotechnical design world widely and resistance factors for drilled shafts are suggested by AASHTO. However, these resistance factors are determined for intact rock conditions; by comparison, most of bedrocks in Korea have weathered condition, so that applying the AASHTO resistance factors is not reasonable. Thus, this study suggests the proper resistance factors for design of drilled shaft in Korea. The 22 cases of pile load test data from 8 sites were chosen and reliability-based approach is used to analyze the data. Reliability analysis was performed by First Order Second Moment Method (FOSM) applying 4 bearing capacity equations. As a result, when the Factor of Safety (FOS) was selected as 3.0, the target reliability indexes (${\beta}_c$) were evaluated as 2.01~2.30. Resistance factors and load factors are determined from optimization based on above results. The resistance factors ranged between 0.48 and 0.56 and load factors for dead load and live load are evaluated as approximately 1.25 and 1.75 respectively. However, when the target reliabilities are considered as 3.0, the resistance factors are evaluated as approximately 50% of the results when the target reliability index was 2.0.

• Journal of the Korean Geotechnical Society
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• v.23 no.3
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• pp.61-75
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• 2007

Deep foundations have been popularly installed in hard stratum such as gravels or rocks in Korea. However, it is necessary to consider sand or sandy gravel layers that locate at the mid-depths as the bearing stratum of piles in the thick Nakdong River deltaic deposits, as done in the Chaophraya (Bangkok) and Mississippi River deltas. This study was focused on the finding of suitable methods for estimating bearing capacity when driving prestressed high-strength concrete (PHC) piles to a required depth in the deltaic area. Ground investigation was performed at five locations of two sites in the deltaic area. Bearing capacity of the driven piles has been computed using a number of proposed methods such as CPT-based and other analytical methods, based on the ground investigation and comparison one another other. Five PDA (pile driving analyzer) tests were systematically carried out at the whole depths of embedded piles, which is a well-blown useful technique for the purposes. As the results, the bearing capacities calculated by various methods were compared with the PDA and static load testing results. It was found that the shaft resistance is significantly governed by set-up effects and then the long-term value agrees well with that of the $\beta$ method. Also, the design methods for toe resistance were determined based on the SLT result, rather than PDA results that led to underestimation. Moreover, using the CPT results, appropriate methods were proposed for calculating the bearing capacity of the piles in the area.

• Tunnel and Underground Space
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• v.33 no.3
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• pp.109-125
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• 2023

Disposal repository for high-level radioactive waste secures its safety by means of engineered and natural barriers. The performance of these barriers should be tested and verified through various aspects in terms of short and/or long-term. KAERI has been conducting various in-situ demonstrations in KURT (KAERI Underground Research Tunnel). After completing previous experiment, a conceptual design of an improved in-situ experiment, i.e. K-COIN (KURT experiment of THMC COupled and INteraction), was established and detailed planning for the experiment is underway. Preliminary characterizations were conducted in KURT for siting a K-COIN test site. 15 boreholes with a depth of about 20 m were drilled in three research galleries in KURT and intact rock specimens were prepared for laboratory tests. Using the specimens, physical measurements, uniaxial compression, indirect tension, and triaxial compression tests were conducted. As a result, specific gravity, porosity, elastic wave velocities, uniaxial compressive strength, Young's modulus, Poisson's ratio, Brazilian tensile strength, cohesion, and internal friction angle were estimated. Statistical analyses revealed that there did not exist meaningful differences in intact rock properties according to the drilled sites and the depth. Judging from the uniaxial compressive strength, which is one of the most important properties, all the specimens were classified as very strong rock so that mechanical safety was secured in all the regions.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1C
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• pp.65-76
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• 2010

Recent earthquake events revealed that severe seismic damages were concentrated mostly at sites composed of soil sediments rather than firm rock. This indicates that the site effects inducing the amplification of earthquake ground motion are associated mainly with the spatial distribution and dynamic properties of the soils overlying bedrock. In this study, an integrated GIS-based information system for geotechnical data was constructed to establish a regional counterplan against ground motions at a representative metropolitan area, Seoul, in Korea. To implement the GIS-based geotechnical information system for the Seoul area, existing geotechnical investigation data were collected in and around the study area and additionally a walkover site survey was carried out to acquire surface geo-knowledge data. For practical application of the geotechnical information system used to estimate the site effects at the area of interest, seismic zoning maps of geotechnical earthquake engineering parameters, such as the depth to bedrock and the site period, were created and presented as regional synthetic strategy for earthquake-induced hazards prediction. In addition, seismic zonation of site classification was also performed to determine the site amplification coefficients for seismic design at any site and administrative sub-unit in the Seoul area. Based on the case study on seismic zonations for Seoul, it was verified that the GIS-based geotechnical information system was very useful for the regional prediction of seismic hazards and also the decision support for seismic hazard mitigation particularly at the metropolitan area.

• 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.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.

• 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.