This article is summary of the paper published in “International Journal of Rock Mechanics and Mining Sciences” (Ishibashi et al., 2023a). To provide key parameters and constitutive laws essential for field-scale multiphysics simulations that accurately predict fracture network structures in enhanced geothermal systems (EGS) and resultant energy extraction, we investigate the comprehensive spectrum of hydraulic shear processes in granite fractures and reassess the connection between hydraulic and mechanical properties during shear slips. Key results from our novel laboratory experiments include the following: (1) Fracture permeability of granite increases due to hydraulic shear slip even at an effective normal stress exceeding 50 MPa, (2) Shear slip and stress drop are proportional, and the increase in fracture permeability correlates with the total shear slip displacement, and (c) although hydraulic shear slip tends to make fracture surfaces slightly smoother, the factual characteristics of surface are maintained after slip. By integrating our experimental results with seismological analysis, we first examine the energy balance during the hydraulic shearing of preexisting rock fractures and highlight the critical role of the elastic potential energy stored in the surrounding bulk rock masses. Subsequently, we derive a constitutive model that relates to the permeability change of granite fractures during hydraulic shearing under typical crustal stress conditions of EGS, estimating that the maximum change in fracture permeability due to shear dilation is approximately 20-fold, though scale effects are not considered. In summary, we successfully demonstrate novel and advanced insights into hydro-mechanical coupled processes during hydraulic shearing, aiming to improve the accuracy of fracture network designs in EGS technology.

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Excavation damaged zones are created when excavating underground caverns and generate AE at micro-amplitude. This research is a challenge to apply DAS with C-OTDR technology to AE measurement. The results of laboratory and in-situ experiments showed that differences in optical fiber specifications did not have a significant effect on AE measurements. In addition, it was found that source location can be identified in the same way as with conventional in-situ AE measurements. Furthermore, the monitoring range of conventional AE sensors is generally 5 m to 10 m, but the new method can extend the monitoring range to 35 m.

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This article summarizes the results of development based on the recent studies (Kojima et al., 2024a, b). On-site observation of excavated tunnel faces is difficult due to safety regulations and a shortage of geological experts. Although several tools have been proposed for remotely observing the face with photographs or videos, they do not provide three-dimensional (3-D) realistic observations and measurements. We developed a new method to solve this problem, using a 3-D point cloud and a virtual reality (VR) system. This method allows to examine a tunnel face in detail remotely. We validated the effectiveness of this new method by comparing it to a conventional on-site method by visual inspection in a tunnel where talus deposits are distributed. The VR method revealed the detailed distribution and geological structures of the talus at the tunnel crown, whereas the conventional method could not. These results show that the VR method could be an effective solution to this problem.

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This article summarizes a PhD dissertation titled Creating granitic geothermal reservoirs by carbon dioxide injection, submitted to the Graduate School of Environmental Studies, Tohoku University. Carbon dioxide (CO₂) has been proposed as an alternative fracturing fluid to create geothermal reservoirs, because it is less reactive to rock-forming minerals, capable to reduce water footprint, and easier to handle compared to the competing alternative gasses. CO₂ has also low viscosity (‹ 100 μPa⋅s) across wide range of conditions, potentially allowing its injection to induce complex, cloud-fracture network (CFN) at conventional (c.a. 150–300 °C) and superhot (› c.a. 400 °C) geothermal conditions. Experiments on intact granite samples clarified that CO₂ injection achieves CFN at conventional and superhot geothermal conditions, through the stimulation of pre-existing microfractures by the low-viscosity CO₂. The aperture of fractures in the CFN increases with temperature and differential stress, and the fracturing pressure can be predicted using the Griffith failure criterion. Then, experiments on cylindrical granite samples with sawcut, serving as an analogue of a natural fracture, elucidated that CO₂ injection achieves CFN in naturally-fractured granite, along with the shearing of the natural fractures. Finally, experiments into granite samples with CFN revealed that chelating agent solution injections improves the permeability of the CFN without inducing excessive rock deformation and acoustic emission, both at slightly acidic and alkaline conditions, and under varying stress state. At large scale, and in radial flow condition, chelating agent solution injection under slightly acidic condition induces higher degree of mineral dissolution around injection borehole; thus, the injection should utilize a lower chelating agent concentration to allow for a lower solution-viscosity, and more uniform degree of mineral dissolution over a greater distance from borehole.

