Search Results (664)

Quarry dust (QD) landfill causes environmental issues that cannot be ignored. In this study, we systematically explore its potential application as a supplementary cementitious material (SCM) in cemented paste backfill (CPB), revealing the activated mechanism of modified QD (MQD) and exploring the hydration process and workability of CPB containing QD/MQD. The experimental results show that quartz, clinochlore and amphibole components react with CaO to form reactive dicalcium silicate (C₂S) and amorphous glass phases, promoting pozzolanic reactivity in MQD. QD promotes early aluminocarbonate (M_c) formation through CaCO₃-derived CO₃²⁻ release but shifts to hemicarboaluminate (H_c) dominance at 28 d. MQD releases active Al³⁺/Si⁴⁺ due to calcination and deconstruction, significantly increasing the amount of ettringite (AFt) in the later stage. With the synergistic effect of coarse–fine particle gradation, MQD-type fresh backfill can achieve a 161 mm flow spread at 20% replacement. Even if this replacement rate reaches 50%, a strength of 19.87 MPa can still be maintained for 28 days. The good workability and low carbon footprint of MQD-type backfill provide theoretical support for—and technical paths toward—QD recycling and the development of low-carbon building materials. Full article

This study proposes an integrated, machine learning-based multi-objective optimization framework to evaluate and optimize the utilization of steel slag in road base layers, simultaneously addressing economic costs and environmental impacts. A comprehensive dataset of 482 scenarios was engineered based on literature-informed parameters, encompassing transport distance, processing energy intensity, initial moisture content, gradation adjustments, and regional electricity emission factors. Four advanced tree-based ensemble regression algorithms—Random Forest Regressor (RFR), Extremely Randomized Trees (ERTs), Gradient Boosted Regressor (GBR), and Extreme Gradient Boosting Regressor (XGBR)—were rigorously evaluated. Among these, GBR demonstrated superior predictive performance (R² > 0.95, RMSE < 7.5), effectively capturing complex nonlinear interactions inherent in slag processing and logistics operations. Feature importance analysis via SHapley Additive exPlanations (SHAP) provided interpretative insights, highlighting transport distance and energy intensity as dominant factors affecting unit cost, while moisture content and grid emission factor predominantly influenced CO₂ emissions. Subsequently, the Gradient Boosted Regressor model was integrated into a Non-Dominated Sorting Genetic Algorithm II (NSGA-II) framework to explore optimal trade-offs between cost and emissions. The resulting Pareto front revealed a diverse solution space, with significant nonlinear trade-offs between economic efficiency and environmental performance, clearly identifying strategic inflection points. To facilitate actionable decision-making, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was applied, identifying an optimal balanced solution characterized by a transport distance of 47 km, energy intensity of 1.21 kWh/ton, moisture content of 6.2%, moderate gradation adjustment, and a grid CO₂ factor of 0.47 kg CO₂/kWh. This scenario offered a substantial reduction (45%) in CO₂ emissions relative to cost-minimized solutions, with a moderate increase (33%) in total cost, presenting a realistic and balanced pathway for sustainable infrastructure practices. Overall, this study introduces a robust, scalable, and interpretable optimization framework, providing valuable methodological advancements for sustainable decision making in infrastructure planning and circular economy initiatives. Full article

This study demonstrates the successful fabrication of high-performance reaction-bonded silicon carbide (RBSC) ceramics through an optimized liquid silicon infiltration (LSI) process employing multi-modal SiC particle gradation and nano-carbon black (0.6 µm) additives. By engineering porous preforms with hierarchical SiC distributions and tailored carbon sources, the resulting ceramics achieved a compressive strength of 2393 MPa and a flexural strength of 380 MPa, surpassing conventional RBSC systems. Microstructural analyses revealed homogeneous β-SiC formation and crack deflection mechanisms as key contributors to mechanical enhancement. Ultrafine SiC particles (0.5–2 µm) refined pore architectures and mediated capillary dynamics during infiltration, enabling nanoscale dispersion of residual silicon phases and minimizing interfacial defects. Compared to coarse-grained counterparts, the ultrafine SiC system exhibited a 23% increase in compressive strength, attributed to reduced sintering defects and enhanced load transfer efficiency. This work establishes a scalable strategy for designing RBSC ceramics for extreme mechanical environments, bridging material innovation with applications in high-stress structural components. Full article

