International Journal of Rock Mechanics and Mining Sciences最新文献_第4页

Rationality analysis of lattice Boltzmann method simulation for gas seepage in mesoscale porous media 点阵玻尔兹曼法模拟中尺度多孔介质中气体渗流的合理性分析

IF 7.5 1区工程技术 Q1 ENGINEERING, GEOLOGICAL

International Journal of Rock Mechanics and Mining Sciences

Pub Date : 2025-12-29 DOI: 10.1016/j.ijrmms.2025.106382

Wei Wang , Weizhong Chen , Jianping Yang , Haizeng Pan , Jiawei Huang , Feilong Liu , Ziang Xia

The rationality of applying the lattice Boltzmann Method (LBM) to the study of gas permeation in porous media, particularly in rocks, requires further discussion. This article focuses on the study of micro-nano scale pores typical of rock structures. It explores the applicability of algorithms for mesoscale gas seepage in porous media, including collision stream, boundary condition, and relaxation time related to the Knudsen number, from the LBM principle. This research firstly verifies classic problems such as Couette flow, Poiseuille flow, around circular cylinder flow, and variable cross-section slit flow. Then, the seepage behaviours of various gases are simulated under different channel sizes. The improved quartet structure generation set (QSGS) method is employed to generate porous media grids for testing. Finally, the calculations for real microfluidic chip channels are performed and compared with experimental phenomena. Results indicate that the LBM algorithm used in this article can accurately simulate the shear collision behaviour between fluid particles as well as their interactions with obstacles. Using the relaxation time associated with the Knudsen number and the rebound-slip combination boundary can effectively replicate gas slip effects under micro-nano scales and demonstrate the differences in gas permeation behaviour of different types in LBM simulation. Additionally, LBM can also effectively reflect the influence of micro-nano scale porosity, directionality, and tortuosity on gas permeability. This research supports the credibility of LBM for simulating gas seepage in mesoscale porous media.

晶格玻尔兹曼方法（LBM）应用于多孔介质特别是岩石中气体渗透研究的合理性有待进一步探讨。本文主要研究岩石结构中典型的微纳尺度孔隙。从LBM原理出发，探讨了多孔介质中尺度气体渗流算法的适用性，包括碰撞流、边界条件和与Knudsen数相关的松弛时间。本研究首先验证了Couette流动、Poiseuille流动、绕圆柱流动、变截面狭缝流动等经典问题。然后，模拟了不同通道尺寸下各种气体的渗流行为。采用改进的四重结构生成集（QSGS）方法生成多孔介质网格进行测试。最后，对实际微流控芯片的通道进行了计算，并与实验现象进行了比较。结果表明，本文所采用的LBM算法可以准确地模拟流体颗粒之间的剪切碰撞行为以及它们与障碍物的相互作用。利用与Knudsen数相关的松弛时间和回弹-滑移组合边界可以有效地模拟微纳尺度下的气体滑移效应，并展示不同类型气体在LBM模拟中的渗透行为差异。此外，LBM还能有效反映微纳尺度孔隙度、方向性和弯曲度对渗透率的影响。本研究支持了LBM模拟中尺度多孔介质中气体渗流的可信性。

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引用次数: 0

Study on dynamic early warning method for coal and gas outburst disasters based on data mining and unsupervised clustering 基于数据挖掘和无监督聚类的煤与瓦斯突出灾害动态预警方法研究

IF 7.5 1区工程技术 Q1 ENGINEERING, GEOLOGICAL

International Journal of Rock Mechanics and Mining Sciences

Pub Date : 2025-12-27 DOI: 10.1016/j.ijrmms.2025.106386

Binglong Liu , Zhonghui Li , Chaolin Zhang , Shan Yin , Zesheng Zang , Yuanming Hu

