Search Results (1,859)

Alkyd resins are among the most common coatings used for exterior wood joinery. In Romania, solvent-borne alkyd coatings are widely used to finish wood. The study aims to compare the performance after 7 years of outdoor exposure of two types of alkyd coatings, a semi-transparent brown stain with micronized pigments (Alk1) and an opaque white enamel (Alk2), applied directly on wood or wood pre-treated with three types of resins: acryl-polyurethane (R1), epoxy (R2), and alkyd-polyurethane (R3). Fir (Abies alba) wood served as the substrate. Cracking, coating adhesion, and biological degradation were periodically assessed through visual inspection and microscopy. Additionally, a cross-cut test was performed, and the loss of coating on the directly exposed upper faces was measured using ImageJ. The results indicated that resin pretreatments somewhat reduced cracking but negatively affected coating adhesion after long-term exposure. All samples pretreated with resins and coated with Alk1 lost more than 50% (up to 78%) of the original finishing film by the end of the test. In comparison, coated control samples lost less than 50%. The Alk2 coating exhibited a film loss between 2% and 12%, compared to an average loss of 9% for the coated control. Overall, samples pretreated with alkyd-polyurethane resin (R3) and coated with alkyd enamel (Alk2) demonstrated the best performance in terms of cracking, adhesion, and discoloration. Full article

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

Automated surface defect detection in steel manufacturing is pivotal for ensuring product quality, yet it remains an open challenge owing to the extreme heterogeneity of defect morphologies—ranging from hairline cracks and microscopic pores to elongated scratches and shallow dents. Existing approaches, whether classical vision pipelines or recent deep-learning paradigms, struggle to simultaneously satisfy the stringent demands of industrial scenarios: high accuracy on sub-millimeter flaws, insensitivity to texture-rich backgrounds, and real-time throughput on resource-constrained hardware. Although contemporary detectors have narrowed the gap, they still exhibit pronounced sensitivity–robustness trade-offs, particularly in the presence of scale-varying defects and cluttered surfaces. To address these limitations, we introduce MBY (MBDNet-Attention-YOLO), a lightweight yet powerful framework that synergistically couples the MBDNet backbone with the YOLO detection head. Specifically, the backbone embeds three novel components: (1) HGStem, a hierarchical stem block that enriches low-level representations while suppressing redundant activations; (2) Dynamic Align Fusion (DAF), an adaptive cross-scale fusion mechanism that dynamically re-weights feature contributions according to defect saliency; and (3) C2f-DWR, a depth-wise residual variant that progressively expands receptive fields without incurring prohibitive computational costs. Building upon this enriched feature hierarchy, the neck employs our proposed MultiSEAM module—a cascaded squeeze-and-excitation attention mechanism operating at multiple granularities—to harmonize fine-grained and semantic cues, thereby amplifying weak defect signals against complex textures. Finally, we integrate the Inner-SIoU loss, which refines the geometric alignment between predicted and ground-truth boxes by jointly optimizing center distance, aspect ratio consistency, and IoU overlap, leading to faster convergence and tighter localization. Extensive experiments on two publicly available steel-defect benchmarks—NEU-DET and PVEL-AD—demonstrate the superiority of MBY. Without bells and whistles, our model achieves 85.8% mAP@0.5 on NEU-DET and 75.9% mAP@0.5 on PVEL-AD, surpassing the best-reported results by significant margins while maintaining real-time inference on an NVIDIA Jetson Xavier. Ablation studies corroborate the complementary roles of each component, underscoring MBY’s robustness across defect scales and surface conditions. These results suggest that MBY strikes an appealing balance between accuracy, efficiency, and deployability, offering a pragmatic solution for next-generation industrial quality-control systems. Full article

