Japan-Korea Joint Symposium on Rock Engineering has been held since 1996. The main purpose of the joint symposium is to exchange knowledge and experiences in rock engineering between two countries and to promote opportunities of exchange for engineers. The joint symposium covers all the aspects of rock mechanics from theoretical to engineering practice, with emphasis on applications of environment-friendly rock engineering technologies in development and storage of energy and mineral resources including hydropower, geothermal energy, radioactive waste disposal, carbon sequestration, and mine rehabilitation. We would like to welcome you to Japan in January, 2024 to excavate and share related issues and to cooperate and offer better environmental solutions in these fields.

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The CCS (Carbon Capture and Storage) technique is aimed at reducing carbon dioxide emissions and ensuring aquifer safety. Utilizing the Enzyme-Induced Calcite Precipitation (EICP) method, we decreased the permeability of reservoir rocks which helps in preventing carbon dioxide leakage. The study applied the three-dimensional discrete element method (3D-DEM) to simulate permeability in porous rocks creating models with varying grain sizes and porosity. The precipitation of micro-minerals in lower porosity rock layers significantly reduces permeability.

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A numerical model was developed to predict permeability change due to the interaction between fractured granite rock and NaCl solution. The NaCl solution was employed to replicate the composition of seawater, where Na and Cl are the major elemental components. During the flow-through experiment conducted at a temperature of 20°C (E-28), secondary minerals were precipitated on the fracture surfaces. As a result, there was a significant decrease in fracture permeability. This significant decrease in permeability cannot be replicated by our proposed model because only one secondary mineral was formed during the simulation. In this simulation, three minerals, such as calcite, dawsonite, and halite, are expected to precipitate. Although additional element concentration has been provided by pressure dissolution and free-face dissolution, the oversaturated condition of the calcite and halite mineral has not yet been reached. However, the oversaturated condition of calcite and/or halite might be reached at specific area, for which the underlying mechanism is still unknown.

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This study aims to practically evaluate the radial anisotropy of rock material through laboratory testing of rock discs. The anisotropy was assessed by measuring the diameter, P-wave velocity, and Brazilian elastic modulus in the radial direction at different angular distances using three representative rock types, granite, marble, and sandstone. The anisotropy of all the properties measured in each rock type was distinctly evident. The results showed that sandstone exhibited a larger diametrical anisotropy compared to the other rock types. The P-wave velocity and Brazilian Elastic Modulus (E_B) were the highest in granite.

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For using helical segments in shield TBM, the thrust jacks compress on the inclined side wall of the segments. In the inclined condition, eccentric force and bending moment occur in the thrust jack module. Those induce a buckling deformation of the hydraulic cylinder parts, which causes oil leakage, plastic deformation, and fatigue damages. The paper examined the buckling reliability of thrust jack contacting on the inclined surface. A static and fatigue analysis was conducted for analyzing the stress concentration of the module. Compression testing system are installed, and then the compression test was conducted for a TBM thrust jack. The testing data is obtained and analyzed for verification of the buckling stability.

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The research studies a consecutive excavation method to enhance the shield TBM advance rate by using helical segments. A new redistribution of thrust force should be designed for compensating of resting jacks on assembling segment. An optimization process is developed to redistribute thrust forces of the jacks, then sine and linear functions are adopted for optimum solutions. To examine the accuracy of these, a scaled model was manufactured. The force redistribution techniques are demonstrated in the scaled model tests, and consecutive advance processes with controlling TBM jacks are partially validated.

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Uniaxial compressive strength (UCS) is a frequently used parameter in predicting TBM excavation performance and disc cutter wear. However, due to financial and time constraints in tunnel projects, typically only UCS information obtained from limited geotechnical investigations is available. In this study, we predicted UCS using operational data collected during TBM excavation and machine learning algorithms based on supervised learning. The models, including KNN, RF, XGBoost, LightGBM, and CatBoost, were evaluated, with CatBoost demonstrating superior performance in terms of the lowest average Root Mean Square Error (RMSE) and the highest average R-squared (R²) for the test dataset. SHAP analysis identified the key variables influencing UCS prediction, with FPI, feed pressure, and cutterhead rotation speed ranking as the most significant factors.

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In this research, we first extracted keywords from geological and topographic survey reports by using a co-occurrence network, which is a text mining technique. We then included the keywords in a prompt for generative AI and asked what construction managers should be aware of during mountain tunnel construction, and used the answers to deepen our consideration. The results of this research show the level of technical advice for construction when keywords extracted by text mining are included in a prompt for generative AI to prevent the leakage of information and also show the usefulness of this method. Notes on using this method in the future are outlined.

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Rock failure at tunnel face during construction of mountain tunnels is recognized as a geological hazard. To mitigate this risk, a shotcrete of thickness 3~5cm is sprayed on the rock surface. However, there are cases where rock failure occurs even when the recommended shotcrete thickness is applied. This implies that various factors are thought to contribute to rock failure. This study uses logistics regression to explore the relationship between five rock properties and their influence on rock failure occurrence. The five parameters are weathering, crack interval, crack density, rock fracture energy, and shotcrete thickness. Moreover, the same model is applied to explore this relationship in different geological strata.

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Blasting excavation of deep tunnels is a typical dynamic process subjected to in-situ stress redistribution and blast loading. This study establishes a numerical model for millisecond blasting in the DEM method for two-dimensional circular tunnel excavation. The process of millisecond blasting in a circular tunnel is depicted as a sequence of delayed multiple blastings (multiple dynamic loading-unloadings and static adjustment processes) executed on distinct blasting surfaces that are concentric with the tunnel. After calibration and verification, the dynamic stress evolution process of surrounding rock and the resulting damage to surrounding rock are investigated.