The gas concentration monitoring data contains a large amount of potentially effective early-warning information. However, the effective information that can be extracted from the raw data and its statistical features is limited, which restricts its application in the early warning of coal and gas outburst disasters. In this study, gas concentration monitoring data from different tunneling faces under various operational conditions were collected, along with gas outburst prediction indicators drilling cuttings weight from the tunneling faces. Based on the EN-TSFRESH method, a total of 784 features were extracted from 8-h (one work shift) gas concentration monitoring data, covering seven categories including statistical, time-frequency, trend, and stability features. The results indicate that the high-dimensional gas concentration features within each time window contain potential early-warning information and show correlation with static indicators. A weakly supervised feature selection method was employed to extract low-dimensional features such as Benford law correlation, peak value, cumulative value, absolute values of Fourier transform coefficients, and energy distribution across different time segments. By combining t-SNE and PCA for dimensionality reduction and visualization, unsupervised clustering methods were applied to classify various gas concentration monitoring datasets. Compared with k-means clustering, hierarchical clustering achieved the highest accuracy, approximately 97.2 %. The high-risk events identified through unsupervised clustering showed a strong correlation with on-site measured drilling cuttings weight, demonstrating the method's potential for early warning of gas outbursts. This study provides theoretical support for dynamic early warning of gas outbursts in tunneling faces and holds significant implications for safe and efficient coal mine production.

气体浓度监测数据中含有大量潜在有效的预警信息。然而，从原始数据及其统计特征中提取的有效信息有限，制约了其在煤与瓦斯突出灾害预警中的应用。本研究收集了不同工况下不同掘进工作面瓦斯浓度监测数据，以及掘进工作面瓦斯突出预测指标钻屑重量。基于EN-TSFRESH方法，从8 h（一个工作班）气体浓度监测数据中提取了784个特征，包括统计特征、时频特征、趋势特征和稳定性特征等7类特征。结果表明，各时间窗内的高维气体浓度特征包含潜在的预警信息，并与静态指标具有相关性。采用弱监督特征选择方法提取低维特征，如Benford律相关性、峰值、累积值、傅里叶变换系数绝对值以及不同时间段的能量分布。结合t-SNE和PCA进行降维和可视化，采用无监督聚类方法对各类气体浓度监测数据集进行分类。与k-means聚类相比，分层聚类的准确率最高，约为97.2%。通过无监督聚类识别的高风险事件与现场测量的钻屑重量有很强的相关性，证明了该方法在天然气爆发早期预警方面的潜力。该研究为掘进工作面瓦斯突出动态预警提供了理论支持，对煤矿安全高效生产具有重要意义。

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引用次数: 0

Influence of pore fluid on the elasto-plastic property of shales 孔隙流体对页岩弹塑性特性的影响

IF 7.5 1区工程技术 Q1 ENGINEERING, GEOLOGICAL

International Journal of Rock Mechanics and Mining Sciences

Pub Date : 2025-12-27 DOI: 10.1016/j.ijrmms.2025.106388

Linghao Chen , Wanqing Shen , Shuitao Zhang , Zhilei Luo , Jianfu Shao , Linlin Wang

The mechanical response of shale under various saturation fluids is critical for many geo-engineering applications, whereas the analysis of elasto-plastic evolution on shale under such conditions remains limited. This study investigates the effect of pore fluid on the mechanical behavior of shales. The hydrostatic, uniaxial, and triaxial compression tests are conducted on specimens under dry, oil (nonpolar)-saturated, and water (polar)-saturated states. The experimental results are calibrated using two models, which enable the quantification of the influence of saturation fluids on the elasto-plastic properties (cohesion, frictional angle, strain hardening rate, etc.). In particular, the micromechanical model, explicitly considering the effect of porosity, enables quantifying the role of swelling, which is intuitively considered as a key mechanism governing the mechanical property of water-saturated shale. The results indicate that dry shale exhibits high stiffness and isotropy, while fluids reduce stiffness and induce anisotropy. The pore fluid also facilitates the rock to deform plastically. Calibration of the plasticity models indicates that the variation of plastic parameters is associated with a decrease in cohesion strength, rather than a reduction in the friction angle. The strain hardening rate decreases in shale saturated with oil or water, with water causing up to a twofold reduction. Contrary to common assumptions, the influence of saturation fluid on shale's elasto-plastic behavior is not primarily due to clay swelling or an increase in porosity, as swelling is limited. Instead, adsorption-related surface energy and fluid-induced damage have a more significant impact on shale's mechanical properties.