Reaction bonding (RB) using Al powder is an effective method for preparing porous ceramics with low shrinkage, high porosity, and high strength. However, it remains challenging to optimize mechanical strength and oil conductivity simultaneously for atomizer applications. Herein, aiming at addressing this issue, porous Al₂O₃ ceramics with ultra-high mechanical strength and oil conductivity were fabricated via the RB process using polymethyl methacrylate (PMMA) microspheres as the pore-forming agent. The pore structure was gradually optimized by regulating the additive amount, particle size, and particle gradation of PMMA microspheres. The bimodal pores, formed by Al oxidation-induced hollow structures (enhancing bonding force) and burnout of large-sized PMMA microspheres, significantly improved mechanical strength; meanwhile, three-dimensional interconnected pores derived from particle gradation increased the diversity and quantity of oil-conduction channels, boosting oil conductivity. Consequently, under an open porosity of 58.2 ± 0.1%, a high compressive strength of 7.9 ± 0.3 MPa (a 54.7% improvement) and an excellent oil conductivity of 2.1 ± 0.0 mg·s⁻¹ (a 46.5% improvement) were achieved. This superior performance combination, overcoming the trade-off between strength and oil conductivity, demonstrates substantial application potential in atomizers. Full article

The following investigation presents concrete cement obtained with the Viterbo O’Reilly Diaz method, introduced to quantify the concrete mixture by using an aggregate gradation method. This research uses this procedure to decrease the amount of cement in the mix, thus reducing the CO₂ footprint and production costs, which directly impact the environmental and economical sustainability of the material. The formulations used structural and general use Portland cements. As aggregates, fine sand and 3/4” gravel were included. Several characterization techniques were used, including granulometry testing for the aggregates, compression strength testing for the concrete samples, and granulometry testing for the raw materials. Compressive tests were conducted on samples after 28 days of curing, while scanning electron microscopy (SEM) with energy-dispersive spectroscopy (EDS) was used to understand the microstructure. The results revealed the optimal amounts of water, cement, and aggregates. Combinations of fine and coarse aggregates were determined as well. The main novelty in this manuscript is the use of the Viterbo O’Reilly mix design method to innovatively enhance concrete mixes by analyzing material properties and behavior in detail, an unexplored method in the literature. This research considers not only strength but also durability and workability, using mathematical tools for data analysis. This data-driven approach ensures effective aggregate gradation towards sustainability when compared to other traditional methods. Full article

Channeling in cementing causes interlayer interference, severely restricting oilfield recovery. Existing channeling plugging agents, such as cement and gels, often lead to reservoir damage or insufficient strength. Oil-soluble resin (OSR) particles show great potential in selective plugging of channeling fractures due to their excellent oil solubility, temperature/salt resistance, and high strength. However, their application is limited by the efficient filling and retention in deep fractures. This study innovatively combines the OSR particle plugging system with the mature rapid filtration loss plugging mechanism in drilling, systematically exploring the influence of particle size and sorting on their filtration, packing behavior, and plugging performance in channeling fractures. Through API filtration tests, visual fracture models, and high-temperature/high-pressure (100 °C, salinity 3.0 × 10⁵ mg/L) core flow experiments, it was found that well-sorted large particles preferentially bridge in fractures to form a high-porosity filter cake, enabling rapid water filtration from the resin plugging agent. This promotes efficient accumulation of OSR particles to form a long filter cake slug with a water content <20% while minimizing the invasion of fine particles into matrix pores. The slug thermally coalesces and solidifies into an integral body at reservoir temperature, achieving a plugging strength of 5–6 MPa for fractures. In contrast, poorly sorted particles or undersized particles form filter cakes with low porosity, resulting in slow water filtration, high water content (>50%) in the filter cake, insufficient fracture filling, and significantly reduced plugging strength (<1 MPa). Finally, a double-slug strategy is adopted: small-sized OSR for temporary plugging of the oil layer injection face combined with well-sorted large-sized OSR for main plugging of channeling fractures. This strategy achieves fluid diversion under low injection pressure (0.9 MPa), effectively protects reservoir permeability (recovery rate > 95% after backflow), and establishes high-strength selective plugging. This study clarifies the core role of particle size and sorting in regulating the OSR plugging effect based on rapid filtration loss, providing key insights for developing low-damage, high-performance channeling plugging agents and scientific gradation of particle-based plugging agents. Full article

