Search Results (783)

In tunnel blasting, an analytical solution for dynamic stress in the surrounding rock of adjacent tunnels is critical for dynamic response analysis, mechanical evaluations, and crack propagation control. Previous studies on stress field analytical solutions primarily modeled rock as a linear elastic material, focusing mainly on the P-wave effects from instantaneous detonation. Based on Heelan’s short cylindrical cavity model, this paper derives an analytical solution for blast-induced dynamic stresses in adjacent tunnel rock, incorporating both induced SV-waves and a rock mass damage factor through rigorous theoretical analysis. Numerical case studies and field measurements were used to analyze stress propagation during tunnel blasting, and theoretical results were compared with measured data. The key findings were as follows: Radial stress > axial stress > hoop stress. All three stresses decay with increasing distance and damage factor, following an inversely proportional relationship with distance. Radial stress decays faster than axial and hoop stresses. Stress also decays exponentially over time, with the peak occurring after the transverse wave arrival. The theoretical results show approximately 10% deviation from the existing empirical formulas, while field measurements closely match the theoretical model, showing consistent stress trends and an average error of 7.02% (radial), 7.56% (axial) and 7.05% (hoop), confirming the reliability of the proposed analytical solution. Full article

Ferronickel slag and ground granulated blast-furnace slag (GGBFS) are solid waste by-products from the metallurgical industry. When incorporated into concrete, they help promote resource utilization, reduce hydration heat, and lower both solid waste emissions and the carbon footprint. To facilitate the application of ferronickel slag–GGBFS concrete in 3D printing, this study examines how aggregate size and nozzle diameter affect its performance. The investigation involves in situ printing, rheological characterization, mechanical testing, and scanning electron microscopy (SEM) analysis. Results indicate that excessively large average aggregate size negatively impacts the smooth extrusion of concrete strips, resulting in a cross-sectional width that exceeds the preset dimension. Excessively small average aggregate size results in insufficient yield stress, leading to a narrow cross-section of the extruded strip that fails to meet printing specifications. The extrusion performance is closely related to both the average aggregate size and nozzle diameter, which can significantly influence the normal extrusion stability and print quality of 3D printed concrete strips. The thixotropic performance improves with an increase in the aggregate size. Both compressive and flexural strengths improve with increasing aggregate size but decrease with an increase in the printing nozzle size. Anisotropy in mechanical behavior decreases progressively as both parameters mentioned increase. By examining the cracks and pores at the interlayer interface, this study elucidates the influence mechanism of aggregate size as well as printing nozzle parameters on the mechanical properties of 3D printed ferronickel slag–GGBFS concrete. This study also recommends the following ranges. When the maximum aggregate size exceeds 50% of the nozzle diameter, smooth extrusion is not achievable. If it falls between 30% and 50%, extrusion is possible but shaping remains unstable. When it is below 30%, both stable extrusion and good shaping can be achieved. Full article

To address the inefficiency of traditional concrete crack detection methods and the heavy reliance of supervised learning on extensive labeled data, in this study, an intelligent assessment method of concrete damage based on pseudo-label semi-supervised learning and fractal geometry theory is proposed to solve two core tasks: one is binary classification of pixel-level cracks, and the other is multi-category assessment of damage state based on crack morphology. Using three-channel RGB images as input, a dual-path collaborative training framework based on U-Net encoder–decoder architecture is constructed, and a binary segmentation mask of the same size is output to achieve the accurate segmentation of cracks at the pixel level. By constructing a dual-path collaborative training framework and employing a dynamic pseudo-label refinement mechanism, the model achieves an F1-score of 0.883 using only 50% labeled data—a mere 1.3% decrease compared to the fully supervised benchmark DeepCrack (F1 = 0.896)—while reducing manual annotation costs by over 60%. Furthermore, a quantitative correlation model between crack fractal characteristics and structural damage severity is established by combining a U-Net segmentation network with the differential box-counting algorithm. The experimental results demonstrate that under a cyclic loading of 147.6–221.4 kN, the fractal dimension monotonically increases from 1.073 (moderate damage) to 1.189 (failure), with 100% accuracy in damage state identification, closely aligning with the degradation trend of macroscopic mechanical properties. In complex crack scenarios, the model attains a recall rate (Re = 0.882), surpassing U-Net by 13.9%, with significantly enhanced edge reconstruction precision. Compared with the mainstream models, this method effectively alleviates the problem of data annotation dependence through a semi-supervised strategy while maintaining high accuracy. It provides an efficient structural health monitoring solution for engineering practice, which is of great value to promote the application of intelligent detection technology in infrastructure operation and maintenance. Full article