页岩在各种饱和流体条件下的力学响应对于许多地质工程应用至关重要，而页岩在这种条件下的弹塑性演化分析仍然有限。研究了孔隙流体对页岩力学行为的影响。在干、油（非极性）饱和和水（极性）饱和状态下，对试件进行静力、单轴和三轴压缩试验。采用两个模型对实验结果进行了校准，从而可以量化饱和流体对弹塑性性能（黏聚力、摩擦角、应变硬化率等）的影响。特别是，微观力学模型明确考虑了孔隙度的影响，可以量化膨胀的作用，直观地认为膨胀是控制饱和水页岩力学性质的关键机制。结果表明，干页岩具有较高的刚度和各向异性，而流体降低了刚度并诱发了各向异性。孔隙流体也有利于岩石的塑性变形。塑性模型的校正表明，塑性参数的变化与黏聚强度的降低有关，而不是与摩擦角的减小有关。在饱和油或饱和水的页岩中，应变硬化速率降低，其中水导致应变硬化速率降低两倍。与通常的假设相反，饱和流体对页岩弹塑性行为的影响主要不是由于粘土膨胀或孔隙度增加，因为膨胀是有限的。相反，与吸附相关的表面能和流体损伤对页岩力学性能的影响更为显著。

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引用次数: 0

Mechanical and fracture behavior of red sandstone under confining pressure and laser irradiation using CT scanning and uniaxial compression 围压和激光照射下红砂岩力学与破裂行为的CT扫描和单轴压缩研究

IF 7.5 1区工程技术 Q1 ENGINEERING, GEOLOGICAL

International Journal of Rock Mechanics and Mining Sciences

Pub Date : 2025-12-27 DOI: 10.1016/j.ijrmms.2025.106389

Xuemin Zhou , Haichun Hao , Lei Yang , Junjun Liu , Jing Xie , Yuanru Li , Lang Zhou , Jiahua Li , Mingzhong Gao

Laser rock breaking, an emerging noncontact and high-efficiency rock-breaking technique, has recently gained attention in deep resource development and extreme-environment drilling. Most studies focus on laser parameters, while the effects of real engineering environments on rock-breaking have received much less attention. In particular, the interaction mechanisms between lasers and rock under confining pressure remain poorly understood. In this study, typical red sandstone was selected as the research object, and a laser rock-breaking experimental system in which confining pressure is controlled was established. Combined with Computed Tomography (CT) scanning and uniaxial compression tests, the thermal response, fracture characteristics, and evolution of the mechanical behavior of rocks after laser irradiation under different confining pressures (0–3 MPa) were qualitatively and quantitatively analyzed. Furthermore, the influence mechanism of confining pressure on crack propagation was investigated. This research yielded the following results: (1) The laser-induced temperature field caused the red sandstone to undergo a heating–melting–evaporation–solidification phase transition process, altering its mineral composition. (2) The confining pressure affected the crack development morphology caused by the laser, and a lower confining pressure caused cracks to develop longitudinally. (3) The spatial distribution of internal cracks was analyzed by CT, revealing the fractal characteristics of different regions of the sample after laser irradiation under the influence of confining pressure. (4) After laser irradiation, both the uniaxial compressive strength and elastic modulus of red sandstone decreased relative to the original sample, and higher confining pressure led to weaker mechanical degradation. The research findings presented in this paper reveal the crack evolution mechanisms and strength degradation effects of laser-induced rock breaking under confining pressure, providing a basis for a deeper understanding of the multi-field coupling between lasers and rock, and offering valuable insights and guidance for the efficient application of laser technology in complex stress environments and engineering practice.

