Achieving carbon neutrality and large-scale industrial waste utilization requires low-carbon mine backfill materials. This study investigates a strategy to enhance cement-fly ash based composites using CO2 nanobubble water. Normal cement-fly ash based backfill and CO2 nanobubble-modified cement-fly ash based backfill were compared through mechanical and microstructural analyses, including uniaxial compression, mercury intrusion porosimetry, scanning electron microscopy and thermogravimetric analysis. The results demonstrate that CO2 nanobubbles effectively mitigate the strength degradation induced by high fly ash replacement. Compared with normal backfill, the uniaxial compressive strength and elastic modulus of modified samples increased by 6.5–13.4% and 14.8–59.1%, respectively, enabling high-volume fly ash utilization without compromising mechanical integrity. Microstructural analyses reveal that CO2 nanobubble water promotes hydration and in-situ carbonation reactions, leading to the formation of uniformly distributed C-S-H gels and calcium carbonate crystals that refine the pore structure and reduce total porosity by approximately 20%. Thermogravimetric results further confirm that CO2 nanobubble significantly enhance carbonation efficiency, with the maximum carbonation degree reaching 13.07% at a fly ash content of 60%. Balancing performance and cost, the optimal fly ash content is identified within 20–60%, providing a green pathway for mining waste valorization.

Folding and subsequent pinching out are common geological features in geologically active areas. This gives layers a non-uniform thickness, especially for a multilayer slope with a weak interlayer. Thickness non-uniformity is often disregarded in stability analysis to simplify slope models. However, the geometrical variability of rock masses always exists, and the impact is inevitable; therefore, it is not to be discounted. This research systematically established a geometric correlation framework to understand how tapering configurations in weak interlayer influence slope stability in layered rock masses. Analytical and numerical methods are implemented using the RocScience code. Statistical analysis was also performed to assess the significance and correlation of tapering configurations to slope stability conditions. It was found out that Tilting Intensity (ρ≥0.736) and Thickness Gradient (ρ≥0.743) consistently exhibited the strongest (α=0) negative correlation with critical strength reduction factors and slip surface radius, confirming that taper steepness and vertical irregularity are the dominant geometrical destabilizers in non-uniform weak layers. Moreover, stratigraphic unevenness not only exerts a direct destabilizing influence but also modulates the sensitivity of other geometrical parameters, such as the aspect ratio, by a factor of 2 units ΔFS recorded at the highest elevation. The findings of this study carry several practical and scientific implications for slope design, geomechanical modeling, and geological interpretation in complex stratified rock masses.

Curved pipe jacking is a satisfying technique for laying the buried pipeline in trenchless crossing scenarios. Estimation of frictional resistance in curved pipe jacking exhibits a more complex pipe-soil interaction compared with linear drives. Deflection differential equations for curved pipes embedded on a Pasternak foundation are established, and the finite difference method is used for estimating the foundation reaction force and frictional resistance. As verified, the proposed model exhibits good rationality compared to a practical drive. Parametric analysis indicates that small-radius curvature induces a larger foundation deformation, while the easement curvature restricts the constraints influence of pipe boundaries on frictional resistance along the axial direction. Limited pipe diameter weakens the influence range of the foundation reaction force on the normal pipe-soil interaction. The axial force transfer within the shear layer diminishes as the foundation reaction coefficient enlarges, while the integral value of the foundation reaction follows a decrease-then-increase pattern. Moreover, increased shear stiffness enhances the force transfer performance among the soil springs in the shear layer, but declines the normal contact behavior between the pipe and foundation, contributing to an expanding frictional resistance.

Slurry-infiltrated granular composites offer a sustainable strategy for underground backfilling, in which a pre-formed aggregate skeleton is bonded by an infiltrating slurry to reduce binder use. Their mechanical integrity is governed by slurry retention within intergranular voids rather than uniform mixing. However, a quantitative link between fresh-state rheology and both the resulting bonded configuration and hardened mechanical performance remains insufficiently established. This study develops an experimental–theoretical framework linking slurry rheology, retention behavior, and uniaxial compressive response. Slurries with varying rheology were prepared by adjusting polycarboxylate ether dosage, and infiltration tests were performed using coarse gangue aggregates of different sizes. The retained slurry mass () was measured and used to define a structural state descriptor, the initial bonded volume fraction (), to characterize the initial bonded configuration. A constitutive model is formulated by decomposing total strain into elastic and compaction components, while progressive degradation of bonded regions is described using a statistical damage approach. Model parameters are identified independently from distinct segments of the stress–strain curves to ensure identifiability. Validation using independent mixtures demonstrates that the proposed model captures early-stage compaction, elastic stiffness, peak strength, and post-peak softening, with relative errors generally within 15%. Within the present uniaxial material-point scope, slurry retention provides a measurable link between fresh-state rheology and hardened mechanical performance, supporting rapid comparison and preliminary assessment of load-bearing behavior in slurry-infiltrated granular systems.

