Search Results (228)

Granite residual soil (GRS) is highly susceptible to water-induced softening, posing significant risks of slope instability and collapse. Conventional impermeable grouting often exacerbates these hazards by blocking groundwater drainage. This study investigates the efficacy of a permeable water-reactive polyurethane (PWPU) in stabilizing GRS, aiming to resolve the conflict between mechanical reinforcement and hydraulic conductivity. Uniaxial compression tests were conducted on specimens with varying initial water contents (5%, 10%, and 15%) and PWPU contents (5%, 10%, and 15%). To reveal the multi-scale failure mechanism, synchronous acoustic emission (AE) monitoring and digital image correlation (DIC) were employed, complemented by scanning electron microscopy (SEM) for microstructural characterization. Results indicate that PWPU treatment significantly enhances soil ductility, shifting the failure mode from brittle fracturing to strain-hardening, particularly at higher moisture levels where failure strains exceeded 30%. This enhancement is attributed to the formation of a flexible polymer network that acts as a micro-reinforcement system to restrict particle sliding and dissipate strain energy. An optimal PWPU content of 10% yielded a maximum compressive strength of 4.5 MPa, while failure strain increased linearly with polymer dosage. SEM analysis confirmed the formation of a porous, reticulated polymer network that effectively bonds soil particles while preserving permeability. The synchronous monitoring quantitatively bridged the gap between internal micro-crack evolution and macroscopic strain localization, with AE analysis revealing that tensile cracking accounted for 79.17% to 96.35% of the total failure events. Full article

As uniaxial compressive strength (UCS) of rock material is influenced by petrographic characteristics, special emphasis is given to the visual assessment and determination of rock properties. Visual determination of properties such as lithology, fabric, defects and porosity were conducted on six petrographically different limestone varieties from Istria, Croatia. In addition to the macroscopic and microscopical determination of petrographic characteristics, measurements of ultrasound propagation velocity through samples were also conducted. According to the gained results of visual macro and micro assessment and ultrasound propagation, velocity estimation of uniaxial compressive strength was performed. Using predicted values of UCS, classification of samples according to different classifications was conducted where four out of six varieties of limestone were classified correctly. Based on the achieved results, the method has proven successful for rocks, which have uniaxial compressive strength over 100 MPa. Full article

In this study, linear and nonlinear parametric models (M1–M6) were jointly evaluated alongside machine learning (ML)-based approaches to achieve reliable and interpretable prediction of the penetration rate (ROP) of tunnel boring machines (TBMs). The analyses incorporate key geomechanical and structural variables, including the brittleness index (BI), uniaxial compressive strength (UCS), mean spacing of weakness planes (DPW), the angle between the tunnel axis and weakness planes (α), and Brazilian tensile strength (BTS). The coefficients of the parametric models were optimized using the Differential Evolution (DE) algorithm. Variable effects were systematically examined through Jacobian-based elasticity analysis under both original and standardized data scenarios. The results indicate that the M6 model, which explicitly incorporates interaction terms, delivers superior predictive accuracy and a more balanced, physically meaningful representation of variable contributions compared to widely used parametric formulations reported in the literature. While the dominant influence of BI and UCS on ROP is consistently preserved across all models, the indirect contributions of variables such as DPW and BTS are more clearly revealed in M6 owing to its interaction-based structure. Model performance improves systematically with increasing complexity, with the coefficient of determination (R²) rising from 0.62 for M1 to 0.69 for M6. Relative to the linear model, M6 achieves a 9.07% reduction in RMSE and a 10.48% increase in R², while providing additional improvements of 2.47% in RMSE and 2.37% in R² compared with the closest competing model. ML-based variable importance analyses are largely consistent with the parametric findings, highlighting BI and α in tree-based models, and UCS and α in SVM and GAM frameworks. Notably, the GAM exhibits the highest predictive performance under both data scenarios. Overall, the integrated use of parametric and ML approaches establishes a robust hybrid modeling framework that enables highly accurate and engineering-interpretable prediction of TBM penetration rate. Full article