激光破岩技术是一种新兴的非接触式高效破岩技术，近年来在深部资源开发和极端环境钻井中受到广泛关注。大多数研究都集中在激光参数上，而实际工程环境对破岩的影响很少得到关注。特别是，在围压下，激光与岩石之间的相互作用机制仍然知之甚少。本研究以典型红砂岩为研究对象，建立了围压可控的激光破岩实验系统。结合计算机断层扫描（CT）和单轴压缩试验，定性和定量分析了不同围压（0 ~ 3 MPa）下激光照射后岩石的热响应、破裂特征和力学行为演变。进一步研究了围压对裂纹扩展的影响机理。研究结果表明：(1)激光诱导温度场使红砂岩经历了加热-熔化-蒸发-凝固的相变过程，改变了红砂岩的矿物组成。(2)围压对激光引起的裂纹发育形态有影响，较低的围压使裂纹纵向发育。(3)利用CT分析了内部裂纹的空间分布，揭示了围压影响下激光照射后试样不同区域的分形特征。(4)激光照射后，红砂岩的单轴抗压强度和弹性模量均较原始试样降低，且围压越高，力学退化越弱。研究结果揭示了围压下激光诱导岩石破裂的裂纹演化机制和强度退化效应，为深入理解激光与岩石的多场耦合提供了基础，为激光技术在复杂应力环境和工程实践中的有效应用提供了有价值的见解和指导。

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引用次数: 0

A permeability determination method for irregular rocks based on numerical Transient Pressure Pulse Decay (TPPD) testing 基于瞬态压力脉冲衰减（TPPD）数值测试的不规则岩石渗透率测定方法

IF 7.5 1区工程技术 Q1 ENGINEERING, GEOLOGICAL

International Journal of Rock Mechanics and Mining Sciences

Pub Date : 2025-12-24 DOI: 10.1016/j.ijrmms.2025.106390

Dongyu Li , Qingquan Liu , Heinz Konietzky , Kun Sang Lee , Peizhuang Han , Biao Lv

Permeability is a key parameter characterizing the flow capacity within porous reservoirs. The Transient Pressure Pulse Decay (TPPD) method is a widely employed technique for permeability characterization; its reliance on the formula necessitates regularly shaped samples. However, samples often experience fragmentation during coring, making it difficult to obtain regular specimens. This study proposes an innovative method combining a modified TPPD experiment for irregular samples with a mathematical model describing the entire testing process, where permeability is determined through inverse problem optimization. Initially, the study conducts tests on regular samples. The results demonstrate strong agreement between the numerically simulated and experimentally measured pressure differential data, with fitting accuracy (R²) beyond 0.9776. Those confirm that the proposed model accurately captures the physical process of the TPPD experiment. The best inverted permeability of 0.148 mD (95 % CI: [0.142, 0.156] mD) closely matches the formula-derived value of 0.143 mD, further validating the model's accuracy. Subsequently, irregular specimens are prepared from the original regular samples and tested by the new method. The results show excellent fitting precision, with R² consistently exceeding 0.9659, proving that the model can also precisely replicate the testing process for irregular samples. However, the permeability differs significantly from that of the original sample, which is attributed to imperfections in the preparation process. The new method has removed the limitation of laboratory permeability measurement on the shape of rocks, facilitating the research on the flow in unconventional reservoirs.

渗透率是表征多孔储层渗流能力的关键参数。瞬态压力脉冲衰减（TPPD）方法是一种广泛应用于渗透率表征的技术；它对公式的依赖需要有规则形状的样本。然而，在取心过程中，样品经常会碎裂，这使得获得常规样品变得困难。本研究提出了一种将不规则样品的改进TPPD实验与描述整个测试过程的数学模型相结合的创新方法，其中渗透率通过逆问题优化确定。最初，该研究对常规样本进行测试。结果表明，数值模拟与实测压差数据吻合较好，拟合精度（R2）均在0.9776以上。这些都证实了所提出的模型准确地捕捉了TPPD实验的物理过程。最佳反向渗透率为0.148 mD (95% CI: [0.142, 0.156] mD)，与公式推导值0.143 mD非常接近，进一步验证了模型的准确性。随后，在原规则试样的基础上制备不规则试样，并采用新方法进行测试。结果表明，拟合精度非常好，R2始终超过0.9659，证明该模型也可以精确地复制不规则样本的测试过程。然而，渗透率与原始样品有很大不同，这是由于制备过程中的缺陷造成的。该方法消除了实验室渗透率测量对岩石形状的限制，为非常规储层渗流研究提供了方便。

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引用次数: 0

Nonlinear flow in rough rock fractures: A geometric model incorporating mesoscale structure and Reynolds number effects 粗糙岩石裂隙中的非线性流动：一个包含中尺度结构和雷诺数效应的几何模型