At the early stage of mine feasibility assessment, decision-making is constrained by high geological uncertainty despite the need for rapid evaluation of economic viability. This study proposes a morphological texture-based classification framework as a screening tool for early-stage mine design. Distinct textural variants within a single ore deposit are classified using field and laboratory data and evaluated across slope stability, excavation energy, and ore grade. A multi-criteria decision analysis (MCDA) approach is applied to quantify trade-offs among these factors. Results show that weakly banded ores, such as deposition type 1 (DT), are easier to excavate but less stable, whereas competent units, such as DT6 and DT4, allow steeper, more stable slopes. The intermediate unit, as in DT5, exhibits higher grades but moderate constraints. MCDA ranking identifies DT6 as the most balanced unit. The framework demonstrates that morphological texture can effectively link geology with engineering and economic considerations, providing early-stage guidance for slope design and prioritisation under uncertainty.

The mechanical performance of cemented backfill in deep engineering environments is jointly governed by curing-induced microstructural evolution and confinement-controlled deformation processes, yet their respective roles and interactions remain insufficiently understood. In this study, the curing- and confinement-dependent mechanical behavior of loess-slag backfill was investigated through triaxial compression tests, acoustic emission (AE) monitoring, mercury intrusion porosimetry (MIP), and a fractional-order constitutive interpretation focused on the stable hardening regime. Results indicate that curing primarily enhances intrinsic stiffness by refining pore network topology. This effect is quantitatively captured by the monotonic increase in the intactstate pore fractal dimension (Df0) and its strong non-linear correlation with the generalized stiffness coefficient (K). In contrast, confinement regulates the damage evolution pathway. The minimum AE b-value (bmin) correlates strongly with the fractional order (a), revealing a fundamental transition from localized brittle cracking to distributed ductile deformation. Furthermore, post-peak softening behavior is shown to be closely linked to damage-induced fractal reorganization, with a strong monotonic relationship between the softening index B and the fractal-dimension increment Delta Df, highlighting the role of fractal preservation in maintaining post-peak stability. Overall, this study provides a fractal-informed constitutive interpretation that clarifies how curing and confinement jointly control stiffness development, deformation mode, and failure stability of loess-slag backfill, offering insights for the design and optimization of cemented backfill systems under highstress conditions.

While conventional numerical studies often treat excavated stopes as empty voids or as backfilled, few investigations have simulated the post-mining void as a weak granular caved rock material that evolves naturally from a hanging wall failure. This study addresses this gap by modeling the caved rock progressively, which makes the excavation representation more realistic for sublevel caving operations. This study introduces stope stability for the Zarmitan gold mine in Uzbekistan, where mining occurs at about a 500 m depth in a narrow quartz vein. A hybrid approach combining empirical and numerical methods was adopted. The Mathews stability graph method provided initial design guidance, while three-dimensional FLAC3D numerical modeling was used to simulate the mining sequence with explicit representation of caved rock behavior. A various study was conducted, which included the effects of stress ratio, stope length along strike, and pillar thickness on overall stability. The obtained results show that the stress ratio is the dominant factor controlling stope behavior. Stope length significantly affects failure extent, with shorter stopes showing better performance under similar conditions. Pillar thickness was found to improve stability and reduce tensile stresses in critical areas, though in all cases, hanging wall support remains essential. The numerical results confirm empirical predictions while providing quantitative insights into stress distributions and failure mechanisms not captured by empirical methods alone. These results provide mine operators with quantitative, site-specific design criteria, most notably that, under the measured high horizontal stress, limiting stope length to 40 m and increasing pillar thickness to 8 m substantially improves hanging wall stability, which demonstrates how a hybrid empirical-numerical methodology can directly support safer and more economic extraction in deep, narrow-vein operations.

