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Granite formations have been frequently involved in subsurface energy‐related activities such as radioactive waste disposal, oil, and gas storage. This is principally because of their mechanical stability, low permeability, and high corrosion resistance. These favorable properties, however, can be compromised by the addition of mineral veins, which tend to occur ubiquitously in upper crustal rock formations. Evaluation of the impact of veins on the integrity and rupture characteristics of granite, especially under true triaxial stresses, is therefore important yet currently underemphasized. This study examines the rupture of veined granite in polyaxial compression via a discrete element method model. In the model with soft veins, the rupture is localized along the fabricated inclined veins (45° relative to the horizontal with strike running in the σ2 direction) under low confining stresses (σ2 < 67 MPa); in contrast, a combined rupture of veins and granite matrix is observed when σ2 is increased to 141.6 MPa. Shear sliding along the inclined veins is revealed by examining the displacement field. Shear‐induced volumetric dilation is suspected in the soft‐veined models in relatively low confining stresses (σ2 < 67 MPa) with sliding and dilation behavior apparently suppressed at σ2 = 141.6 MPa. Hard veins impede local rupture, resulting in conjugate shear bands. The well‐recognized σ2 effect is observed for the hard‐veined models, while no pronounced σ2 effect is noticed for the soft‐veined models. This study also reveals that vein thickness has a negligible impact on rupture characteristics, which is however profoundly affected by vein orientation. Published version The author thanks the financial supportof the Open Fund of State KeyLaboratory of Geohazard Preventionand Geoenvironment Protection(Chengdu University of Technology)(Grant no. SKLGP2020). This materialis partially based on research/worksupported by the Land and LiveabilityNational Innovation Challenge underL2 NIC (Award no. L2NICCFP1-2013-3).

Cryptocrystalline flint is an extremely hard siliceous rock that is found in chalk formations. The chalk is frequently a prefered rock type, which in recent decades is often used as a host for underground rock caverns and tunnels in Europe and North America. A reliable estimation of the uniaxial compressive strength (UCS) of the extremely strong flint, with an average UCS of about 600 MPa will provide guidance for a proper engineering design, where flint is encountered, thereby avoiding project progress delay, litigation as well as economic consequences. Conventional UCS measurement using core samples is cumbersome for flint due to the extreme strength and hardness of the rock, for which the core sample preparation process is often extremely difficult. In this study, the UCS prediction models of flints collected from the North-West Europe were developed and the validity of the developed models was investigated. A series of laboratory index tests (comprising the three-point-bending, point load, ultrasonic velocity, density, Shore hardness and Cerchar Abrasivity tests) were perfomed. The index test results were correlated with the UCS values previously determined in the laboratory using both cylindrical and cuboidal specimens to develop the UCS prediction models. Regression analysis of the UCS and the index test results was then performed to evaluate for any potential correlations that can be applied to estimate the UCS of the cryptocrystalline flint. Intensive validity and comparison studies were performed to assess the performance of the proposed UCS prediction models. This study showed that UCS of the tested flint is linearly correlated with its point load strength index, tensile strength and compressional velocity, and is parabolically correlated with its density. The present study also demonstrated that only a couple of the previously developed empirical UCS models for estimating UCS are suitable for flint, which should be used with care. Accepted version

Rocks in cold regions tend to experience exacerbated degradation under the combined effects of environmental and anthropogenic factors, which may arise from, for example, temperature fluctuation, mechanical excavation, and blasting. Activities related to rock support or open-pit slope optimization in cold regions require a complete understanding of the failure mechanisms of rock under the complex conditions. This paper quantitatively documents the impact of combined cyclic mechanical load and freeze-thaw cycles (i.e., the effect of stress “history”) on the microstructural evolution and mechanical degradation of three porous sandstones with distinct porosity values (from 3.9 to 14.1%). The three sandstone samples were collected from different geological regions in China. The microstructural evolution of the tested samples was quantitatively analyzed using the low-field Nuclear Magnetic Resonance (NMR) technique. To investigate sample degradation arising from the impact of the stress “history”, the cyclic-loaded and freeze-thaw cycled samples were eventually compressed to failure, during which an acoustic emission system was used to monitor microseismic activities. The results of the study show that the porosity of all tested sandstone samples was increased after cyclic load, with a much more rapid and further increase in porosity observed for samples being subsequently treated under the freeze-thaw cycles. More interestingly, the Chuxiong sandstone with relatively small porosity values were much more sensitive to the impact of cyclic load compared with the Linyi sandstone, exhibiting a somewhat larger increase rate in porosity. However, the Linyi sandstone with larger initial porosity values exhibited a relatively large increase rate in porosity under the multiple freeze-thaw treatments. The multiple freeze-thaw treatments mainly resulted in the development of relatively large pores. The results of the uniaxial compression tests show that the strength reduction of the samples being solely treated by freeze-thaw cycles was within the range of 5–10%, whereas it was within the range of 20–40% for those samples subjected to the combined cyclic load and freeze-thaw cycles. This work is financially supported by the Research Funds for the Central Universities of China (award no. 2017zzts164) and the National Natural Science Foundation of China (award no. 11772358).

The existence of highly complex and heterogeneous geological and hydrogeological conditions makes it cumbersome to determine grouting parameters for a cost-efficient grouting process. Although many empirical, numerical and analytical models have been proposed previously, there are still some gaps between the existing predictive models and practical grouting applications, leading to the fact that practical grouting design mainly depends on onsite engineers’ experience. In this study, we propose to use data mining to discover grouting knowledge from onsite data of a project in Singapore. After systematic analysis of data concerning the geological information, hydrogeological conditions and grouting records, an artificial neural network was structured to further extract grouting knowledge, based on which the grout take can be estimated under given geological and hydrogeological conditions. The grout take at individual station is found to be closely correlated with overall water inflow and Q value of rock mass, making it promising to estimate the potential grout take, once probe hole and face mapping information are given before pre-grouting. The degree of correlation between input parameters and the corresponding model accuracy are significantly affected by the classification methods used.