The operation of heavy-haul railway trains with large loads results in significant cracking issues in reinforced concrete beams. Atmospheric carbon dioxide, oxygen, and moisture from the atmosphere penetrate into the beam interior through these cracks, accelerating the carbonation of the concrete and the corrosion of the steel bars. The rust-induced expansion of steel bars further exacerbates the cracking of the beam. The interaction between environmental factors and beam cracks leads to a rapid decline in the durability of the beam. To address this issue, a multi-physics field coupling durability assessment method was proposed, considering concrete beam cracking, concrete carbonation, and steel bar corrosion. The interaction among these three factors is achieved through sequential coupling, using crack width, carbonation passivation time, and steel bar corrosion rate as interaction parameters. Using this method, the deterioration morphology and stiffness degradation laws of 8 m reinforced concrete beams under different load conditions, including those of heavy and light trains in heavy-haul railways, are compared and assessed. The analysis reveals that within a 100-year service cycle, the maximum relative stiffness reduction for beams on the heavy train line is 20.0%, whereas for the light train line, it is only 7.4%. The degree of structural stiffness degradation is closely related to operational load levels, and beam cracking plays a critical role in this difference. Full article

Postharvest losses amongst small-scale farmers in developing countries are high due to inadequate resources and infrastructure. Among the various affected crops, tomatoes are particularly vulnerable; however, studies on postharvest losses of most fruits and vegetables are limited. Therefore, this study aimed to assess postharvest tomato losses under different production systems within the small-scale supply chain using the indirect assessment (questionnaires and interviews) and direct quantification of losses. Farmers reported tomato losses due to insects (82.35%), cracks, bruises, and deformities (70.58%), and diseases (64.71%). Chemical sprays were the main form of pest and disease control reported by all farmers. The direct quantification sampling data revealed that 73.07% of the tomatoes were substandard at the farm level, with 47.92% and 25.15% categorized as medium-quality and poor-quality, respectively. The primary contributors to the losses were decay (39.92%), mechanical damage (31.32%), and blotchiness (27.99%). Postharvest losses were significantly higher under open-field production systems compared to closed tunnels. The fungi associated with decay were mainly Geotrichum, Fusarium spp., and Alternaria spp. These findings demonstrate the main drivers behind postharvest losses, which in turn highlight the critical need for intervention through training and support, including the use of postharvest loss reduction technologies to enhance food security. Full article

The Silurian marine shale in the Sichuan Basin is currently the main reservoir for shale gas reserves and production in China. This study investigates the reservoir evolution of the Silurian marine shale based on fractal dimension, quantifying the complexity and heterogeneity of the shale’s pore structure. Physical simulation experiments were conducted on field-collected shale samples, revealing the evolution of total organic carbon, mineral composition, porosity, and micro-fractures. The fractal dimension of shale pore was characterized using the Frenkel–Halsey–Hill and capillary bundle models. The relationships among shale components, porosity, and fractal dimensions were investigated through a correlation analysis and a principal component analysis. A comprehensive evolution model for porosity and micro-fractures was established. The evolution of mineral composition indicates a gradual increase in quartz content, accompanied by a decline in clay, feldspar, and carbonate minerals. The thermal evolution of organic matter is characterized by the formation of organic pores and shrinkage fractures on the surface of kerogen. Retained hydrocarbons undergo cracking in the late stages of thermal evolution, resulting in the formation of numerous nanometer-scale organic pores. The evolution of inorganic minerals is represented by compaction, dissolution, and the transformation of clay minerals. Throughout the simulation, porosity evolution exhibited distinct stages of rapid decline, notable increase, and relative stabilization. Both pore volume and specific surface area exhibit a trend of decreasing initially and then increasing during thermal evolution. However, pore volume slowly decreases after reaching its peak in the late overmature stage. Fractal dimensions derived from the Frenkel–Halsey–Hill model indicate that the surface roughness of pores (D1) in organic-rich shale is generally lower than the complexity of their internal structures (D2) across different maturity levels. Additionally, the average fractal dimension calculated based on the capillary bundle model is higher, suggesting that larger pores exhibit more complex structures. The correlation matrix indicates a co-evolution relationship between shale components and pore structure. Principal component analysis results show a close relationship between the porosity of inorganic pores, microfractures, and fractal dimension D2. The porosity of organic pores, the pore volume and specific surface area of the main pore size are closely related to fractal dimension D1. D1 serves as an indicator of pore development extent and characterizes the changes in components that are “consumed” or “generated” during the evolution process. Based on mineral composition, fractal dimensions, and pore structure evolution, a comprehensive model describing the evolution of pores and fractal dimensions in organic-rich shale was established. Full article