Underground coal mining in inclined seams presents complex geomechanical challenges that differ significantly from horizontal strata, particularly regarding surface subsidence behavior. This study investigates the influence of seam inclination and panel geometry on the morphology of subsidence troughs using a 3D numerical modeling approach (FLAC3D). The model configuration is grounded in the specific operational conditions of a coal mine in East Kalimantan, Indonesia, utilizing a 16 degrees seam inclination and site-specific lithology. A parametric study was conducted to evaluate the sensitivity of subsidence to panel width, depth, and height. The results reveal a distinct asymmetry in the subsidence profile driven by the tangential component of gravity along the bedding planes. Specifically, the locus of maximum subsidence shifts noticeably toward the down-dip direction, while the subsidence profile exhibits a steeper gradient on the up-dip side. Pearson correlation analysis quantifies the influence of geometric parameters, identifying extraction height as the governing variable (rho = 0.671). Panel width demonstrates a moderate positive correlation (rho = 0.395), whereas panel depth exhibits a weak inverse relationship (rho =-0.141), functioning as a minor attenuating factor. The findings demonstrate that traditional symmetrical monitoring designs are insufficient for inclined seams. Consequently, this research suggests that subsidence management strategies in the Indonesian coal basin and similar geological settings must account for the down-dip shift of the maximum impact zone to ensure effective risk mitigation.

Longwall coal mining in East Kalimantan, Indonesia, causes significant surface subsidence, yet specific, data-driven characterisations of this process remain limited. This study offers a detailed spatial and temporal analysis of surface subsidence above a single longwall panel using total station monitoring data collected from February 2021 to December 2022. The analysis identified a maximum final subsidence of 1.336 m. The development of subsidence over time followed four distinct phases: initial, acceleration, deceleration, and stabilisation, with time delays of up to 16 months observed between the passage of the panel and the end of settlement. This behaviour is attributed to subcritical extraction conditions. The subsidence trough was asymmetrical, with its shape strongly influenced by the 12° dip of the coal seam. A comparison with the empirical UK National Coal Board (NCB) method revealed that the observed maximum subsidence was more than twice the predicted value of 0.6 m. These findings highlight the limitations of applying generic empirical models to Indonesia’s unique geological conditions and emphasise the need to develop locally calibrated predictive tools for effective and safe subsidence management.

Oversized rock fragments (boulders) produced during bench blasting adversely affect the efficiency of mining downstream processes such as loading, hauling, and crushing, thus leading to regularly requiring costly secondary breakage and the use of mechanized rock breakers. This study presents a probabilistic framework for forecasting boulder size in surface mining operations by employing Gaussian Process Regression (GPR), benchmarked against the Kuznetsov-Cunningham-Ouchterlony (KCO) empirical fragmentation model and a Multivariate Regression Analysis (MVRA) equation. The research study has analyzed blasting datasets, comprising Geological Strength Index (GSI), number of holes (NH), hole depth (HD), maximum charge per delay (MCPD), total explosive mass (TEM), and boulder size determined by Split-Desktop image analysis. Eight Gaussian Process Regression kernels-squared exponential, rational quadratic, matern with nu = 3/2, and matern with nu = 5/2, both with and without automatic relevance determination (ARD)-were assessed. The GPR model with the ARD matern 3/2 kernel attained superior validation performance of R2 = 0.9016 and RMSE = 4.2482, outperforming the KCO and MVRA models, which displayed significant prediction errors for boulder size. In addition, the sensitivity analysis results demonstrated that GSI and HD were the most influential parameters on boulder size, followed by NH, MCPD, and TEM, accordingly. The findings indicate that GPR, especially when employing ARD matern kernels, precisely estimates the boulder size, and thus can serve as a viable method for optimizing blast design and facilitate efficient boulder management in surface mining operations.

Stope stability is a critical factor in underground mining, directly influencing safety, productivity, and overall mining efficiency. Traditional stope design methods often employ uniform stope lengths, disregarding geotechnical variability and thereby increasing the risk of instability or suboptimal dimensions. This study introduces an automated stability analysis approach that iteratively evaluates multiple stope dimension scenarios based on the Modified Stability Number (N’) to identify the optimum stable configuration. By conducting detailed stability assessments for each stope wall, the method provides a more accurate representation of geotechnical conditions compared to the conventional methods with uniform stope length. The case study demonstrates that this approach effectively reduces the total number of stopes while maintaining geotechnical stability, in contrast to conventional methods where 14%–40% of stopes exhibit instability. Furthermore, the optimization method achieves a balanced outcome between dilution control and operational efficiency resulted in lower stope production cost. The optimized configurations generated by the proposed method deliver the lowest total production cost, with estimated savings of approximately USD 1.6–2.4 million compared to conventional designs. These findings confirm that the optimization framework not only enhances geotechnical stability but also provides a demonstrable economic advantage, underscoring the importance of integrating geotechnical variability into stope design.