Reliable models for predicting the uniaxial compressive strength (UCS) of rocks are crucial for mining operations and rock engineering design. Empirical methods, including statistical methods, are often faced with many limitations when generalizing in a wide range of lithological types. To address this limitation, this study investigates the capability of grey wolf optimization (GWO)-optimized ensemble machine learning models, including decision tree (DT), extreme gradient boosting (XGBoost), and adaptive boosting (AdaBoost) for predicting UCS using a small dataset of easily measurable and non-destructive rock index properties. The study’s objective is to evaluate whether metaheuristic-based hyperparameter optimization can enhance model robustness and generalization performance under small-sample conditions. A unified experimental framework incorporating GWO-based optimization, three-fold cross-validation, sensitivity analysis, and multiple statistical performance indicators was implemented. The findings of this study confirm that although the GWO-XGBoost model achieves the highest training accuracy, it exhibits signs of mild overfitting. In contrast, the GWO-AdaBoost model outpaced with significant improvement in terms of coefficient of determination (R²) = 0.993, root mean square error (RMSE) = 2.2830, mean absolute error (MAE) = 1.6853, and mean absolute percentage error (MAPE) = 4.6974. Therefore, the GWO-AdaBoost has proven to be the most effective in terms of its prediction potential of UCS, with significant potential for adaptation due to its effectively learned parameters. From a theoretical perspective, this study highlights the non-equivalence between training accuracy and predictive reliability in UCS modeling. Practically, the findings support the use of GWO-AdaBoost as a reliable decision-support tool for preliminary rock strength assessment in mining and geotechnical engineering, particularly when comprehensive laboratory testing is not feasible. Full article

With the increasing requirements for “Green Mine” construction, Cemented Tailings Backfill (CTB) has emerged as the preferred strategy for solid waste management and ground pressure control in underground metal mines. However, full tailings, characterized by wide particle size distribution and high fine-grained content, exhibit complex physicochemical properties that lead to significant non-linear behavior in slurry rheology and strength evolution, posing challenges for accurate prediction using traditional empirical formulas. Addressing the issues of significant strength fluctuations and difficulties in mix proportion optimization in a specific lead–zinc mine, this study systematically conducted physicochemical characterizations, slurry sedimentation and transport performance evaluations, and mechanical strength tests. Through multi-factor coupling experiments, the synergistic effects of cement type, cement-to-tailings (c/t) ratio, slurry concentration, and curing age on backfill performance were elucidated. Quantitative results indicate that solids mass concentration is the critical factor determining transportability. Concentrations exceeding 68% effectively mitigate segregation and stratification during the filling process while maintaining optimal fluidity. Regarding mechanical properties, the c/t ratio and concentration show a significant positive correlation with Uniaxial Compressive Strength (UCS). For instance, with a 74% concentration and 1:4 c/t ratio, the 3-day strength increased by 1.4 times compared to the 68% concentration, with this increment expanding to 2.0 times by 28 days. Furthermore, a comparative analysis of four cement types revealed that 42.5# cement offers superior techno-economic indicators in terms of reducing binder consumption and enhancing early-age strength. This research not only establishes an optimized mix proportion scheme tailored to the operational requirements of the lead–zinc mine but also provides a quantitative scientific basis and theoretical framework for the material design and safe production of CTB systems incorporating high fine-grained full tailings. Full article

The Cerchar Abrasivity Index (CAI) is essential for predicting tool wear in mechanized tunneling and mining, but direct measurement requires time-consuming laboratory procedures. We developed a data-driven framework to estimate CAI from standard geomechanical and mineralogical properties using 193 rock samples covering igneous, metamorphic, and sedimentary lithologies. After evaluating 278 feature combinations with multicollinearity constraints (VIF < 10.0), we identified an optimal four-variable subset: brittleness index B₁, density, Equivalent Quartz Content (EQC), and Uniaxial Compressive Strength (UCS), with rock type indicators. CatBoost achieved the best performance (Test R² = 0.907, RMSE = 0.420), and SHAP analysis confirmed that density and EQC are primary drivers of abrasivity. Additionally, symbolic regression derived an explicit formula using only three variables (density, EQC, B₁) without rock type classification (Test R² = 0.720). The proposed framework offers a practical approach for assessing rock abrasivity at early project stages. Full article

