Search Results (252)

Glazed components in ancient Chinese architecture hold profound historical and cultural value. However, over time, environmental erosion, physical impacts, and human disturbances gradually lead to various forms of damage, severely impacting the durability and stability of the buildings. Therefore, preventive protection of glazed components is crucial. The key to preventive protection lies in the early detection and repair of damage, thereby extending the component’s service life and preventing significant structural damage. To address this challenge, this study proposes a Restoration-Scale Identification (RSI) method that integrates depth information. By combining RGB-D images acquired from a depth camera with intrinsic camera parameters, and embedding a Convolutional Block Attention Module (CBAM) into the backbone network, the method dynamically enhances critical feature regions. It then employs a scale restoration strategy to accurately identify damage areas and recover the physical dimensions of glazed components from a global perspective. In addition, we constructed a dedicated semantic segmentation dataset for glazed tile damage, focusing on cracks and spalling. Both qualitative and quantitative evaluation results demonstrate that, compared with various high-performance semantic segmentation methods, our approach significantly improves the accuracy and robustness of damage detection in glazed components. The achieved accuracy deviates by only ±10 mm from high-precision laser scanning, a level of precision that is essential for reliably identifying and assessing subtle damages in complex glazed architectural elements. By integrating depth information, real scale information can be effectively obtained during the intelligent recognition process, thereby efficiently and accurately identifying the type of damage and size information of glazed components, and realizing the conversion from two-dimensional (2D) pixel coordinates to local three-dimensional (3D) coordinates, providing a scientific basis for the protection and restoration of ancient buildings, and ensuring the long-term stability of cultural heritage and the inheritance of historical value. Full article

This paper focuses on the scoring-wheel cutting process for circular structures of OLED display panels, conducting in-depth research through an experiment–analysis–optimization system. Based on the Taguchi experimental design, a three-factor, five-level experiment is conducted, with the blade wheel angle (A), cutting speed (B), and pressure (C) set as influencing factors, and the scratch depth (h), width (w), median crack depth (l), and transverse crack width (d) set as evaluation indicators. The experiments are carried out using a self-developed dicing-wheel cutting device, and the morphology, roughness, and hardness of the cutting surface and cross-section are characterized by means of ultra-depth-of-field microscopy, laser confocal microscopy, microhardness tester, and other equipment. The research shows that the order of factors affecting the cutting quality is as follows: A > C > B. Through the analysis of morphology and crack characteristics, it is determined that the optimal parameter combination is a dicing wheel angle of 130°, a cutting speed of 20 mm/s, and a pressure of 11 N. The verification results indicate that this combination can reduce surface roughness, stabilize hardness, and realize efficient and precise processing of special-shaped structures in OLED display panels, providing strong theoretical and technical support for industrial process optimization. Full article

Preventive maintenance treatments are widely applied to asphalt pavements to mitigate deterioration and extend service life. This study evaluated four common technologies: a high-elasticity ultra-thin overlay, an Stone Mastic Asphalt (SMA)-10 thin overlay, micro-surfacing (MS-III), and a chip seal. Laboratory testing focused on skid resistance, surface texture, and low-temperature cracking resistance. Skid resistance was measured with a tire–pavement dynamic friction analyzer under controlled load and speed, while surface macrotexture was assessed using a laser scanner. Low-temperature cracking resistance was determined through three-point bending beam tests at −10 °C. The results showed that chip seal achieved the highest initial friction and texture depth, immediately enhancing skid resistance but exhibiting rapid texture loss and gradual friction decay. Micro-surfacing also demonstrated good initial skid resistance but experienced a sharp reduction of over 30% due to fine aggregate polishing. By contrast, the high-elastic ultra-thin overlay and SMA thin overlay provided more stable skid resistance, lower long-term friction loss, and excellent crack resistance. The polymer-modified ultra-thin overlay achieved the highest low-temperature bending strain ≈40% higher than untreated pavement, indicating superior crack resistance, followed by the SMA thin overlay. Micro-surfacing with a chip seal layer only slightly improved low-temperature performance. Overall, the high-elastic ultra-thin overlay proved to be the most balanced preventive maintenance option under heavy-load traffic and cold climate conditions, combining durable skid resistance with enhanced crack resistance. Full article