Rapid pavement repair demands materials that combine accelerated strength gains, dimensional stability, long-term durability, and sustainability. However, finding materials or formulations that offer these balances remains a critical challenge. This study systematically evaluates two polymer-modified belitic calcium sulfoaluminate (CSA) concretes—CSAP (powdered polymer) and CSA-LLP (liquid polymer admixture)—against a traditional Type III Portland cement (OPC) control under both laboratory and realistic outdoor conditions. Laboratory specimens were tested for fresh properties, early-age and later-age compressive, flexural, and splitting tensile strengths, as well as drying shrinkage according to ASTM standards. Outdoor 5 × 4 × 12-inch slabs mimicking typical jointed plain concrete panels (JPCPs), instrumented with vibrating wire strain gauges and thermocouples, recorded the strain and temperature at 5 min intervals over 16 weeks, with 24 h wet-burlap curing to replicate field practices. Laboratory findings show that CSA mixes exceeded 3200 psi of compressive strength at 4 h, but cold outdoor casting (~48 °F) delayed the early-age strength development. The CSA-LLP exhibited the lowest drying shrinkage (0.036% at 16 weeks), and outdoor CSA slabs captured the initial ettringite-driven expansion, resulting in a net expansion (+200 µε) rather than contraction. Approximately 80% of the total strain evolved within the first 48 h, driven by autogenous and plastic effects. CSA mixes generated lower peak internal temperatures and reduced thermal strain amplitudes compared to the OPC, improving dimensional stability and mitigating restraint-induced cracking. These results underscore the necessity of field validation for shrinkage compensation mechanisms and highlight the critical roles of the polymer type and curing protocol in optimizing CSA-based repairs for durable, low-carbon pavement rehabilitation. Full article

Crack initiation, propagation, and slippage serve as the key mesoscopic mechanisms contributing to the deterioration of deep tunnel surrounding rocks. In this study, a secondary anisotropy of deep tunnels surrounding rocks was proposed: The axial-displacement constraint of deep tunnels forces cracks in the surrounding rock to initiate, propagate, and slip in planes parallel to the tunnel axial direction. These cracks have no significant effect on the axial strength of the surrounding rock but significantly reduce the tangential strength, resulting in the secondary anisotropy. First, the secondary anisotropy was verified by a hybrid stress–strain controlled true triaxial test of sandstone specimens, a CT 3D (computed tomography three-dimensional) reconstruction of a fractured sandstone specimen, a numerical simulation of heterogeneous rock specimens, and field borehole TV (television) images. Subsequently, a novel SSA (strain-softening and secondary anisotropy) constitutive model was developed to characterise the secondary anisotropy of the surrounding rock and developed using C++ into a numerical form that can be called by FLAC^3D (Fast Lagrangian Analysis of Continua in 3 Dimensions). Finally, effects of secondary anisotropy on a deep tunnel surrounding rock were analysed by comparing the results calculated by the SSA model and a uniform strain-softening model. The results show that considering the secondary anisotropy, the extent of strain-softening of the surrounding rock was mitigated, particularly the axial strain-softening. Moreover, it reduced the surface displacement, plastic zone, and dissipated plastic strain energy of the surrounding rock. The proposed SSA model can precisely characterise the objectively existent secondary anisotropy, enhancing the accuracy of numerical simulations for tunnels, particularly for deep tunnels. Full article

This article provides a comprehensive overview of recent studies concerning laser heat treatment (LHT) of structural and tool steels, with particular attention to the 21NiCrMo2 steel used for carburized gear wheels. Analysis includes the influence of critical laser processing conditions—including power output, motion speed, spot size, and focusing distance—on surface microhardness, hardening depth, and microstructure development. The findings indicate that the energy density is the dominant factor that affects the outcomes of LHT. Optimal results, in the form of a high surface microhardness and a sufficient depth of hardening, were achieved within the energy density range of 80–130 J/mm², allowing for martensitic transformation while avoiding defects such as melting or cracking. At densities below 50 J/mm², incomplete hardening occurred with minimal microhardness improvement. On the contrary, densities exceeding 150–180 J/mm² caused surface overheating and degradation. For carburized 21NiCrMo2 steel, the most effective parameters included 450–1050 W laser power, 1.7–2.5 mm/s scanning speed, and 2.0–2.3 mm beam diameter. The review confirms that process control through energy-based parameters allows for reliable prediction and optimization of LHT for industrial applications, particularly in components exposed to cyclic loads. Full article