Loess, a typical soil widely distributed in China, exhibits engineering properties that are highly sensitive to environmental changes, leading to increased erosion and the development of surface cracks. This article examines the influence of initial moisture content, dry density, and thickness on crack formation in compacted loess subjected to wet–dry cycles, using both laboratory experiments and numerical simulation analysis. It quantitatively analyzes the process of crack evolution using digital image processing technology. The experimental results indicate that wet–dry cycles can cause cumulative damage to the soil, significantly encouraging the initiation and expansion of secondary cracks. New cracks often branch out and extend along the existing crack network, demonstrating that the initial crack morphology has a controlling effect over the final crack distribution pattern. Numerical simulations based on MultiFracS software further revealed that soil samples with a thickness of 0.5 cm exhibited more pronounced surface cracking characteristics than those with a thickness of 2 cm, with thinner layers of soil tending to form a more complex network of cracks. The simulation results align closely with the indoor test data, confirming the reliability of the established model in predicting fracture dynamics. The study provides theoretical underpinnings and practical guidance for evaluating the stability of engineering slopes and for managing and mitigating fissure hazards in loess. Full article

Efficient detection of road surface defects is vital for timely maintenance and traffic safety. This study introduces a novel AI-powered web framework, TriRoad AI, that integrates multiple versions of the You Only Look Once (YOLO) object detection algorithms—specifically YOLOv8 and YOLOv11—for automated detection of potholes and cracks. A user-friendly browser interface was developed to enable real-time image analysis, confidence-based prediction filtering, and severity-based geolocation mapping using OpenStreetMap. Experimental evaluation was conducted using two datasets: one from online sources and another from field-collected images in Ankara, Turkey. YOLOv8 achieved a mean accuracy of 88.43% on internet-sourced images, while YOLOv11-B demonstrated higher robustness in challenging field environments with a detection accuracy of 46.15%, and YOLOv8 followed closely with 44.92% on mixed field images. The Gemini AI model, although highly effective in controlled environments (97.64% detection accuracy), exhibited a significant performance drop of up to 80% in complex field scenarios, with its accuracy falling to 18.50%. The proposed platform’s uniqueness lies in its fully integrated, browser-based design, requiring no device-specific installation, and its incorporation of severity classification with interactive geospatial visualization. These contributions address current gaps in generalization, accessibility, and practical deployment, offering a scalable solution for smart infrastructure monitoring and preventive maintenance planning in urban environments. Full article

To explore the influence of mine roof on the damage and failure of sandstone surrounding rock under different pressure rates, mechanical experiments with different strain rates were carried out on sandstone rock samples. The strength, deformation, failure, energy and damage characteristics of rock samples with different strain rates were also discussed. The research results show that with the increases in the strain rate, peak stress, and elastic modulus show a monotonically increasing trend, while the peak strain decreases in the reverse direction. At a low strain rate, the proportion of the mass fraction of complete rock blocks in the rock sample is relatively high, and the shape integrity is good, while rock samples with a high strain rate retain more small-sized fragmented rock blocks. This indicates that under high-rate loading, the bifurcation phenomenon of secondary cracks is obvious. The rock samples undergo a failure form dominated by small-sized fragments, with severe damage to the rock samples and significant fractal characteristics of the fragments. At the initial stage of loading, the primary fractures close, and the rock samples mainly dissipate energy in the forms of frictional slip and mineral fragmentation. In the middle stage of loading, the residual fractures are compacted, and the dissipative strain energy keeps increasing continuously. In the later stage of loading, secondary cracks accelerate their expansion, and elastic strain energy is released sharply, eventually leading to brittle failure of the rock sample. Under a low strain rate, secondary cracks slowly expand along the clay–quartz interface and cause intergranular failure of the rock sample. However, a high strain rate inhibits the stress relaxation of the clay, forces the energy to transfer to the quartz crystal, promotes the penetration of secondary cracks through the quartz crystal, and triggers transgranular failure. A constitutive model based on energy damage was further constructed, which can accurately characterize the nonlinear hardening characteristics and strength-deformation laws of rock samples with different strain rates. The evolution process of its energy damage can be divided into the unchanged stage, the slow growth stage, and the accelerated growth stage. The characteristics of this stage reveal the sudden change mechanism from the dissipation of elastic strain energy of rock samples to the unstable propagation of secondary cracks, clarify the cumulative influence of strain rate on damage, and provide a theoretical basis for the dynamic assessment of surrounding rock damage and disaster early warning when the mine roof comes under pressure. Full article