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Understanding the dynamic tensile fracture behavior of rocks is a critical issue in rock engineering, particularly in contexts such as blasting operations, seismic events, and impact-induced failures. Conventional Brazilian disk tests are widely used for estimating tensile strength, but when the loading rate exceeds approximately 20 s⁻¹, these tests frequently result in shear fractures near the loading ends instead of the desired central tensile failure. This limitation has prompted the adoption of spalling tests, typically conducted with Hopkinson bar systems, as an alternative means of evaluating the dynamic tensile strength of rocks. However, existing evaluation methods for spalling tests often produce inconsistent results, not only in the determination of tensile strength but also in the estimation of strain-rate conditions. Such discrepancies make it difficult to achieve a clear and reliable understanding of the strain-rate dependency of tensile strength, which is essential for both theoretical interpretation and engineering applications. This is the summary of the original paper published by Min et al. (2023), which received the Best Paper Award from the Japanese Society for Rock Mechanics (JSRM). In the study, a three-dimensional finite–discrete element method (3D FDEM) is employed to simulate the dynamic fracture process in spalling tests using granite specimens. The numerical simulations successfully reproduce both the characteristic fracture patterns and the free-surface velocity responses observed in corresponding laboratory experiments. Furthermore, the modeling results provide insights into the sources of discrepancies among existing evaluation approaches, clarifying the conditions under which they diverge. By integrating experimental evidence with advanced numerical simulation, this framework contributes to improving the accuracy and reliability of dynamic tensile strength assessment, while also providing a more robust interpretation of strain-rate dependency in rock tensile behavior.

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Weathering of rocks can cause severe geohazards, such as rockfalls and collapses, posing threats to human safety. Understanding the mechanisms of rock weathering and developing geotechnologies that can autonomously regulate this process are therefore essential for sustainable society. Although weathering is largely governed by physical and chemical processes, endolithic microorganisms are increasingly recognized as significant contributors. This biologically driven process, known as microbial weathering, has been observed on rock outcrops and cave surfaces; however, few studies have investigated its role in caves, and none have directly linked it to cave stability. In this study, we examined microbial weathering in an artificial sandstone cave (Nybi sandstone) in Okinawa, Japan, focusing on surface flora, microstructure, and rock strength. The cave, excavated ~80 years ago, shows advanced weathering on both its ceiling and sidewalls, limiting accessibility. Field investigations revealed a progressive decrease in sidewall strength from the upper to lower sections, where 16S rRNA analysis identified abundant microbial communities, including cyanobacteria. The activation of these microorganisms promotes bio-alkalization on the sandstone surface, accelerating weathering. These results demonstrate that microbial activity plays a crucial role in the deterioration of sandstone caves and should be considered in the assessment of cave safety and long-term stability.

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In geomechanical parameter searches for elastoplastic constitutive models conducted through element tests, state-of-the-art techniques are predominantly based on stochastic optimization algorithms to calibrate parameters against experimental stress-strain curves. However, these methods are prone to falling into local optima instead of identifying the global optimum and require extensive computation time. To overcome these challenges, we propose a novel parallelized computational method, implemented as an open-source program. By leveraging vectorization and parallelization on GPUs and TPUs, the method achieves over 1000× computational speedup, making global exhaustive search a practical alternative to stochastic optimization for complex parameter calibrations. To demonstrate its effectiveness, the method was applied to calibrate the geomechanical parameters of silica sand in consolidated-drained triaxial compression tests under different confining pressures. The results showed that exhaustive searches using GPUs completed the calibration in just 11 minutes, whereas Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) required 15–21 hours. Additionally, the proposed method outperformed stochastic optimization in terms of Mean Absolute Error (MAE) and Mean Squared Error (MSE), achieving superior accuracy in matching experimental data. This advantage significantly enhances the accuracy and the efficiency of computational geotechnics, enabling more precise and scalable implementations of sophisticated elastoplastic models.

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