IF 7.5 1区工程技术 Q1 ENGINEERING, GEOLOGICAL

International Journal of Rock Mechanics and Mining Sciences

Pub Date : 2025-12-23 DOI: 10.1016/j.ijrmms.2025.106378

Rihua Jiang , Kang Duan , Luchao Wang , Qiangyong Zhang , Jingrui Liu , Xuejian Li

Understanding nonlinear seepage in fractures - strongly governed by mesoscale fracture surface morphology - is critical for hydrogeology, geothermal energy, and underground resource extraction. In this study, a geometric model for nonlinear flow in rough fracture is developed, which improves upon existing geometric formulations by incorporating Reynolds-number-dependent local resistance effects and establishing quantitative relationships between mesoscopic geometric parameters, the Reynolds number, and the Forchheimer coefficients (A and B). Model validation is performed through laboratory experiments and numerical simulations. Sensitivity analysis of mesh resolution reveals that reducing the number of fracture segments significantly decreases the coefficient B, and dimensionless analysis indicates that the number of fracture segments should exceed one-tenth of the fracture length-to-aperture ratio to ensure predictive accuracy. Using the model, A and B are computed for 553 fracture profiles, and the influence of roughness Z₂ and apertures on seepage characteristics is studied. Results reveal that Z₂ shows a power-law relationship with A, and a linear relationship with B. Larger apertures reduce both linear and nonlinear flow resistance, while increased roughness enhances inertial effects. A complex interplay is observed between aperture and roughness in controlling seepage dynamics, with roughness dominating at smaller apertures and aperture effects prevailing at larger scales. The critical Reynolds number exhibits a non-monotonic dependence on hydraulic aperture, decreasing initially and increasing thereafter, while higher roughness amplifies inertial effects and promotes nonlinear seepage. These findings advance the understanding of nonlinear flow transitions in fractured media by linking mesoscale geometric structure to key hydraulic parameters.

裂缝的非线性渗流受中尺度裂缝表面形态的强烈控制，理解裂缝中的非线性渗流对于水文地质学、地热能和地下资源开采至关重要。本研究建立了粗糙裂缝中非线性流动的几何模型，该模型在现有几何公式的基础上进行了改进，纳入了依赖于雷诺数的局部阻力效应，并建立了介观几何参数、雷诺数和Forchheimer系数（a和B）之间的定量关系。模型验证通过实验室实验和数值模拟进行。网格分辨率敏感性分析表明，减少裂缝段数可显著降低裂缝系数B，无量纲分析表明，裂缝段数应超过裂缝长度孔径比的十分之一，以保证预测精度。利用该模型计算了553条裂缝剖面的A和B值，并研究了粗糙度Z2和孔径对渗流特性的影响。结果表明，Z2与a呈幂律关系，与b呈线性关系。孔径越大，线性和非线性流动阻力均减小，粗糙度越大，惯性效应增强。孔径和粗糙度在控制渗流动力学方面存在复杂的相互作用，较小孔径下粗糙度占主导地位，较大尺度下孔径效应占主导地位。临界雷诺数与水力孔径呈非单调依赖关系，先减小后增大，而粗糙度的增大放大了惯性效应，促进了非线性渗流。这些发现通过将中尺度几何结构与关键水力参数联系起来，促进了对裂缝介质中非线性流动转变的理解。

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引用次数: 0

Rock mass discontinuity trace mapping using a voxel-based morphology-topology framework 基于体素的岩体结构面轨迹映射