HPMC, regulating slurry properties, is widely used in cement-based materials. Research on the application of HPMC in gangue slurry is still in its early stages. Moreover, the interactive effects of various factors on gangue slurry performance have not been thoroughly investigated. The work examined the effects of slurry concentration (X₁), maximum gangue particle size (X₂), and HPMC dosage (X₃) on slurry performance using response surface methodology (RSM). The microstructure of the slurry was characterized via scanning electron microscopy (SEM) and polarized light microscopy (PLM), while low-field nuclear magnetic resonance (LF-NMR) was employed to analyze water distribution. Additionally, industrial field tests were conducted. The results are presented below. (1) X₁ and X₃ exhibited a negative correlation with layering degree and slump flow, while X₂ showed a positive correlation. Slurry concentration had the greatest impact on slurry performance, followed by maximum particle size and HPMC dosage. HPMC significantly improved slurry stability, imposing the minimum negative influence on fluidity. Interaction terms X₁X₂ and X₁X₃ significantly affected layering degree and slump flow, while X₂X₃ significantly affected layering degree instead of slump flow. (2) Derived from the RSM, the statistical models for layering degree and slump flow define the optimal slurry mix proportions. The gangue gradation index ranged from 0.40 to 0.428, with different gradations requiring specific slurry concentration and HPMC dosages. (3) HPMC promoted the formation of a 3D floc network structure of fine particles through adsorption-bridging effects. The spatial supporting effect of the floc network inhibited the sedimentation of coarse particles, which enhanced the stability of the slurry. Meanwhile, HPMC only converted a small amount of free water into floc water, which had a minimal impact on fluidity. HPMC addition achieved the synergistic optimization of slurry stability and fluidity. (4) Field industrial trials confirmed that HPMC-optimized gangue slurry demonstrated significant improvements in both stability and flowability. The optimized slurry achieved blockage-free pipeline transportation, with a maximum spreading radius exceeding 60 m in the goaf and a maximum single-borehole backfilling volume of 2200 m³. Full article

The innovation of multi-material offers significant benefits to architectural systems. The fusion of multiple materials, transitioning from one to another in a graded manner, enables the creation of fused space without the need for mechanical connections. Given that plastic is a major contributor to ecological imbalance, this research on fused space aims to recycle plastic and use it as a multi-material for building applications, due to its capacity for being 3D printed and fused with other materials. Furthermore, to generate diverse properties for the fused space, several nature-inspired forming algorithms are employed, including Swarm Behavior, Voronoi, Game of Life, and Shortest Path, to shape the building enclosure. Subsequently, digital analyses, such as daylight analysis, structural analysis, porosity analysis, and openness analysis, are conducted on the enclosure, forming the color mapping digital diagram, which determines the distribution of varying thickness, density, transparency, and flexibility gradation parameters, resulting in spatial diversity. During the fabrication process, Dual Force V1 and Dual Force V2 were developed to successfully print multi-material gradations with fused plastic following an upgrade to the cooling system. Finally, three test sites in London were chosen to implement the fused space concept using multi-material. Full article

