As a novel technology in the field of petroleum exploitation, rock breaking with supercritical carbon dioxide (SC-CO2) has considerable social and economic benefits. To investigate the rock breaking mechanism under SC-CO2 jet impacting, in term of mass and energy conservation, a fluid-solid coupling numerical model was established using smoothed particle hydrodynamics (SPH) method coupled with the finite element method (FEM). Jet movement feature and the stress distribution rule of impact target were obtained. Moreover, the space-time evolution of erosion cavity and failure process of elements were analyzed. The numerical research results are as follows: (1) The hybrid algorithm of SPH-FEM was applicable to accomplish the numerical representation of rock breaking process under SC-CO2 jet impacting, and the simulation results were in good agreement with the experimental data. (2) The asymmetrical distribution characteristic of monitored points caused the erosion cavity to deviate from the geometrical center of the target face. (3) Soft rock under SC-CO2 jet impacting presented two failure forms: erosion and exfoliation. (4) The process of rock breaking with SC-CO2 jet was as follows: when the jet came into contact with the target plane, pressure stress on the mating face and shear stress on the contact edge dominated the evolution of initial compression-shear failure zone. Thereafter, the high diffusivity driven SC-CO2 penetrated into tiny cracks or pores near failure zone, and strong air wedge effect caused tensile failure. With the continuous high-speed impacting, initial failure zone extended to a larger primary failure zone. Moreover, a few discrete failure zones formed due to the high uncertainties of particles’ motion trajectories, which mutually contributed to the main failure zone, and the erosion cavity was formed. When the jet became steady, quasi-static action was applied to rock sample, and erosion range expanded continuously.

Wavelet transform is a widespread and effective method in seismic waveform analysis and processing. Choosing a suitable wavelet has also aroused many scholars’ research interest and produced many effective strategies. However, with the convenience of seismic data acquisition, the existing wavelet selection methods are unsuitable for the big dataset. Therefore, we proposed a novel wavelet selection method considering the big dataset for seismic signal intelligent processing. The relevance r is calculated using the seismic waveform’s correlation coefficient and variance contribution rate. Then values of r are calculated from all seismic signals in the dataset to form a set. Furthermore, with a mean value μ and variance value σ² of that set, we define the decomposition stability w as μ/σ². Then, the wavelet that maximizes w for this dataset is considered to be the optimal wavelet. We applied this method in automatic mining-induced seismic signal classification and automatic seismic P arrival picking. In classification experiments, the mean accuracy is 93.13% using the selected wavelet, 2.22% more accurate than other wavelets generated. Additionally, in the picking experiments, the mean picking error is 0.59 s using the selected wavelet, but is 0.71 s using others. Moreover, the wavelet packet decomposition level does not affect the selection of wavelets. These results indicate that our method can really enhance the intelligent processing of seismic signals.

Current artificial intelligence models for evaluating goaf stability in underground metal mines need a large amount of sample data for training, and their accuracy declines with small sample size. With the aim of solving this problem, this paper proposes an improved TrAdaBoost algorithm based on transfer learning theory. The scope of the TrAdaBoost algorithm is extended from the two-level classification to multi-level classification problems, which makes it suitable for evaluating goaf stability. The isolated forest method is used to filter the bad points of the auxiliary training set, thereby eliminating the interference of abnormal data. The dynamic factor concept is introduced to solve the problem that the weight of source domain data decreases too quickly and irreversibly, and this enhances the generalization performance of the algorithm for different goaf samples. To test the accuracy of the proposed model in predicting goaf stability, an evaluation model is constructed and the performance compared with other algorithms in current use. The prediction accuracy and generalization ability of the model are evaluated by mean square error and F1 measurements, which prove that the performance of the model is excellent. The most obvious finding to emerge from this paper is that, with suitable improvements, goaf evaluation models can still maintain a high level of accuracy with small sample size.

