Search Results (80)

Epoxy–granite (EG) composites, comprising granite quarry waste and low-cost epoxy, present a sustainable alternative to cast iron for machine tool foundations. This study develops a data-driven simulation framework to enhance the mechanical properties of epoxy–granite systems by integrating published experimental data with Gaussian Process Regression (GPR) surrogate modeling and Bayesian optimization (BO). The objective is to maximize compressive strength and vibration damping—both critical factors for machining accuracy and dynamic stability. Experimental results from composites with 12–25 wt% epoxy and varied aggregate gradations demonstrate compressive strengths up to 76.8 MPa and flexural strengths reaching 35.4 MPa. The peak damping ratio of 0.0202 was observed at intermediate epoxy content. Mixtures enriched with fine particles also exhibited enhanced fracture toughness and low water absorption, outperforming cementitious concretes, polymer concretes, and natural granite. To address the limitations of experimental coverage, a GPR-based simulation model was employed to explore the four-dimensional design space defined by epoxy content and aggregate fractions. Integrated with BO under realistic manufacturing constraints, the framework identifies optimal formulations comprising 22–26 wt% epoxy and 55–70% fine aggregates. These compositions yield predicted compressive strengths of 78–85 MPa and damping ratios approaching 0.022, indicating significant improvement in overall mechanical properties. Bayesian Weibull analysis further quantifies reliability, revealing shape parameters α ≈ 2.4–2.9, which indicate consistent performance with moderate variability. This work presents the first reported application of an integrated GPR-BO-Bayesian Weibull simulation framework to epoxy–granite composites, enabling simultaneous optimization of conflicting objectives and probabilistic reliability assessment of key mechanical properties. The approach reduces experimental effort by over 70% and supports the circular economy through valorization of granite waste in high-value manufacturing. Nonetheless, predictive uncertainty remains high in under-sampled regions (e.g., damping with n = 2). Future experimental validation—comprising at least 10–15 data points across varied epoxy ratios and gradations—is essential to corroborate the predicted optimum. Full article

This study presents a statistical modeling approach for predicting the operational reliability of induction motors used in dump truck drives. The proposed method uses censored data, including both time to failure and data on properly operating engines, to assess reliability indicators, such as uptime based on Weibull and lognormal distributions. A generalized “life curve” of the stator and bearing unit is constructed, which makes it possible to determine interval estimates of the service life and residual service life. The model is implemented as software for calculating distribution parameters and visualizing reliability dependencies. Approbation based on the operational data of quarry transport confirmed the applicability of the proposed approach for diagnosing and optimizing the maintenance system of induction motors of heavy equipment. Full article

This study introduces a Blasting Safety Index (BSI), a composite analytical framework for quantifying the cumulative mechanical, environmental, and geotechnical effects of quarry blasting operations. The index integrates ground vibration expressed as Peak Particle Velocity (PPV), noise, dust concentration, and slope stability, each normalized and weighted according to its operational relevance, to provide a unified measure of blasting-related risk. Field application in a pyroxenic andesite quarry is presented as a demonstrative pilot case illustrating the internal coherence and operational feasibility of the proposed framework and resulted in a BSI value of 0.91, classifying the operation as high risk despite full compliance with individual regulatory thresholds. Within the applied weighting structure, PPV represented the dominant contribution to the composite index, reflecting its widely documented influence on blast-induced safety outcomes. The proposed methodology offers a transparent, measurement-based decision-support tool for operational control, regulatory communication, and environmental impact assessment. Owing to its compatibility with digital monitoring ecosystems, the BSI supports the advancement of sustainable, risk-aware, and technically optimized blasting practices within modern quarry operations. Full article