This study presents colorless polyimides (PIs) suitable for use as plastic substrates in flexible displays, designed to be compatible with controlled soft adhesion and easy delamination (temporary adhesion) processes. For this purpose, we focused on a PI system derived from norbornane-2-spiro-α-cyclopentanone-α′-spiro-2″-norbornane-5,5″,6,6″-tetracarboxylic dianhydride (CpODA) and 2,2′-bis(trifluoromethyl)benzidine (TFMB). This system was selected with the aim of exhibiting excellent optical transparency and low linear coefficient of thermal expansion (CTE) properties. However, fabricating this PI film via the conventional two-step process was challenging because of crack formation. In contrast, modified one-pot polymerization at 200 °C using a combined catalyst resulted in a homogeneous solution of PI with an exceptionally high molecular weight, yielding a flexible cast film. The solubility of PI plays a crucial role in its success. This study delves into the mechanism behind the significant catalytic effect on enhancing molecular weight. The CpODA/TFMB PI cast film simultaneously achieved very high optical transparency, an extremely high glass transition temperature (T_g = 411 °C), a significantly low linear coefficient of thermal expansion (CTE = 16.7 ppm/K), and sufficient film toughness, despite the trade-off between low CTE and high film toughness. The CpODA/TFMB system was modified by copolymerization with minor contents of another cycloaliphatic tetracarboxylic dianhydride, 5,5′-(1,4-phenylene)-exo-bis(hexahydro-4,7-methanoisobenzofuran-cis-exo-1,3-dione) (BzDAxx). This approach was effective in improving the film toughness without sacrificing the low CTE and other target properties. The peel strengths (σ_peel) of laminates comprising surface-modified glass substrates and various colorless PI films were measured to evaluate the compatibility with the temporary adhesion process. Most colorless PI films studied were found to be incompatible. Additionally, no correlation between σ_peel and PI structure was observed, making it challenging to identify the structural factors influencing σ_peel control. Surprisingly, a strong correlation was observed between σ_peel and CTE of the PI films, suggesting that the observed solid–solid lamination is closely linked to the unexpectedly high surface mobility of the PI films. The laminate using CpODA(90);BzDAxx(10)/TFMB copolymer exhibited suitable adhesion strength for the temporary adhesion process, while meeting other target properties. The modified one-pot polymerization method significantly contributed to the development of colorless PIs suitable for plastic substrates. Full article

The decommissioning and dismantling of nuclear research reactors can lead to a large amount of low- and intermediate-level radioactive waste. For repositories, the materials must be kept confined and safety must be ensured for extended time spans. Waste is encapsulated in concrete, which leads to alkaline conditions with pH values of 12 and higher. This can be advantageous for some radionuclides due to their precipitation at high pH. For other materials, such as reactive metals, however, it can be disadvantageous because it might foster their corrosion. The Studsvik R2 research reactor contained an AlMg3.5 alloy with a composition close to that of commercial Al5154 for its core internals and the reactor tank. Aluminum corrosion is known to start rapidly due to the formation of an oxidation layer, which later functions as natural protection for the surface. The corrosion can lead to pressure build-up through the accompanied production of hydrogen gas. This can lead to cracks in the concrete, which can be pathways for radioactive nuclides to migrate and must therefore be prevented. In this study, unirradiated rod-shaped samples were cut from the same material as the original reactor tank manufacture. They were embedded in concrete with elevated water–cement ratios of 0.7 compared to regular commercial concrete (ca. 0.45) to ensure water availability throughout all of the experiments. The sample containers were stored in pressure vessels with attached high-definition pressure gauges to read the hydrogen-induced pressure build-up. A second set of samples were exposed in simplified artificial cement–water to study similarities in corrosion characteristics between concrete and cement–water. Additionally, the samples were exposed to concrete and cement–water in free-standing sample containers for deconstructive examinations. In concrete, the corrosion rates started extremely high, with values of more than 10,000 µm/y, and slowed down to less than 500 µm/y after 2000 h, which resulted in visible channels inside the concrete. In the cement–water, the samples showed similar behavior after early fluctuations, most likely caused by the surface coverage of hydrogen bubbles. These trends were further supported by mass loss evaluations. Full article