Failure behavior of pillars in deep mines is affected by various cyclic loads that cause initial pre-damage. Pillars will be further damaged and developed in the long-term compressive stress until they are destroyed. To reveal the strength characteristics and crack damage fracture laws after rock pre-damage, uniaxial compression tests were carried out on granite specimens damaged by cyclic loading using the digital speckle correlation method. The experimental results indicate that the mechanical properties of pre-damaged specimens show large damage differences for different cycles. The damage variable of the pre-damaged specimens increases with the increase of cycle number and confining pressure. The damage of specimens is primarily due to the strength weakening effect caused by cycle numbers, and the confining pressure restriction effect is not obvious. The evolution laws of uniaxial compression damage propagation in the pre-damaged specimens show differences and obvious localization phenomenon. Pre-damaged specimens experienced three failure modes in the uniaxial compression test, namely tensile shear failure (Mode I), quasi-coplanar shear failure (Mode II), and stepped path failure (Mode III), and under different pre-damage stress environments with high confining pressures, the failure modes are dominated by Mode II and Mode III, respectively.

The existing methods of generating random mineral grains in numerical rock specimens mostly adopt random polygons (in 2D) or random polyhedrons (in 3D) to represent mineral grains. Although this simplification is effective and reasonable, the complex three-dimensional (3D) shape of mineral grains can be reconstructed by computed tomography (CT) scan and image processing techniques, and then, random grains with real shape can be generated in a numerical specimen. In this paper, we proposed an improved grain-based model to construct random mineral grains with real 3D shape in numerical specimens. The granite specimens with granular minerals are scanned by CT. After the CT slices are denoised and corrected, the minerals, including biotite, quartz, and feldspar, are segmented from the CT slices to reconstruct the 3D mineral shapes; these shapes are stored in grain library. By importing the grain library in PFC (Particle Follow Code, a simulation software), heterogeneous specimens with random mineral grains are constructed, and uniaxial compression tests are carried out on them. Results show that the ranges of Young’s modulus, Poisson’s ratio, and uniaxial compressive strength of these numerical specimens are similar to those of real specimens measured in the laboratory. Therefore, the proposed method is feasible and reasonable. This work can provide a reference for the study of constructing heterogeneous numerical rock specimens in rock mechanics.

To investigate the influence of intersection structures on the mechanical properties and failure mechanisms of rock materials, a series of uniaxial compression tests on complete red sandstone specimens and specimens with various hole shapes (T-shape, cross-shape, shaft-roadway-shape) were conducted by the Instron 1346 servo-controlled rock mechanics testing machine. Flac3d software and Digital Image Correlation (DIC) were used to simulate the internal stress distribution of rock specimens and reproduce the process of fracture, i.e., cracks initiate, propagate and coalesce with each other into macroscopic failure under progressive loading. The results show that the intersection structure has a significant weakening effect on the mechanical properties of the rock. The rock strength, elastic modulus and peak strain of specimens can be ranked as: complete specimens ’ cross-shaped specimens ’ T-shaped specimens ’ shaft-roadway-shaped specimens. The energy consumption ratio of the intersection-structure specimens before the peak reaches more than 30%, which is approximately twice that of the intact sample. The brittleness coefficients of the four types of specimens are 0.18, 0.26, 0.21 and 0.20, respectively. The intersection-structure specimens induced different degrees of tensile and compressive stress concentration zones on the top and bottom sides of the intersection center point. As a result, initial tensile cracks parallel to the loading direction and shear cracks leading to spalling failure on both sides of the holes were formed. With the increase of the axial stress, secondary tensile cracks extending on the opposite direction appeared at the upper and lower corners of the hole. When the far-field cracks that propagated along the diagonal line coalesced with secondary tensile cracks, macro shear-failure of the specimens appeared. With the increase in axial stress, the principal strain monitored during the fracture process of the specimens gradually increased, then it slowly decreased after the peak. The arched boundary of the T-shaped specimen had good stability because of its advantage of suppressing the occurrence of the spalling failure. The specimen with a shaft-roadway-shaped hole could provide compensation space for the secondary tensile cracks due to the existence of the vertical well. The degree of inhibition of initial tensile cracks was so small that the type of specimens was highly prone to instability or failure.