Fibres can markedly enhance the uniaxial compressive strength (UCS) of cemented paste backfill (CPB). However, previous studies have mainly verified the effectiveness of polypropylene and straw fibres in improving the UCS of CPB experimentally, while systematic multi-factor evaluation remains limited. In this study, laboratory experiments were conducted on polypropylene- and straw fibre-reinforced CPB to construct a reliable dataset. The factors influencing the intensity of uniaxial compressive strength were divided into four aspects (mixture proportions, physical properties of the cement–tailings mixture, chemical characteristics of tailings, and fibre properties), and four intelligent models were developed for effectiveness analysis and UCS prediction. SHapley Additive exPlanations (SHAP) were employed to quantify the contributions of individual features, and the findings were experimentally validated. The GWO–LGBM model outperformed the SVR, ANN, and LGBM models, achieving R² = 0.907, RMSE = 0.78, MAE = 0.515, and MAPE = 0.157 for the training set, and R² = 0.949, RMSE = 0.627, MAE = 0.38, and MAPE = 0.115 for the testing set, respectively. Feature analysis reveals that mixture proportions contribute the most to UCS, followed by the tailings’ physical properties, the fibre properties, and the tailings’ chemical characteristics. This study found that cement content and tailings gradation control CPB structural compactness and fibres enhance bonding between hydration products and tailings aggregates, while the chemical composition of the tailings plays an inert role, functioning mainly as an aggregate. Full article

Magnesite tailings are by-products of magnesite mining, yet their utilization rate remains extremely low. Although previous studies have explored their basic physical properties and potential use in cementitious or geotechnical materials, research on cement-stabilized magnesite tailings-particularly regarding their mechanical behavior, engineering applicability, and microstructural evolution-remains limited. Key scientific gaps include the lack of systematic evaluation of their compaction characteristics, strength development, stiffness evolution, and bearing capacity, as well as insufficient understanding of the stabilization mechanisms governing their performance. Addressing these gaps is essential for assessing their feasibility as road construction materials. In this study, magnesite tailings were selected as the primary raw material and mixed with ordinary Portland cement to prepare mixtures for evaluating their suitability as highway subgrade fillers. The compaction characteristics, unconfined compressive strength (UCS), ultrasonic pulse velocity (UPV), and California Bearing Ratio (CBR) of the mixtures were systematically examined. Furthermore, the evolution of composition and stabilization mechanisms of the mixtures was analyzed using X-ray diffraction, scanning electron microscopy, and thermogravimetric analysis. The results show that cement incorporation effectively improves the poor particle gradation of magnesite tailings, leading to a denser and more homogeneous structure. Adding 7% cement increases the maximum dry density and optimum moisture content by 3.7% and 5.1%, respectively. The unconfined compressive strength rises by 100.9–126.3% within 3–28 days, and the maximum uniaxial stress is 119.6% higher than that of the 1% cement mixture. These improvements demonstrate the potential of cement-stabilized magnesite tailings as a sustainable subgrade material and provide insight into their microstructural and mechanical behavior. Full article

To address the problem of wellbore instability in the development of deep coalbed methane reservoirs in Daniudi gas field, this study takes the coal seam cores from Member 1 of the Taiyuan Formation at a depth of approximately 2880 m as the research object. Through CT scanning, scanning electron microscopy (SEM), mineralogical analysis, laboratory mechanical tests, and drilling fluid interaction experiments, the study investigated the coal seam fabric characteristics, mechanical response, anisotropy, and the interaction between drilling fluids and the formation. Based on the double-weak-plane criterion, a wellbore collapse prediction model was established, and instability risk assessment under multi-factor coupling conditions was carried out. Experimental and computational results indicate that the deep coal seam exhibits significant heterogeneity in fabric structure, the clay minerals show low swelling potential, and the bright coal and semi-bright coal are prone to instability due to their dual pore structures. The average uniaxial compressive strength (UCS) of the coal cores is 16.3 MPa, which is weaker than that of the roof, floor, and dirt band. The coal also exhibits anisotropy, with the lowest strength occurring when the loading direction forms an angle of 30–60° with the weak planes, corresponding to 67.5% of the intrinsic compressive strength. Immersion in drilling fluid causes the coal rock strength to decay in a pattern of “rapid decline in the initial stage—gradual decrease in the middle stage—stabilization in the later stage.” After 24 h, the strength is only 55–65% of that in the dry state. Due to its excellent plugging and inhibition performance, HX-Coalmud drilling fluid delays strength loss more effectively than the strongly inhibitive composite salt drilling fluid. The wellbore instability risk assessment indicates that as the drilling time is extended, the collapse pressure rises significantly. After 7 and 20 days of contact between the wellbore and drilling fluid, the equivalent collapse pressure density increases by 0.08–0.15 g/cm³ and 0.13–0.20 g/cm³, respectively. Therefore, homogeneous isotropic models tend to underestimate the risk of wellbore collapse. The findings can provide theoretical and technical support for the safe drilling of deep coalbed methane in Daniudi gas field. Full article