The cement sheath is critical for ensuring the long-term safety and operational efficiency of oil and gas wells. However, complex geological conditions and operational stresses during production can induce cement sheath deterioration and cracking, leading to reduced zonal isolation, diminished hydrocarbon recovery, and elevated operational expenditures. This study investigates the development of a novel microbial self-healing well cement slurry system, employing fly ash as microbial carriers and sustained-release microcapsules encapsulating calcium sources and nutrients. Systematic evaluations were conducted, encompassing microbial viability, cement slurry rheology, fluid loss control, anti-channeling capability, and the mechanical strength, permeability, and microstructural characteristics of set cement stones. Results demonstrated that fly ash outperformed blast furnace slag and nano-silica as a carrier, exhibiting superior microbial loading capacity and viability. Optimal performance was observed with additions of 3% microorganisms and 3% microcapsules to the cement slurry. Microscopic analysis further revealed effective calcium carbonate precipitation within and around micro-pores, indicating a self-healing mechanism. These findings highlight the significant potential of the proposed system to enhance cement sheath integrity through localized self-healing, offering valuable insights for the development of advanced, durable well-cementing materials tailored for challenging downhole environments. 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

This study evaluates the influence of fiber type, geometry, and interfacial behavior on the physical and mechanical performance of cementitious composites reinforced with recycled pulp from beverage cartons (RPBC), bamboo fiber (BF), and eucalyptus fiber (EF) as the sole reinforcing agents. The BF was rounded in shape and had the highest aspect ratio, while the ribbon-shaped EF exhibited the highest tensile strength index. The RPBC fibers were fibrillated and the shortest, with a ribbon shape. Flexural strength results showed that RPBCC achieved a maximum strength that was 47.6% higher than the control specimen (0% fiber), outperforming both BF- and EF-reinforced counterparts. This superior performance is attributed to the higher fibrillation level of the ribbon-shaped RPBC fibers, which promoted better fiber–matrix bonding. As the fiber content increased, the bulk density of EFC and BFC decreased linearly, while RPBC composites showed only a modest decrease in density. Porosity steadily increased in EFC and BFC, whereas a non-linear trend was observed in RPBCC, likely due to its unique morphology and fibrillation. Conversely, EFC exhibited significantly higher maximum fracture toughness (3600 J/m² at 10 wt.%) compared to PBFCC (1600 J/m² at 14 wt.%) and BFC (1400 J/m² at 14 wt.%). This enhancement is attributed to extensive fiber pullout mechanisms and increased energy absorption during crack propagation. Overall, all composite types demonstrated flexural strength values above 4 MPa, placing them in the Grade I category. Those reinforced with 10–14% RPBC exhibited strengths of 11–12 MPa, categorizing them as Grade II according to ASTM C1186-02. Full article

Wireless sensor networks (WSNs) are used for data acquisition and transmission in unmanned surface vessels (USVs). However, the openness of wireless networks makes USVs highly susceptible to false data injection (FDI) attacks during data transmission, which affects the sensors’ ability to receive real data and leads to decision-making errors in the control center. In this paper, a novel dynamic data encryption method is proposed whereby data are encrypted prior to transmission and the key is dynamically updated using historical system data, with a view to increasing the difficulty for attackers to crack the ciphertext. At the same time, a dynamic relationship is established among ciphertext, key, and auxiliary encrypted ciphertext, and an attack detection scheme based on dynamic encryption is designed to realize instant detection and localization of FDI attacks. Further, an $H_{\infty }$ fusion filter is designed to filter external interference noise, and the real information is estimated or restored by the weighted fusion algorithm. Ultimately, the validity of the proposed scheme is confirmed through simulation experiments. Full article