This study investigated the fracture behavior of asphalt mixtures under indirect tensile loading by comparing the performance of homogenized and micromechanical finite element (FEMs) models based on the cohesive zone model (CZM). Five asphalt mixture types were tested experimentally, and both models were calibrated and validated using load–displacement curves from indirect tensile tests (IDTs). The micromechanical model, incorporating random aggregate generation and three-phase material definition, exhibited significantly higher predictive accuracy (R² = 0.86–0.98) than the homogenized model (R² = 0.66–0.77). The validated micromechanical model was further applied to quantify the impact of construction-related deficiencies—namely, increased air voids, non-continuous gradation, and aggregate segregation. The simulation results showed that higher void content (from 4% to 10%) reduced peak load by up to 35% and increased localized stress concentrations by up to 40%. Discontinuous gradation and uneven aggregate distribution also led to premature crack initiation and more complex fracture paths. These findings demonstrated the value of micromechanical modeling for evaluating sensitivity to mix design and compaction quality, providing a foundation for performance-based asphalt mixture optimization and durability improvement. Full article

Background/Objectives: The accurate identification of insect bites from images of skin is daunting due to the fine gradations among diverse bite types, variability in human skin response, and inconsistencies in image quality. Methods: For this work, we introduce DeepBiteNet, a new ensemble-based deep learning model designed to perform robust multiclass classification of insect bites from RGB images. Our model aggregates three semantically diverse convolutional neural networks—DenseNet121, EfficientNet-B0, and MobileNetV3-Small—using a stacked meta-classifier designed to aggregate their predicted outcomes into an integrated, discriminatively strong output. Our technique balances heterogeneous feature representation with suppression of individual model biases. Our model was trained and evaluated on a hand-collected set of 1932 labeled images representing eight classes, consisting of common bites such as mosquito, flea, and tick bites, and unaffected skin. Our domain-specific augmentation pipeline imputed practical variability in lighting, occlusion, and skin tone, thereby boosting generalizability. Results: Our model, DeepBiteNet, achieved a training accuracy of 89.7%, validation accuracy of 85.1%, and test accuracy of 84.6%, and surpassed fifteen benchmark CNN architectures on all key indicators, viz., precision (0.880), recall (0.870), and F1-score (0.875). Our model, optimized for mobile deployment with quantization and TensorFlow Lite, enables rapid on-client computation and eliminates reliance on cloud-based processing. Conclusions: Our work shows how ensemble learning, when carefully designed and combined with realistic data augmentation, can boost the reliability and usability of automatic insect bite diagnosis. Our model, DeepBiteNet, forms a promising foundation for future integration with mobile health (mHealth) solutions and may complement early diagnosis and triage in dermatologically underserved regions. Full article

To investigate the effects of heavy-metal-sludge sintered aggregates on the workability, mechanical properties, and fracture toughness of ultra-high-strength concrete (UHSC), this study systematically evaluated the influence of different aggregate replacement ratios and particle gradations on the fluidity, flexural strength, compressive strength, and fracture energy of UHSC. Microstructural characterization techniques including SEM, XRD, TG, and FTIR were employed to analyze the hydration mechanism and interfacial transition zone evolution. The results demonstrated the following: Fluidity continuously improved with the increase in the sintered aggregate replacement ratio, with coarse aggregates exhibiting the most significant enhancement due to the “ball-bearing effect” and paste enrichment. The mechanical properties followed a trend of an initial increase followed by a decrease, peaking at 15–20% replacement ratio, at which flexural strength, compressive strength, and fracture energy were optimally enhanced; excessive replacement led to strength reduction owing to skeletal structure weakening, with coarse aggregates providing superior improvement. Microstructural analysis revealed that the sintered aggregates accelerated hydration reactions, promoting the formation of C-S-H gel and Ca(OH)₂, thereby densifying the ITZ. This study identified 15–20% of coarse sintered aggregates as the optimal replacement ratio, which synergistically improved the workability, mechanical properties, and fracture toughness of UHSC. Full article