Cemented Paste Backfill (CPB) is a technique that utilizes mine tailings, mining-process water, and a binder, typically Ordinary Portland Cement (OPC), to backfill the opening created in underground mining. However, the use of cement in CPB increases operational costs and has adverse environmental effects. To mitigate these effects, eco-friendly natural pozzolan can be used as a partial replacement for OPC, thereby reducing its consumption and environmental impact. The volcanic region of western Saudi Arabia contains extensive deposits of Saudi natural pozzolan (SNP), which is a promising candidate for this purpose. This study evaluates the mechanical performance of CPB under four scenarios: a control mixture (CTRL), a mixture with untreated SNP (UT), and mixtures with activated SNP, specifically heat-treated (HT) and mechanically treated (MT). Each scenario was tested at replacement levels of 5%, 10%, 15%, and 20% of OPC. The performance was assessed using Uniaxial Compressive Strength (UCS) with Elastic Modulus (E), Ultrasonic Pulse Velocity (UPV), and Indirect Tensile Strength (ITS/Brazilian) tests. The results indicate that the HT scenario at a 5% replacement level delivered the highest performance, slightly outperforming the MT scenario. Both activated scenarios (HT and MT) significantly surpassed the untreated mixture (UT). Overall, the HT scenario proved to be the most effective among all CPB mixtures tested. XRD diffractogram analysis supported HT as the material with the highest strength performance due to the occurrence of more strength phases than other CPB materials, including Alite, Quartz, and Calcite. While UCS and UPV showed a positive correlation across all CPB materials, the relationship between UPV and the modulus of elasticity (E) demonstrated a low correlation. The findings suggest that using activated SNP materials can enhance CPB sustainability by lowering cement demand, stabilizing operating costs, and reducing environmental impacts. Full article

In plateau and high-altitude areas, freeze-thaw cycles often alter the uniaxial compressive strength (UCS) of rock, thereby impacting the stability of geotechnical engineering. Acquiring rock samples in these areas for UCS testing is often time-consuming and labor-intensive. This study developed a hybrid model based on the XGBoost algorithm to predict the UCS of rock under freeze-thaw conditions. First, a database was created containing longitudinal wave velocity (Vp), rock porosity (P), rock density (D), freezing temperature (T), number of freeze-thaw cycles (FTCs), and UCS. Four swarm intelligence optimization algorithms—artificial bee colony, Newton–Raphson, particle swarm optimization, and dung beetle optimization—were used to optimize the maximum iterations, depth, and learning rate of the XGBoost model, thereby enhancing model accuracy and developing four hybrid models. The four hybrid models were compared to a single XGBoost model and a random forest (RF) model to evaluate overall performance, and the optimal model was selected. The results demonstrate that all hybrid models outperform the single models. The XGBoost model optimized by the sparrow algorithm (R² = 0.94, RMSE = 10.10, MAPE = 0.095, MAE = 7.22) performed best in predicting UCS. SHapley Additive exPlanations (SHAP) were used to assess the marginal contribution of each input variable to the UCS prediction of freeze-thawed rock. This study is expected to provide a reference for predicting the UCS of freeze-thawed rock using machine learning. Full article

Environmental stressors, such as freeze–thaw (F–T) cycling and acid rain, affect the durability of carbonate rocks used in engineering and cultural heritage structures. This study investigates the mechanical degradation and strain evolution of Carrara marble subjected to 10 F–T cycles and immersion in a simulated sulfuric acid solution (pH 5) for 3, 7, and 28 days. The mechanical strength of the samples was tested under uniaxial compression using a displacement-controlled loading rate, while full-field deformation and fracture evolution were analyzed with Digital Image Correlation (DIC). Results show that F–T cycling led to a substantial reduction in uniaxial compressive strength (UCS) and a very large decrease in tangent Young’s modulus. Acid exposure also caused progressive degradation, with both UCS and stiffness continuing to decline as exposure time increased, reaching their greatest reduction at the longest treatment duration. Additionally, DIC strain maps revealed a change in deformation response as a function of the treatment. The findings provide the integrated assessment of Carrara marble mechanical response under both F–T and acid weathering, linking bulk strength loss with changes in strain localization behavior, highlighting the vulnerability of marble to environmental stressors, and providing mechanical insights relevant to infrastructure resilience and heritage conservation. Full article