This paper evaluates the synergistic effect of polyvinyl alcohol (PVA) fibers and nanosilica (nS) on the mechanical behavior and deformation properties of engineered cementitious composites (ECCs). ECCs have gained a reputation for high ductility, crack control, and strain-hardening behavior. Nevertheless, the next step is to improve their performance even more through nano-modification and fine-tuning of fiber dosage—one of the major research directions. In the experiment, six types of ECC mixtures were made by maintaining constant PVA fiber content (0.5, 1.0, 1.5, and 2.0%), while the nanosilica contents were varied (0, 1, 2, 3, and 5%). Stress–strain tests carried out in the form of compression, together with unrestrained shrinkage measurement, were conducted to test strength, strain capacity, and resistance to deformation, which was highest at 80 MPa, recorded in the concrete with 2% nS and 0.5% PVA. On the other hand, the mixture of 1.5% PVA and 3% nS had the highest strain result of 2750 µm/m, which indicates higher ductility. This is seen to be influenced by refined microstructures, improved fiber dispersion, and better fiber–matrix interfacial bonding through nS. In addition to these mechanical modifications, the use of nanosilica, obtained from industrial byproducts, provided the possibility to partially replace Portland cement, resulting in a decrease in the amount of CO₂ emissions. In addition, the enhanced crack resistance implies higher durability and reduced long-term maintenance. Such results demonstrate that optimized ECC compositions, including nS and PVA, offer high performance in terms of strength and flexibility as well as contribute to the sustainability goals—features that will define future eco-efficient infrastructure. Full article

The increasing demand for sustainable construction materials has driven research into low-carbon geopolymers that mitigate both cement-related emissions and plastic and glass waste accumulation. This study explores the development of geopolymer concrete incorporating fly ash (FA), slag (S), and FA + S blends, with 10% recycled crushed glass (RCG) and recycled plastic waste (RPW) as partial coarse aggregate replacements. Compressive strength testing revealed that FA + S-based geopolymers (25FA + S) with 100% ordinary Portland cement (OPC) replacement achieved a 7-day strength of 24.6 MPa, representing a 98% improvement over control specimens. Slag-based geopolymers demonstrated water absorption properties comparable to OPC, indicating enhanced durability. Microstructural analyses using SEM, XRD, and EDS confirmed the formation of a dense aluminosilicate matrix, with slag promoting FA reactivity and reinforcing interfacial transition zone (ITZ). These effects contributed to superior mechanical performance and water resistance. Despite minor shrinkage-induced cracking, full OPC replacement with S or FA + S geopolymers outperformed control specimens, consistently exceeding the target strength of 15 MPa required for low-impact, single-story housing applications within seven days. These findings underscore the potential of geopolymer systems for rapid and sustainable construction, offering an effective solution for reducing carbon footprints and repurposing industrial waste. Full article

Some chemical reactors exhibit coupled dynamics with multiple equilibrium points and strong nonlinearities. The accurate modeling of these dynamics is crucial to optimal control and increasing the reactor’s economic performance. While neural networks can effectively handle complex nonlinearities, they sacrifice interpretability. Alternatively, block-oriented Hammerstein–Wiener models and Koopman operator-based linear predictors combine nonlinear representation with linear dynamics, offering a gray-box identification approach. This paper comprehensively reviews recent advancements in both the Hammerstein–Wiener and Koopman operator methods and benchmarks their accuracy against neural network-based approaches to modeling a large-scale industrial Fluid Catalytic Cracking fractionator. Furthermore, Monte Carlo simulations are employed to validate performance under varying signal-to-noise ratios. The results demonstrate that the Koopman bilinear model significantly outperforms the other methods in terms of accuracy and robustness. Full article

This paper presents a UAV-based building crack real-time detection system that integrates an improved YOLOv8 algorithm with Linear Active Disturbance Rejection Control (LADRC). The system is equipped with a high-resolution camera and sensors to capture high-definition images and height information. First, a trajectory tracking controller based on LADRC was designed for the UAV, which uses a linear extended state observer to estimate and compensate for unknown disturbances such as wind interference, significantly enhancing the flight stability of the UAV in complex environments and ensuring stable crack image acquisition. Secondly, we integrated Convolutional Block Attention Module (CBAM) into the YOLOv8 model, dynamically enhancing crack feature extraction through both channel and spatial attention mechanisms, thereby improving recognition robustness in complex backgrounds. Lastly, a skeleton extraction algorithm was applied for the secondary processing of the segmented cracks, enabling precise calculations of crack length and average width and outputting the results to a user interface for visualization. The experimental results demonstrate that the system successfully identifies and extracts crack regions, accurately calculates crack dimensions, and enables real-time monitoring through high-speed data transmission to the ground station. Compared to traditional manual inspection methods, the system significantly improves detection efficiency while maintaining high accuracy and reliability. 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