High-volume fly ash (HVFA) binders are widely utilized as a mature method for cemented paste backfill in green mining, yet their performance remains highly sensitive to mix design. The fundamental coupling mechanism between the water-to-binder mass ratio (W/B) and sodium lignosulfonate (SL) content in pozzolan-rich HVFA systems remains insufficiently understood. In this study, HVFA pastes with varying SL contents (0–0.9wt

Blast-induced ground vibrations present substantial safety and environmental hazards in surface mining operations. This study proposes and evaluates the Sparrow Search Algorithm-optimized ANN (SSA-ANN) against artificial neural network (ANN), Genetic Algorithm-optimized ANN (GA-ANN), and empirical formula (USBM) to estimate peak particle velocity (PPV). In addition, the input parameters include key blasting design parameters and rock mass features (GSI and UCS). The SSA-ANN demonstrated superior prediction accuracy, attaining an average R2 of 0.51 using bootstrap validation, surpassing GA-ANN (0.41) and standard ANN (0.26). Furthermore, the incorporation of GSI enhanced the model’s geotechnical sensitivity. These results illustrate that the application of SSA-ANN alongside comprehensive rock mass characteristics can substantially decrease uncertainty in PPV prediction, therefore enhancing safety within the blast area and improving vibration control methods in blasting operations.

Abstract. In addition to causing severe damage to human health and mechanical equipment, mineral dust particles (MDPs) also affect the rate at which glaciers melt. Although the acceleration of glacier melting by MDPs has attracted attention, there is limited understanding of the main controlling variables affected by MDPs that change the melting rate, and the mathematical relationships between each variable and the rate of melting remain to be fully elucidated. To address this problem, we first reconstructed the ablation environment to simulate changes in the rate of glacier melting under the influence of MDPs. The environment was analyzed through both physical and numerical experiments, and the response of glacier melting to multiple particles and individual particles on both macroscopic and microscopic levels was examined. Subsequently, based on thermodynamic laws, we theoretically derived a formula to calculate the increase in the rate of glacier melting attributable to MDPs. Through mutual validation of experiments and theory, we found that MDP coverage on the glacier surface increases the energy absorbed by the glacier, thereby resulting in an increased rate of melting, with an uplift of 10 %–40 %. The increase in the rate of melting is controlled primarily by four variables: particle number, particle diameter, irradiance, and particle surface albedo. Particle number, irradiance, and particle surface albedo each exhibit a linear relationship with the rate of increase in meltwater production, whereas particle diameter shows an exponential (quadratic) relationship. Our findings elucidate the mathematical relationship between MDPs and the rate of glacier melting, thereby providing scientific reference for glacier protection and accurate prediction of glacier melting rate.

During pipe-roof construction using pipe-jacking technology, lubricants are injected into the tail void to reduce pipe–soil friction and minimize soil loss. However, research on ground settlement caused by multiple adjacent pipe jackings remains limited, and the influence of lubricant Young’s modulus on ground settlement control is not clear. To address these gaps, this study conducts a comprehensive investigation using a Fast Lagrangian Analysis of Continua in 3 Dimensions (FLAC3D). Initially, the research model is validated against a pipe-roof case in Japan. Subsequently, ground response characteristics are simulated under lubricants with different Young’s moduli, considering four burial depths, two pipe-roof arrangements (“gate-shaped” and “horseshoe-shaped”), and two tail voids. The results indicate that low-stiffness lubricants mobilize greater surface settlement, while increasing the lubricant Young’s modulus more markedly optimizes the interaction among adjacent pipelines, thereby greatly alleviating the settlement. Nonetheless, the control effectiveness of lubricant on the settlement is influenced by other factors. Increasing burial depths and tail voids weaken the lubricant’s capacity to mitigate surface settlement. In contrast, the horseshoe-type arrangement is more conducive to the lubricant’s control effect on surface settlement than the gate-type system. Moreover, under these three cases, an increase in the lubricant Young’s modulus can more substantially reduce surface settlement. These findings provide valuable insights for controlling ground settlement during pipe-roof construction.