This study examines the influence of tectonically induced mineralogical and microfabric changes on the strength of different rocks within the Hanzel Fault Damage Zone (FDZ) in the Tethyan Himalayas, Pakistan. Integrating field observations, petrographic analysis, and laboratory experiments (uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), ultrasonic pulse-wave velocity (UPV), and porosity), this study systematically characterizes the spatial variations in intact rock strength across horizontal distance from the fault core to the outer limit of the FDZ. Seven rock units—granites (biotite granite, leucogranite schist, granodiorite schist, and diorite) and amphibolites (foliated amphibolite, amphibolite, and plagioclase amphibolite)—were sampled at varying distances (−500 to +4035 m) from the fault core. Results reveal that proximity to the fault core correlates with significant strength reductions (40%–70%): granitic rocks exhibit lower UCS (41–59 MPa) and BTS (4.8–6.7 MPa) compared to distal amphibolites and diorites UCS (75–107 MPa) and BTS (10–13.67 MPa). Petrographic analysis identifies key factors that reduce strength, including high mica content (up to 33%), pervasive micro-fracturing, S-C fabrics, and mineral alteration. These features increase porosity (up to 1.21%) and reduce UPV (2867–3315 m/s) in fault-proximal rocks. Moderate inverse relationships (R² = 0.68–0.72) between mica percentage and UCS/UPV confirm phyllosilicates as primary strength controls. The spatial variation in rock strength is attributed to ductile–brittle deformation processes, with foliated or schistose textures increasing in proximity to the fault core. This study demonstrates that tectonic processes significantly influence the mineralogy and microfabric within FDZs, leading to variations in rock strength with direct implications for stability in tectonically active regions. Full article

Focusing on underground reservoir coal pillar dams subjected to long-term water immersion, this study employed a self-developed non-destructive water saturation apparatus to prepare monolithic and composite coal–rock specimens with varying moisture conditions. Through uniaxial compression tests combined with acoustic emission (AE) monitoring technology, the mechanical failure characteristics and energy dissipation behavior of these specimens were systematically investigated. The results indicated that both the UCS and elastic modulus (E) of the single-rock specimens decreased with increasing water content. Conversely, the mechanical properties of the composite specimens were significantly influenced by the properties and water saturation state of the rock components within the composite. When the rocks within the composite specimens share identical moisture conditions, higher rock strength correlates with greater specimen strength and strain. Under identical lithological conditions, the peak stress (σ_c), peak strain (ε_c), and elastic modulus (E) of the composite specimens decreased with increasing rock moisture content, which exhibited reductions of 45%, 21.8%, and 13.5% in σ_c, ε_c, and E, respectively, under saturated conditions. Acoustic emission (AE) monitoring data revealed that AE events in coal–rock composite specimens under uniaxial loading exhibited distinct spatial distribution patterns. Furthermore, as the rock moisture content increased, the ultimate failure mode of the composite specimen progressively shifted from shear failure within the coal matrix toward tensile failure of the composite as a whole. An analysis of the energy characteristics of coal–rock composite specimens under uniaxial compression revealed that rock properties and moisture content significantly influence energy absorption and conversion during loading. With increasing rock moisture content, the total energy, elastic strain energy, and dissipated energy at the peak load exhibited decreasing trends, reflecting the weakening effect of water on energy dissipation in coal–rock composites. This study systematically investigated the instability mechanisms of coal–rock composites from three perspectives—mechanical properties, failure modes, and energy dissipation—thereby providing valuable insights for evaluating the long-term stability of underground reservoir coal pillar dams subjected to prolonged water immersion. Full article

This study systematically investigates the mechanical behavior and failure mechanisms of cemented tailings backfill (CTB) prepared from classified and unclassified tailings across cement-to-tailings (C/T) ratios of 1:8, 1:6, and 1:4 and slurry concentrations of 60%, 65%, and 70%. Specimens were evaluated by uniaxial compression (UCS) tests, failure mode observation, and SEM. The results show that increasing C/T and concentration markedly enhances compressive strength: the maximum 28-day UCS reached 5.38 MPa under unclassified tailings, C/T = 1:4, 70%. Moreover, unclassified tailings exhibited a later-age strength gain of 244.9%, far exceeding the 58.5% observed for classified tailings. Failure modes evolve from brittle splitting to shear-dominated behavior as mixes densify, reflecting a transition from near-symmetric early-age stress/microstructural fields to asymmetric localized failure (symmetry breaking). SEM reveals that higher binder ratios and concentrations promote C-(A)-S-H-dominated gel formation, improved ITZ continuity, and reduced apparent porosity, thereby restraining microcrack initiation and coalescence. These findings elucidate the micro-to-macro mechanisms governing CTB strength and failure and provide field-relevant guidance for mix optimization and safe, efficient underground backfilling. Full article