Soil moisture is one of the key hydrologic components indicating the performance of landfill final covers. Conventional compacted clay (CC) covers and evapotranspiration (ET) covers often suffer from moisture-induced stresses, such as desiccation cracking and irreversible hydraulic conductivity. Engineered turf (EnT) cover systems have been introduced recently as an alternative; however, their field-scale moisture distribution behavior remains unexplored. This study investigates and compares the soil moisture distribution characteristics of EnT, ET, and CC landfill covers at a shallow depth using one year of field-monitored data in a humid subtropical region. Three full-scale test Sections (3 m × 3 m × 1.2 m) were constructed side by side and instrumented with moisture sensors at a depth of 0.3 m. Distributional characteristics of moisture were evaluated with descriptive statistics, goodness-of-fit tests such as Shapiro–Wilk (SW) and Anderson–Darling (AD), Gaussian probability density functions, Q–Q plots, and standard-normal transformations. Results revealed that Shapiro–Wilk (W = 0.75–0.92, p < 0.001) and Anderson–Darling $(A^2=1.63\times {10}^3\mathrm{to}6.31\times {10}^3,p<0.001)$ tests rejected normality for every cover, while Levene’s test showed unequal variances between EnT and the other covers $(F>5.4\times {10}^4,$$p<0.001)$ but equivalence between CC and ET (F = 0.23, p = 0.628). EnT cover exhibited the narrowest moisture envelope $(95\%\mathrm{range}=0.156\mathrm{to}0.240{\mathrm{m}}^3/{\mathrm{m}}^3;\mathrm{CV}=10.6\%)$, whereas ET and CC covers showed markedly broader distributions (CV = 38.6 % and 33.3 %, respectively). These findings demonstrated that EnT cover maintains a more stable shallow soil moisture profile under dynamic weather conditions. Full article

The development of sustainable and energy-efficient asphalt pavements is essential to address the growing demand for climate-neutral transportation infrastructure. This study investigates the structural design and functional performance of low rolling resistance asphalt mixtures utilizing reclaimed asphalt pavement (RAP) and warm mix asphalt (WMA) technologies. Ten mixtures with WMA additive—including asphalt concrete (AC) and stone mastic asphalt (SMA) with and without RAP—were evaluated for volumetric and mechanical performance. Laboratory results show that RAP addition did not compromise compaction nor indirect tensile strength ratio (ITSR), and in some cases improved these properties. SMA and SMA RAP-modified mixtures achieved the highest resistance to rutting (as low as 5.0% rut depth), while AC and SMA mixtures both demonstrated low rolling resistance (coefficients of energy loss 0.00604–0.00636). Resistance to low-temperature cracking was strong for all mixtures, with thermal stress restrained specimen test (TSRST) fracture temperatures ranging from −32.8 °C to −36.0 °C. SMA mixtures generally exhibited superior resistance to fatigue (up to 63 με at 1 million cycles). Overall, three asphalt mixtures with different particle size distribution containing 14% RAP and a WMA additive (SMA 8 S_1 R, SMA 8 S_3 R, and AC 11 VS_2 R) demonstrated the best balance of rolling resistance, durability, and circularity, and are recommended for field trials to support climate-neutral and sustainable road infrastructure. These results encourage broader adoption of circular practices in road infrastructure projects, contributing to lower emissions and life-cycle costs. Full article

This study evaluated the fatigue performance of nitrided H13 steel with and without a compound layer (CL), using two nitrogen potentials (K_N = 0.8, designated as LN, and K_N = 2.0, designated as HN). Fine particle peening (FPP) was applied prior to gas nitriding to introduce a refined microstructure and compressive residual stress (CRS) in the peened zone. After gas nitriding at 540 °C for 8 h, the refined structure remained on the outermost layer of all samples, regardless of the nitrogen potential. A CL primarily composed of Fe₃N formed on the external surface of the HN sample, whereas the LN sample remained free of CL. A higher K_N promoted CL formation and slightly increased the case depth in the HN sample compared to the LN sample. Fatigue cracks initiated at the external surface of the H13 steel substrate (SB). Overall, the LN and HN samples exhibited similar residual stress fields and, consequently, comparable fatigue performance. In the high-cycle fatigue regime, fatigue cracks originated from subsurface inclusions, resulting in significantly improved fatigue strength and life for both the LN and HN samples compared to the SB sample. Under cyclic stresses at or above 1100 MPa, the crack initiation site in the HN sample tended to shift from subsurface inclusions to the external surface. Throughout the fatigue tests, no multi-cracking or spalling of the CL was observed in the HN sample, regardless of the cyclic stress. Full article

Ensuring the structural safety of components or facilities is essential for the smooth operation of industrial production and transportation. As a key index to evaluate structural health, the crack depth detection method has evolved from the early single physical field detection to the contemporary multi-physical field collaborative artificial intelligence algorithm. This paper presents a systematic review of crack depth detection technology under specific engineering conditions, such as those found in roads, train tracks, and engine blades. The framework categorizes and reviews detection technology according to detection principles, including physical principles, model inversion, hybrid methods, and evaluation indicators such as detection accuracy, speed, and cost. The paper compares various detection technologies, highlighting their advantages and limitations in real-world applications. The analysis reveals key challenges, which include complex environmental interference, the detection of microcracks and deep cracks, and the balance between accuracy and cost. Addressing these challenges is imperative to improving the reliability and generalization of detection technology. This paper proposes future research directions focusing on integrating multi-physical field detection with artificial intelligence, utilizing AI’s robust capabilities to develop more advanced methods for detecting crack depth. Full article