To investigate the evolution trend of the extraction zone above the drawbell in block caving, an experimental apparatus incorporating the drawbell structure was designed. Ore drawing experiments were conducted using materials with varying particle size gradations. The results demonstrate that the extraction zones for all three gradations exhibit an ellipsoidal shape in the vertical direction, with elliptical cross-sections. As the draw height increases, both the major and minor axes of the extraction zone’s maximum cross-section continuously enlarge, stabilizing beyond a draw height of 80 cm. The ore fragment size significantly influences the extraction zone dimensions. Gradation I, characterized by the smallest average particle size, yielded the largest extraction zone, whereas Gradation III, with the largest average particle size, resulted in the smallest. Numerical simulations of ore drawing for the different particle sizes were performed using PFC3D. The extent of the extraction zone in the numerical results was determined by reconstructing the initial positions of the drawn particles. The simulations show good agreement with the experimental findings, particularly regarding how the major and minor axes of the extraction zone cross-section vary with increasing draw height. Moreover, the simulations confirm that smaller average particle sizes enhance particle flowability, leading to larger extraction zones, as anticipated. Full article

Grouting, as a widely applicable and versatile foundation treatment technology, plays a crucial role in addressing seepage control problems in cover layers due to its flexibility and convenience. The effectiveness of grouting largely depends on slurry diffusion; however, due to the opaque nature of geotechnical media, the diffusion mechanism of slurry in the cover layers remains insufficiently understood. To investigate this, a visual grouting model device was designed and fabricated, and grouting tests were conducted using transparent soil materials to simulate the cover layers. The slurry diffusion patterns and the velocity field within the transparent soil were analyzed. The results show that, based on refractive-index matching, fused quartz sand of specific gradation and white mineral oil were selected as simulation materials for the cover layers. A stable slurry suitable for transparent grouting was also chosen to satisfy visualization requirements. The transparent soil grouting model, integrated with a Digital Image Correlation (DIC) monitoring system, has the advantages of demonstrating simple operation, real-time monitoring, and high precision. These tests verify the feasibility of visualizing slurry diffusion in cover layers. Furthermore, step-pressure grouting tests preliminarily reveal the dynamic mechanism of slurry diffusion. The results suggest that, in the cover layer, the cover layer in this grouting test is mainly splitting grouting, accompanied by compaction grouting. These methods offer new insights and methods for model testing of cover layer grouting mechanisms. Full article

The composition design of asphalt mixtures plays a pivotal role in determining pavement performance and durability. To improve skeleton stability, paving uniformity, and mechanical strength, this research proposes a three-dimensional optimization framework for asphalt mixture design, focusing on aggregate gradation and optimum asphalt content. A skeleton-dense and anti-segregation gradation optimization method was developed by integrating a previously established skeleton-dense model with a segregation tendency prediction approach. In parallel, a mechanically driven method for determining optimum asphalt content was proposed by introducing the maximum migration shear stress as a performance-based alternative to the conventional Marshall stability parameter. Research results show that asphalt mixtures designed and compacted with the optimized gradation exhibit significantly enhanced high-temperature stability, while maintaining satisfactory low-temperature cracking resistance and moisture susceptibility. Field validation was conducted through the construction of a trial pavement section using the optimized gradation under recommended mixing and compaction temperatures. The resulting pavement demonstrated excellent compaction, strong resistance to segregation, and a highly stable spatial structure. These findings confirm the effectiveness of the proposed methodology in enhancing the high-temperature deformation resistance and overall structural integrity of asphalt mixtures. Full article

Precise grading of manufactured sand is vital to concrete performance, yet standard sieve tests, though accurate, are too slow for online quality control. Thus, we devised an image-based inspection method combining a dual-camera module with a Temporal Interval Sampling Strategy (TISS) to enhance throughput while maintaining precision. In this design, a global wide-angle camera captures the entire particle field, whereas a local high-magnification camera focuses on fine fractions. TISS selects only statistically representative frames, effectively eliminating redundant data. A lightweight segmentation algorithm based on geometric rules cleanly separates overlapping particles and assigns size classes using a normal-distribution classifier. In tests on ten 500 g batches of manufactured sand spanning fine, medium, and coarse gradations, the system processed each batch in an average of 7.8 min using only 34 image groups. It kept the total gradation error within 12% and the fineness-modulus deviation within ±0.06 compared to reference sieving. These results demonstrate that the combination of complementary optics and targeted sampling can provide a scalable, real-time solution. Full article