IF 7.5 1区工程技术 Q1 ENGINEERING, GEOLOGICAL

International Journal of Rock Mechanics and Mining Sciences

Pub Date : 2025-12-19 DOI: 10.1016/j.ijrmms.2025.106385

Jingsong Sima, Qiang Xu, Xiujun Dong, Haoliang Li, Qiulin He, Bo Deng

Discontinuity trace is a critical geological information element in engineering geology. However, existing point cloud-based methods still face challenges, including insufficient trace connectivity and ambiguous topological relationships between trace. To address these limitations, this paper proposes a voxel-based morphology-topology approach instead of complex point connection algorithms. Initially, we coarsely extract trace points by applying the elbow method to optimize K-means++ clustering, which based on normal vector neighborhood deviations of point clouds. After voxelizing the trace points, we enhance and refine spatial connectivity through morphological dilation and an improved secondary erosion process. We then define Euler characteristics to characterize the topological properties of the voxels. Finally, obtain a simplified voxel skeleton containing trace points through topological iterative deletion, generate vectorized trace paths by connecting voxel centers, followed by post-processing. We validate the method through three slope cases, the topological connectivity rate compared to existing methods is the highest reaching 90.48 %, 90.91 %, and 91.97 %, respectively. demonstrating its ability to identify finer trace details more precisely than alternative approaches. The proposed method enables robust extraction of vectorized paths from the trace spatial skeleton, which shifting from connecting points to simplifying a topological structure. This approach offers reliable technical support for digital geological logging and intelligent assessment of engineering stability.

不连续面迹是工程地质中重要的地质信息元素。然而，现有的基于点云的方法仍然面临着迹线连通性不足、迹线之间拓扑关系不明确等挑战。为了解决这些限制，本文提出了一种基于体素的形态拓扑方法，而不是复杂的点连接算法。首先，基于点云的法向量邻域偏差，采用肘部法优化k -means++聚类，对迹点进行粗提取。在对痕迹点体素化之后，我们通过形态扩张和改进的二次侵蚀过程来增强和细化空间连通性。然后，我们定义欧拉特征来表征体素的拓扑属性。最后，通过拓扑迭代删除得到包含轨迹点的简化体素骨架，通过连接体素中心生成矢量化轨迹路径，并进行后处理。通过三种斜坡情况验证，与现有方法相比，拓扑连通性率最高，分别达到90.48%、90.91%和91.97%。演示其比其他方法更精确地识别更精细的跟踪细节的能力。该方法实现了从轨迹空间骨架中提取矢量化路径的鲁棒性，从连接点转向简化拓扑结构。该方法为数字地质测井和工程稳定性智能评价提供了可靠的技术支持。

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引用次数: 0

Confining pressure effects on mining-induced unloading failure characteristics along a rough fault: Experimental and numerical investigations 围压对粗断层采动卸荷破坏特征的影响：实验与数值研究

IF 7.5 1区工程技术 Q1 ENGINEERING, GEOLOGICAL

International Journal of Rock Mechanics and Mining Sciences

Pub Date : 2025-12-18 DOI: 10.1016/j.ijrmms.2025.106356

Minghe Ju , Han Zhu , Liyuan Yu , Yang Zou , Xin Peng , Linming Dou , Qiang Zhang , Xiaofeng Li

Mining disturbances can induce fault unloading slip, posing major challenges in underground engineering. This study examines fault slip behavior under varying fault roughness and confining pressures using laboratory experiments and numerical simulations. Acoustic Emission (AE) and Digital Image Correlation (DIC) were employed to capture full-process slip characteristics, while Confocal Laser Scanning Microscopy (CLSM) revealed microstructural changes on fault surfaces. Discrete element modeling with the Smooth Joint Model (SJM) in PFC was used to explore microcrack evolution and localized stress–strain responses. Results show that fault unloading slip is governed by the evolution of normal and shear stresses on the fault plane and proceeds through four stages. In the linear steady stage, stress and deformation fields remain stable. When confining pressure reduces to 80 %–85 % of its initial value, the nonlinear steady stage emerges, with stable displacements. Further unloading leads to the meta-instability stage, characterized by 5 %–10 % stress fluctuations, localized displacements, and increased high-energy AE events. Finally, the instability stage exhibits strong stress oscillations and rapid macroscopic slip. Energy release cycles lengthen with increasing confining pressure and roughness. For a 180-grit fault, the cycle extends from 58 s at 10 MPa to 105 s at 30 MPa; at 30 MPa, roughness from 1000-grit to 60-grit increases the cycle from 68 s to 142 s. CLSM and simulations confirm that high-roughness surfaces concentrate stresses at asperities, enhancing damage, whereas smooth surfaces show uniform wear. With confining pressure ≥30 MPa and roughness ≤180-grit, deformation shifts from elastic to plastic and wear from abrasive to adhesive. Coupled AE b-value and entropy evolution—transitioning from high to low states—effectively indicate slip stages. These findings advance understanding of fault slip instability in deep coal mining and provide guidance for monitoring and early warning.