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The purpose of this review paper is to serve as a comprehensive guide for researchers and professionals engaged in the study of EDZs. By summarizing the historical context, EDZ characteristics related to excavation method, and exploring the latest advancements, it equips readers with a deep understanding in EDZ research. Furthermore, by addressing unresolved issues and suggesting future research directions, this paper paves the way for innovative solutions and advancements in geomechanical engineering and underground construction. It identifies unresolved issues and proposes directions for future research, aiming to inspire further investigations and breakthroughs in this area.

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This paper introduces an innovative technique for the automatic extraction of discontinuities in the digital 3D model of a tunnel face. The discontinuity areas are identified by segmenting the projected 2D images of the 3D tunnel face model using a deep learning model called U-Net. The U-Net model integrates various input features including the projected RGB, depth map, and local surface properties-based (i.e., normal vector and curvature) images to effectively segment areas of discontinuity in the images. The segmentation results are subsequently projected back onto the 3D model using depth maps and projection matrices, ensuring an accurate representation of the location and extent of discontinuities within the 3D space.

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Box-jacking is an increasingly popular means for installing underground utilities and infrastructure. Accurately estimating the expected jacking forces in box-jacking is a key design concern, which can ensure the available thrust is not exceeded, to prevent damage to the box-culverts and/or launch shaft, and the construction efficacy of the jacking project. However, prediction of the total jacking force is complicated due to a multitude of influencing factors. The development of jacking force can be influenced by the site geology, the lubricant performance, work stoppages, shape of box culvert, and tunnel boring machine driving style. In this paper, a probabilistic observational approach is introduced aimed at prediction of jacking forces during the box-jacking process. Markov Chain Monte Carlo (MCMC) was adopted for this purpose which allows forecasts to be performed within a probabilistic framework. The proposed framework was applied to a box-jacking case histories completed in Kanagawa: a 150-m drive in fine and medium sands. The forecasts were appraised through comparisons to predictions determined using a classical optimization technique, namely genetic algorithms. The results show that the proposed framework yields highly accurate predictions for the monitored field data, and the prediction accuracy improves obviously as more data are acquired from the drive.

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In high-level radioactive waste disposal facilities, buffer and backfill materials play a crucial role as hydraulic and radionuclide barriers and as thermal-mechanical barrier materials. The performance of bentonite-based buffer-backfill samples subjected to hydration was analyzed. Four cylindrical samples with the same upper buffer material, and different lower backfill materials were subjected to a constant water pressure of 10 psi. The swelling pressure was recorded continually, while X-ray CT scanning were taken periodically to follow the internal evolution of the samples. The initial density, porosity, and swelling ability of the backfill influenced the hydration process and the buffer-backfill interface displacement.

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We have investigated many axial DITF traces on the borehole wall over the depth range of 400~700 m, where a NX borehole was drilled in granite region during the winter season. Considering geomechanical and especially thermal factors, we have analysed the condition of axial DITF regime and have established the parametric relationship estimating axial DITF range with depth. With the general range of thermal stress factor of granite (0.5~1.0 MPa/℃), the seasonal temperature and geothermal gradient at the site, and in-situ stress state and tensile strength of rock mass measured by field hydraulic fracturing, the induced tensile thermal stress could generate the axial DITF for a depth range associated with the field case.

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In this study, stone walls of Kanazawa Castle were clustered using Self-Organizing Maps (SOM) based on the basic information and inspection records of the stone walls described in the “stone wall chart”. In addition, the soundness of stone walls is evaluated by analyzing the characteristics of the stone walls where deformation/displacement are observed, based on the measurement/monitoring data and examination results for countermeasure. Finally, we attempted to acquire data that would contribute to the prioritization of countermeasures.

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We introduce a task-specific convolutional neural network for rock fracture image segmentation, named R-DoGAN (Rock-DoG-GAN), which integrates distinct features of fracture segmentation into the network training and input processes. Instead of using low-dimensional information for network training, a generative adversarial network (GAN)-based perceptual loss is used; and the difference of Gaussians (DoG) images, which contain multi-resolution edge information, are used as additional network input. Test results demonstrate that R-DoGAN outperforms previous networks, despite having fewer network parameters and a smaller training dataset.

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This research focuses on Mode I fracture in rock, vital for tensile fracture resistance in rock engineering such as blasting and hydraulic fracturing. Considering the fact that natural rock often shows anisotropic mechanical properties, we use a GPGPU-accelerated 3-D finite discrete element method (3-D FDEM) with an orthotropic elastic model and a new self-consistent scheme (NSCS) for a comprehensive understanding of anisotropic rock fracture behavior. The study involves numerical simulations of the straight-notched disc bend (SNDB) test to evaluate Mode I fracture toughness under both quasi-static and dynamic loads. We extensively analyze the Mode I fracture process, including fracture patterns and the influence of loading rates on toughness. These insights are crucial for managing rock fractures in various engineering applications, highlighting the importance of considering anisotropy in rock mechanics.

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Water inrush hazard, which is the most frequent geo-hazard encountered by underground engineering, particularly when passing through water-rich geological formations. Understanding the incubation, evolution, and occurrence of water inrush, as well as the reinforcement approach in tunnels, is crucial for disaster mitigation and risk control. To this end, we systematically put forward our solutions to this problem by giving full play to the advantages of discontinuous deformation analysis (DDA). The practical application of our numerical solutions, starting from the hydro-weakening origins, progressing to the water and rock inflow, and culminating in the grouting process for disaster mitigation, demonstrates that our work provides a comprehensive understanding of the evolution mechanism of water inrush disasters.

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