The effect of rebar in reinforced concrete on blasting demolition was clarified through laboratory tests. In this study, blasting tests were conducted using concrete plate specimens containing iron bar, and the strain/stress state around the rebar and crack propagation were examined. The strain generated in the specimen after ignition of the explosive was calculated by the digital image correlation method. This method successfully visualized cracks that could not be seen visually and clarified stress wave propagation and crack propagation behavior around the rebar before and after crack initiation. The results showed that the presence of rebar in the propagation path of a stress wave causes more regular cracking than when no rebar is present due to reflection and diffraction of the stress wave.

A case study of designing a waste dump was conducted for the iron mine located in the Bulacan area, Philippines. Iron ore mines generate a relatively high amount of waste, and at the study mine, the constrained waste dumping area of 3 hectares necessitated a higher dump design, leading to potential stability issues. Additionally, the waste dump is projected to be situated on an inclined surface; subsequently, there is a concern about dump stability. Therefore, this study aims to find the optimum waste dump design by assessing its stability, and a geometrical configuration was conducted to optimize the bench parameters. Numerical modeling of the finite difference method (FDM) was used to estimate the distribution of the Factor of Safety by simulating several models. Models with steeper base inclinations (>12°) demonstrate progressive instability, as demonstrated by pre-assessment. The statistical analysis results show that the total model simulations with a 45-degree slope angle have a significantly high probability of failure of 38.2%. Whereas models with 35-degree and 40-degree slope angles have probabilities of failure calculated as 0.3% and 6.5%, respectively. Therefore, results suggest that the general slope angle should be kept at 40 degrees or less. Moreover, the results show that an average of 0.02 points drops in FoS for each 2.5 m of increment in dump height. Regarding geometrical setup, four benches with 7.5 m of berm would be preferable for the waste dump design of the case study. Overall, the effect of an inclined surface as a base was discussed, the effect of a gradual increase in dump height was outlined, and the significance of the dump slope angle on dump design was highlighted.

Blast-induced airblast poses a significant environmental and operational issue for surface mining, affecting safety, regulatory adherence, and the well-being of surrounding communities. Despite advancements in machine learning methods for predicting airblast, present studies neglect essential geomechanical characteristics, specifically rock mass strength (RMS), which is vital for energy transmission and pressure-wave attenuation. This paper presents a capuchin search algorithm-optimized multilayer perceptron (CapSA-MLP) that incorporates RMS, hole depth (HD), maximum charge per delay (MCPD), monitoring distance (D), total explosive mass (TEM), and number of holes (NH). Blast datasets from a granite quarry were utilized to train and test the model in comparison to benchmark approaches, such as particle swarm optimized artificial neural network (PSO-ANN), multivariate regression analysis (MVRA), and the United States Bureau of Mines (USBM) equation. CapSA-MLP outperformed PSO-ANN (RMSE = 1.120, R2 = 0.904 compared to RMSE = 1.284, R2 = 0.846), whereas MVRA and USBM exhibited lower accuracy. Sensitivity analysis indicated RMS as the main input factor. This study is the first to use CapSA-MLP with RMS for airblast prediction. The findings illustrate the significance of metaheuristic optimization in developing adaptable, generalizable models for various rock types, thereby improving blast design and environmental management in mining activities.

A barrier pillar between the surface and underground mining sections provides a critical buffer zone in the transition from the boxcut highwall to underground sections by isolating stress fields from underground sections and preventing them from affecting the boxcut highwall slope. In this study, an empirical scaled span method and Rocscience RS2 software were used to conduct parametric studies on key parameters for designing barrier pillars and analyzing the room and pillar design for a planned underground mine on the Great Dyke, Zimbabwe. The approach included analyzing the effect of barrier pillar width, assuming a 10° dipping angle of the orebody, with room and pillar dimensions of 7 m and 6 m, respectively. The impact on boxcut slope stability and the roof of the first stope was monitored. The stability of the barrier pillar was analyzed for varying widths (6 m, 10 m, 20 m, 30 m, and 40 m) and orebody dipping angles (0°, 10°, 20°, 30°, and 40°). The effect of deteriorated rock mass conditions, represented by Geological Strength Index (GSI) values from 30 to 50, was assessed. The optimum room and pillar design was evaluated against the planned 6 m pillar sizes. This comprehensive study aims to support the integrity and longevity of the critical structures of the mining operation.