采矿扰动可诱发断层卸荷滑移，给地下工程带来重大挑战。本研究通过实验室实验和数值模拟，考察了不同断层粗糙度和围压下的断层滑动行为。采用声发射（AE）和数字图像相关（DIC）捕捉断层滑动的全过程特征，而共聚焦激光扫描显微镜（CLSM）则揭示了断层表面的微观结构变化。采用PFC中的光滑节理模型（SJM）进行离散元建模，研究微裂纹演化和局部应力-应变响应。结果表明，断层卸荷滑移受断面上正应力和剪应力的演化控制，经历4个阶段。在线性稳定阶段，应力场和变形场保持稳定。当围压降至初始值的80% ~ 85%时，进入非线性稳定阶段，排水量稳定。进一步卸荷会导致亚不稳定阶段，其特征是5% - 10%的应力波动、局部位移和增加的高能声发射事件。最后，失稳阶段表现为强应力振荡和快速宏观滑移。能量释放周期随着围压和粗糙度的增加而延长。对于180粒度的断层，周期从10 MPa下的58 s延长到30 MPa下的105 s；在30 MPa下，粗糙度从1000砂砾增加到60砂砾，循环时间从68秒增加到142秒。CLSM和模拟证实，高粗糙度表面集中了凸起处的应力，加剧了损伤，而光滑表面则呈现均匀磨损。围压≥30 MPa，粗糙度≤180磨粒时，变形由弹性向塑性转变，磨损由磨粒向粘粒转变。声发射b值和熵演化（由高状态向低状态过渡）的耦合可以有效地指示滑移阶段。这些发现促进了对深部采煤断层滑动不稳定性的认识，并为深部采煤断层滑动不稳定性的监测和预警提供了指导。

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引用次数: 0

Nonlinear progressive failure mechanism and shear strength model of deeply buried jinping marble under direct shear

IF 7.5 1区工程技术 Q1 ENGINEERING, GEOLOGICAL

International Journal of Rock Mechanics and Mining Sciences

Pub Date : 2025-12-18 DOI: 10.1016/j.ijrmms.2025.106380

Chunfeng Ye , Cunbao Li , Hengjun Chen , Fei Wu , Peng Chu , Heping Xie

A comprehensive understanding of the nonlinear shear behavior of deep rocks is vital for the safe operation and design of deep underground engineering. This study presents a series of direct shear tests on deeply buried Jinping marble, coupled with real-time acoustic emission (AE) monitoring. The results revealed a progressive transition in dominant shear failure mechanisms from dilatant–interlocking to compaction–shear modes with increasing normal stress. Peak and residual shear strength, as well as crack initiation and crack damage stresses, exhibited nonlinear increases with normal stress, albeit with diminishing growth rates. This evolution was accompanied by a shift in failure mode from multicrack propagation to large-scale spalling failure. The AE energy and b-value evolved in four nonlinear failure stages: initiation, stable propagation, accelerated coalescence, and chaotic breakdown. The rise time over amplitude–average frequency (RA–AF) analysis revealed that the distribution of tensile and shear cracks varies nonlinearly and nonmonotonically with normal stress: mixed-mode (tensile–shear) rupture predominates at low-to-moderate stress levels, whereas shear-dominated failure prevails at high-stress levels. A novel nonlinear shear strength model was proposed based on the decoupled evolution of cohesion and friction angle. The model incorporates stage-specific recognition, adaptive response regulation, and boundary-constrained convergence. Compared with the Mohr–Coulomb, bilinear strength, and generalized nonlinear failure criteria, the proposed model demonstrates superior predictive accuracy (R² > 0.99) for both the peak and residual shear strength of Jinping marble. Moreover, it shows promising adaptability and applicability in other weak rocks, such as layered sandstone and ultralow-strength sandstone.