Foam concrete is well-appreciated for its thermal and acoustic benefits and is prepared by introducing foam into cement slurry/mortar. The current research examines the feasibility of Quarry Micro Fines (QMF), a waste generated from the quarries during sand manufacturing, as a substitute for fine aggregate in the preparation of foam concrete. During the preparation of concrete, a portion of cement is replaced with sugarcane bagasse ash (SCBA), while polypropylene (PP) fibers are added to improve the shrinkage resistance and tensile strength of the resulting concrete. A three-factor, three-level Box–Behnken Design (BBD) in Response Surface Methodology (RSM) was used to optimize the compressive strength of foam concrete, considering QMF (0%, 50%, 100%) by weight of fine aggregate, SCBA (0%, 10%, 20%) by weight of cement, and PP fiber (0.2%, 0.4%, 0.6%) by volume of foam concrete as variables. The three mixtures, including control (FC), mix with 50% QMF, 10% SCBA, and 0.4% PP fiber (F50S10F0.4), and mix with 100% QMF, 10% SCBA, and 0.4% PP fiber (F100S10F0.4), were chosen for a more in-depth investigation based on the test results. While Q50S10F0.4 achieved the highest compressive strength (6.18 MPa), Q100S10F0.4 showed the best overall performance, with low water absorption of 14.10%, porosity of 20.17%, UPV 2388 m/s, and RCPT values of 1407.96 Coulombs. The modified mixtures exhibited enhanced bonding and pore enhancement as demonstrated by scanning electron microscopy and mercury intrusion porosimetry analyses. The study highlights the effective use of QMF, SCBA, and PP fibers in producing high-performance, sustainable foam concrete. Full article

In the global context of biodiversity loss, increased demand for natural resources, and major efforts to restore ecosystems altered by human activities, the widespread use of passive acoustic monitoring (PAM) and acoustic recording devices allows for the collection of enormous amounts of data for monitoring the health of ecosystems. BirdNET Analyzer is a freely accessible machine learning tool that has had a great impact on the scientific community due to its apparent ease of use for identifying animals by sound. However, the literature shows some gaps regarding the influence of certain BirdNET configuration parameters on the results of its predictions. This study applies PAM and uses BirdNET in a real acoustic monitoring project and analyzes the potential impact of the configuration parameters Overlap and Sensitivity on the results of the bird inventory of a wetland created on the site of a former limestone quarry in Spain. Our results guide other researchers in the optimal combination of configuration parameters at the community level. Higher Sensitivity configuration values provided the optimal solution for minimizing the loss of species in the bird inventory. On the other hand, we identified that Recall is the best indicator to identify all combinations of BirdNET configuration parameters that cause the lowest species loss, in line with the goal of this monitoring program. Full article

Worldwide, large volumes of industrial residues, such as water treatment sludge (WTS), biomass ash (BA), iron slag (IS), and quarry fines (QF), are generated with limited reuse. This study evaluates their potential as additives for two soils, using two types of soils as matrices. A comprehensive laboratory program (particle size distribution, Proctor compaction, Atterberg limits, falling-head permeability, oedometer consolidation, consolidated undrained triaxial tests, and scanning electron microscopy) was performed on soil–residue mixtures across practical dosages. Optimal mixes balanced strength and transport properties: 15% WTS lowered hydraulic conductivity (k) into the 10⁻⁹ m/s range while reducing plasticity; 20% BA rendered the soil non-plastic but increased k into the 10⁻⁸–10⁻⁷ m/s range; 50% IS increased friction angle while maintaining k ~10⁻⁸ m/s; and QF produced modest changes while preserving k ~10⁻⁹ m/s. These findings support the sustainable reuse of these industrial wastes for soft soil stabilization, also contributing to the circular economy in the industrial and construction sectors, and are aligned with the United Nations’ sustainable development goals 6, 9, 11, 12, and 15. Full article

The development of electric quarry transport puts a significant strain on local power grids, leading to sharp peaks in consumption and degradation of power quality. Existing methods of peak smoothing, such as generation control, virtual power plants, or intelligent load management, have limited efficiency under the conditions of stochastic and high-power load profiles of industrial charging stations. A new strategy for direct charge and discharge management of a system for integrated battery energy storage (IBES) is based on dynamic iterative adjustment of load boundaries. The mathematical apparatus of the method includes the formalization of an optimization problem with constraints, which is solved using a nonlinear iterative filter with feedback. The key elements are adaptive algorithms that minimize the network power dispersion functionality (i.e., the variance of $P_{grid}\left(t\right)$ over the considered time interval) while respecting the constraints on the state of charge (SOC) and battery power. Numerical simulations and experimental studies demonstrate a 15 to 30% reduction in power dispersion compared to traditional constant power control methods. The results confirm the effectiveness of the proposed approach for optimizing energy consumption and increasing the stability of local power grids of quarry enterprises. Full article