Currently, most studies on slope stability either neglect or consider only one of the two critical factors—rainfall conditions and crack state—that influence the stability of recent landslides. To address this limitation, eleven parameters, including slope height, internal friction angle, cohesion, rainfall conditions, and crack state, were selected as evaluation indexes. GeoStudio software 2018 R2 was also used to simulate the slope safety factor under various parameters, and 363 datasets were obtained. The eXtreme Gradient Boosting–Particle Swarm Optimization–Support Vector Regression (XGBoost–PSO–SVR) model was employed to train the simulation results and construct a predictive model. The MSE of XGBoost–PSO–SVR when compared with the MSE of the single-machine methods of XGBoost and PSO–SVR is reduced by 71.9% and 57.8%, respectively. Furthermore, when compared with four single-machine models—Decision Tree (DT), Naive Bayes (NB), Random Forest (RF), and K-Nearest Neighbors (KNN)—the XGBoost–PSO–SVR model had the smallest MSE of 0.0016 and the largest R² of 0.9919. Thus, the XGBoost–PSO–SVR model demonstrated superior training performance. The predicted safety factor for a recent landslide in Yongchun County, Fujian Province, China, during 4–7 November 2016 was 0.9658, which closely aligned with the actual conditions. This study could provide a new method for the stability prediction of recent landslides based on various factors, such as rainfall conditions and crack state. Full article

Concrete bridge cracks are critical indicators for maintenance planning. Traditional visual inspections are often subjective, labor-intensive, and time-consuming, requiring close-range access by inspectors. In contrast, UAV-based remote sensing, combined with advanced image processing, offers a more efficient and accurate solution. This study proposes an enhanced crack detection method combining Laplacian of Gaussian (LoG) filtering and Otsu thresholding to improve segmentation accuracy through background noise suppression. The proposed approach extracts key crack characteristics—including area, length, centroid, and main direction—enabling precise damage assessment. Experimental validation on a real bridge dataset demonstrates significant improvements in detection accuracy. The method provides a reliable tool for automated structural health monitoring, supporting data-driven maintenance decisions. Full article

China has a vast number of infrastructure projects, with concrete structures accounting for the majority. To achieve the rapid and effective reinforcement and renovation of existing engineering structures, this paper proposes a novel approach for the rapid strengthening of concrete beams: an external prestressed reinforcement method applied to the side facade. To investigate the effectiveness of this new reinforcement method, we used three ordinary concrete beams serving as control specimens without prestress application, nine beams reinforced using traditional external prestressing, and nine beams reinforced with external prestressing applied to the side facade. The results indicated that, in comparison to the control beam and depending on the initial prestress level, the ultimate bearing capacity of the concrete beams reinforced with traditional external prestressing increased by 152% to 155%. Additionally, for the concrete beams reinforced with external prestressing on the side face, the ultimate bearing capacity improved by 53% to 61%. Both the cracking load and yield load of the reinforced concrete significantly increased, thereby enhancing the overall working performance. Based on the finite element simulation results, it can be observed that the simulation calculation outcomes aligned closely with the experimental test results. Full article

Material scientists face a critical challenge in characterizing the mesoscopic damage evolution of concrete under tensile loading, as traditional experimental and theoretical approaches struggle to resolve the complexities of its multiphase heterogeneous structure. This study addresses this gap by employing the Discrete Element Method (DEM) with PFC2D to model concrete’s mesoscopic cracking, integrating aggregates, mortar, interfacial transition zones (ITZ), and pores. Through parameter calibration against experimental data, uniaxial tensile simulations reveal how aggregate percentages (30–45%) and pore percentages (1–6%) influence crack propagation and tensile strength. Specifically, when the aggregate percentage increased from 30% to 40%, the peak tensile strength decreased by 26%, while increasing from 40% to 45% led to a recovery in strength. With porosity increasing from 2% to 4%, the peak strength dropped by approximately 3%, and further to 6% caused a 14% reduction, demonstrating the quantitative impact of microstructural parameters on concrete performance. Simulation results align closely with experimental data, validating DEM’s efficacy in modeling mesoscopic cracking. This work provides a mesoscopic theoretical foundation for optimizing concrete’s tensile properties and underscores the need to incorporate realistic mesoscopic features in future simulations. Full article