全面了解深部岩石的非线性剪切特性对深部地下工程的安全运行和设计至关重要。结果表明，随着法向应力的增加，主要剪切破坏机制逐渐从膨胀-联锁模式转变为压实-剪切模式。峰值抗剪强度和残余抗剪强度，以及裂纹起裂应力和裂纹损伤应力，随正应力的增加呈非线性增长，尽管增长速率递减。这种演变伴随着失效模式从多架传播到大规模剥落失效的转变。声发射能量和b值分别经历起裂、稳定传播、加速聚并和混沌击穿四个非线性破坏阶段。上升时间比幅均频率（RA-AF）分析表明，拉伸和剪切裂纹的分布随正应力呈非线性和非单调变化：低至中等应力水平下以拉剪混合模式破裂为主，而高应力水平下以剪切为主。基于黏聚力和摩擦角的解耦演化，提出了一种新的非线性抗剪强度模型。该模型结合了阶段识别、自适应反应调节和边界约束收敛。此外，该方法在层状砂岩、超低强度砂岩等弱岩中也具有良好的适应性和适用性。

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引用次数: 0

Predicting rockfall hazard with deep learning: Latent feature extraction from geological layers 基于深度学习的岩崩灾害预测：地质层的潜在特征提取

IF 7.5 1区工程技术 Q1 ENGINEERING, GEOLOGICAL

International Journal of Rock Mechanics and Mining Sciences

Pub Date : 2025-12-17 DOI: 10.1016/j.ijrmms.2025.106379

Guilherme Barros, Klaus Thoeni, Pablo Moscato, Jinsong Huang, Anna Giacomini

This study introduces an innovative and comprehensive Machine Learning (ML) methodology for forecasting rockfall hazards in open-pit mining environments by integrating detailed geological stratigraphy extracted from 3D point clouds with advanced deep learning techniques. Rockfall is the sudden detachment of one or more rock blocks from a steep slope or cliff, followed by free-fall, bouncing, and rolling downslope. In open-pit mining, rockfall poses significant danger to both personnel and machinery. Unlike existing approaches that predominantly rely on basic geometric features and linear regression, this research incorporates geological stratification information into predictive models. A comprehensive synthetic dataset was created using detailed stochastic simulations of rockfall events on slope profiles, which were automatically generated from real-world 3D point clouds including stratigraphic features. A Variational Autoencoder (VAE) was developed to automatically extract latent features that effectively capture the complex relationships between geological structure and slope morphology. A thorough comparison of several regression algorithms, including Linear Regression (LR), K-Nearest Neighbour (KNN), Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGB), demonstrates the superior performance of nonlinear models combined with VAE-derived latent features. The findings indicate that incorporating these latent features significantly enhances prediction accuracy, representing a notable advancement over models based solely on traditional geometric parameters. This pioneering approach provides a reliable solution for accurately estimating key rockfall risk indicators at the base of highwalls, thereby enhancing the reliability and data-driven nature of risk assessments in open-pit mining operations.

该研究引入了一种创新的、全面的机器学习（ML）方法，通过将从3D点云提取的详细地质地层学与先进的深度学习技术相结合，用于预测露天矿开采环境中的落石危险。岩崩是指一个或多个岩石块从陡峭的斜坡或悬崖上突然脱离，随后自由落体、弹跳和滚下斜坡。在露天矿开采中，岩崩对人员和机械都造成了极大的危险。与现有的主要依赖基本几何特征和线性回归的方法不同，该研究将地质分层信息纳入预测模型。通过对斜坡剖面上的岩崩事件进行详细的随机模拟，生成了一个综合的合成数据集，该数据集是根据包括地层特征在内的真实世界的3D点云自动生成的。开发了一种变分自编码器（VAE），用于自动提取潜在特征，有效地捕捉地质构造与边坡形态之间的复杂关系。通过对几种回归算法（包括线性回归（LR）、k近邻（KNN）、支持向量机（SVM）、随机森林（RF）和极限梯度增强（XGB））的全面比较，证明了非线性模型与vae衍生的潜在特征相结合的优越性能。研究结果表明，与仅基于传统几何参数的模型相比，结合这些潜在特征显著提高了预测精度。这种开创性的方法为准确估计高岩壁底部关键岩崩风险指标提供了可靠的解决方案，从而提高了露天矿开采作业风险评估的可靠性和数据驱动性。

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引用次数: 0