This study explores a sustainable strategy for enhancing high-strength concrete (HSC) by partially replacing natural fine aggregates with stone quarry sludge (SQS), a byproduct of quarrying operations. The aim is to promote environmental conservation and waste valorization while maintaining or improving concrete performance. Concrete mixes were prepared by substituting fine sand with SQS at incremental levels of 10%, 20%, 30%, 40%, and 50%. Mechanical properties were assessed through specific weight measurements, compressive strength tests, and three-point bending evaluations. FTIR analysis was conducted to investigate microstructural changes, and a carbon footprint assessment was performed to quantify environmental benefits. The mix containing 20% SQS exhibited optimal performance, achieving a compressive strength of 61 MPa and a bending strength of 5.1 MPa. FTIR results confirmed enhanced C–S–H gel formation, indicating improved microstructural integrity. Carbon footprint analysis revealed that moderate SQS substitution significantly reduces embodied carbon. These findings support the use of quarry sludge as a viable component in eco-friendly HSC, with potential for further optimization and long-term durability studies. Full article

The reclamation of exhausted open-pit coal mines is an energy-intensive and costly process. Traditional methods offer no economic return. This study explores the feasibility of using autonomous electric dump trucks (EDTs) to fill the pit, leveraging regenerative braking during descent to generate energy and reduce operational costs. A comprehensive energy balance model was developed based on the operational cycle of the Komatsu HD605-7 (E-Dumper) in the unique downhill-loaded logistics of the Pery quarry. The model incorporates vehicle dynamics equations, including rolling resistance, gradient, and aerodynamic forces, to calculate net energy consumption per cycle. Three energy storage system (ESS) configurations were compared: NMC/NCA batteries, LiFePO₄ (LFP) batteries, and a hybrid LFP + supercapacitor (SC) system. Simulation results demonstrate that the net energy per cycle decreases with increasing payload capacity, even becoming negative (net energy generation) for loads above 110 tons due to powerful regenerative braking on the 13% descent grade. The hybrid LFP + SC system proved most efficient, achieving the lowest specific energy consumption (kWh/ton) by effectively capturing high-power regenerative currents. While LFP batteries have a lower energy density, their superior cycle life, thermal stability, and safety make them the optimal choice for the harsh mining environment. The proposed operation strategy, utilizing EDTs in a downhill-loaded cycle, transforms mine reclamation from a cost center into a potentially energy-neutral or even energy-positive process. A hybrid ESS with LFP batteries and supercapacitors is recommended as the most reliable and efficient solution for this specific application. Full article

In rock blasting for engineering applications—such as quarrying and tunnel construction—blasting is often detonated in carefully timed sequences to optimize rock fragmentation. This study examines Model I crack propagation in tunnel blasting sections with empty holes using circular PMMA (Polymethyl Methacrylate) samples containing pre-made initial cracks and empty holes. The distance between holes was varied from 10 mm to 30 mm. Using AUTODYN V18.0 numerical simulation software, how these holes affect crack initiation, propagation, and the surrounding stress field were analyzed. Key findings include the following: (a) Blasting stress waves diffract and reflect off empty hole edges, creating overlapping pressure zones between adjacent empty holes. Within a critical range of the empty hole distance, wider hole distance leads to slower stress wave propagation due to increased dispersion. (b) The empty holes weaken the stress concentration at crack tips, with greater distance further reducing peak strength. Proximal crack tips experience more pronounced stress field alterations than distal ones. (c) Holes hinder crack initiation, with the required stress intensity factor rising in near-linear proportion to hole separation distance. Full article

The environmental performance of natural aggregates for concrete and road construction, extracted from a dolomite quarry, was investigated. Environmental hotspots were identified, and potential optimization measures to further reduce the environmental footprint were proposed. The natural aggregates extracted from the dolomite quarry have relatively low GWP and a low environmental footprint in general. The GWP of 1 tonne of natural aggregates used in concrete production is 1.13 kg CO₂ equiv., while for 1 tonne of aggregates used in road construction, it is 0.97 kg CO₂ equiv. The dolomite rock in the quarry in question is tectonically fractured, such that very intensive extraction is not required, taking into account the blasting of the rock and further processing. The use of non-road mobile machinery is already optimized. Additional reductions in environmental impact could be achieved by powering the screening process exclusively with electricity from renewable sources, such as a photovoltaic system. In this context, integrating on-site battery storage systems might present a promising solution for addressing the seasonal mismatch between solar energy generation and processing demands. Full article

This paper proposes algorithms for optimal placement of base stations (BSs) and central stations (CSs) in mining quarries to ensure reliable radio communication for automated machinery. The BS placement is modeled as a minimum dominating set problem, solved using integer linear programming with cutting-plane methods. The CS placement is formulated as a nonlinear programming problem, addressed via a minimum circle covering algorithm. Applied in a 200 km² quarry, the approach achieves full coverage with nine BSs and one CS, minimizing costs and ensuring robust performance. Comparative analyses show superior optimality, scalability, and adaptability, offering a scalable framework for industrial communication infrastructure. Full article

The construction industry increasingly integrates technological advancements to enhance efficiency and meet technical, environmental, and economic requirements. Self-compacting mortars are gaining popularity due to their superior fluidity, optimized compaction, and improved mechanical properties. This study explores the potential of statistical mix design methodology to optimize self-compacting mortars’ fresh properties and strength development by replacing up to 20% of cement with pozzolana, limestone, and marble powder. A self-compacting mortar repository was used to develop robust models predicting slump flow, compressive strength at 28 days, water absorption, and capillary absorption. Results indicate that marble powder mixtures exhibit superior slump flow, up to 9% higher than other formulations. Compressive strengths range from 50 MPa to 70 MPa. Pozzolana and marble-based mortars show 15% and 12% strength reductions compared to the limestone-based mix, respectively. Water absorption increases slightly for mortars with marble (+2%) or pozzolana (+3%). The mortar containing marble powder has the lowest sorptivity coefficient due to its high specific surface area. The statistical analysis was conducted using a mixture design approach based on a second-order polynomial regression model. ANOVA results for the studied responses indicate that the calculated F-values exceed the critical thresholds, with p-values below 0.05 and R-squared values above 0.83, confirming the robustness and predictive reliability of the developed models. Life cycle assessment reveals that cement production accounts for over 80% of the environmental impact. Partial replacement with pozzolana, limestone, and marble powder reduces up to 19% of greenhouse gas emissions and 17.22% in non-renewable energy consumption, demonstrating the environmental benefits of optimized formulations. Full article

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. Full article

This study presents a discrete event simulation model to minimize operating costs in quarry mining processes by determining the optimal allocation of backhoes and dump trucks, which are the primary mining equipment. The modeling focuses on four principal vehicle types (24-ton dump truck, 2.0 m³ backhoe, 41-ton dump truck, 4.64 m³ backhoe) commonly deployed in quarry mining. The simulation replicates the sequential mining stages involving soil removal, rock ripping (weathered rock or weathered soil), and blasting operations. This methodology is applied to a case study of mining process planning under resource constraints, incorporating real-world quarry conditions in South Korea. Results demonstrate that optimizing the number of equipment units reduces construction costs and shortens the construction period by decreasing dump truck waiting times. When the number of backhoes is limited to 10 during operations, findings indicate an increase in costs and a gradual decline in net profit. Additionally, the interaction between the 24-ton and 41-ton dump trucks is shown to influence the optimal allocation strategy. The simulation-based optimization executes iterative experiments for each scenario, yielding statistically robust results within a 95% confidence interval, thereby supporting informed decision-making for managers. Full article