The Jiaoshiba area, as an important production capacity contribution block for the Fuling shale gas field, is of great significance for its long-term stable production. This study is based on continuous coring, and uses methods such as whole-rock mineral analysis, porosity and permeability analysis, gas content analysis, and organic geochemistry to systematically analyze the influencing factors of reservoir properties and gas content in the studied interval. Combined with the variation law of TOC and other parameters with depth, the target reservoir is comprehensively evaluated, and the evaluation results are verified based on actual production data. The results show that the influence of minerals on permeability is very weak, and cracks can greatly improve permeability, but their contribution to porosity is not significant. Porosity has a certain impact on gas content, but it is not the main controlling factor. The pores related to quartz (organic silicon) are mostly organic pores, which host a large amount of shale gas, while clay minerals are not conducive to the occurrence of shale gas. Organic matter (OM) maturity contributes more to porosity than OM abundance, but OM abundance has a stronger impact on gas content than its maturity. The research intervals can be divided into four categories: Class I (①–③) is the best, followed by Class II (⑦–⑨); Class III (④–⑥) is poor, and Class IV (top, non-gas-bearing layer) is the worst. Full article

The resistivity imaging system is specifically designed for the precise measurement of resistivity distributions within drilled columnar core samples. Its coaxial symmetric configuration enables the non-destructive characterization of electrical properties, with broad applications in oil and gas exploration, reservoir evaluation, and geological research. By integrating a ring return electrode and full-circumference electrode arrays, the system can acquire core-scale resistivity data in conductive media environments. The self-developed imaging software employs advanced processing algorithms—including depth correction, amplitude normalization, and image enhancement—to transform raw resistivity measurements into high-resolution surface imaging maps. Experimental results demonstrate that the system can resolve features such as cracks with a minimum width of 0.5 mm and pores with a minimum inner diameter of 0.4 mm in granite core, providing a novel technical approach for the fine-scale characterization of core materials. Full article

The article presents a new AM (Additive Manufacturing) process development, necessary to repair parts made from Aluminum 6061 material, with T6 treatment. The laser Directed Energy Deposition (DED) and Extreme High-Speed Directed Energy Deposition (EHLA) capabilities are evaluated for repairing Al large components. To optimize the process parameters, single-track depositions were analyzed for both laser-powder DED (feed rate of 2 m/min) and EHLA (feed rate 20 m/min) for AlSi10Mg and Al6061 powders. The cross-sections of single tracks revealed the bonding characteristics and provided laser-powder DED, a suitable parameter selection for the repair. Three damage types were identified on the Al component to define the specification of the repair process and to highlight the capabilities of laser-powder DED and EHLA in repairing intricate surface scratches and dents. Our research is based on variation of the powder mass flow and beam power, studying the influence of these parameters on the weld bead geometry and bonding quality. The evaluation criteria include bonding defects, crack formation, porosity, and dilution zone depth. The bidirectional path planning strategy was applied with a fly-in and fly-out path for the hatching adjustment and acceleration distance. Samples were etched for a qualitative microstructure analysis, and the HV hardness was tested. The novelty of the paper is the new process parameters for laser-powder DED and EHLA deposition strategies to repair large Al components (6061 T6), using AlSi10Mg and Al6061 powder. Our experimental research tested the defect-free deposition and the compatibility of AlSi10Mg on the Al6061 substrate. The readers could replicate the method presented in this article to repair by laser-powder DED/EHLA large Al parts and avoid the replacement of Al components with new ones. Full article

The deformation characteristics of the surrounding rock in tunnel groups are considered critical for the design of support structures and the assurance of the long-term safety of deep-buried diversion tunnels. The deformation behavior of surrounding rock in tunnel groups was investigated to guide structural support design. Field tests and numerical simulations were performed to analyze the distribution of ground stress and the ground reaction curve under varying conditions, including rock type, tunnel spacing, and burial depth. A solid unit–structural unit coupled simulation approach was adopted to derive the two-liner support characteristic curve and to examine the propagation behavior of concrete cracks. The influences of surrounding rock strength, reinforcement ratio, and secondary lining thickness on the bearing capacity of the secondary lining were systematically evaluated. The following findings were obtained: (1) The tunnel group effect was found to be negligible when the spacing (D) was ≥65 m and the burial depth was 1600 m. (2) Both P_0.3 and P_max of the secondary lining increased linearly with reinforcement ratio and thickness. (3) For surrounding rock of grade III (IV), 95% u_lim and 90% u_lim were found to be optimal support timings, with secondary lining forces remaining well below the cracking stress during construction. (4) For surrounding rock of grade V in tunnels with a burial depth of 200 m, 90% u_lim is recommended as the initial support timing. Support timings for tunnels with burial depths between 400 m and 800 m are 40 cm, 50 cm, and 60 cm, respectively. Design parameters should be adjusted based on grouting effects and monitoring data. Additional reinforcement is recommended for tunnels with burial depths between 1000 m and 2000 m to improve bearing capacity, with measures to enhance impermeability and reduce external water pressure. These findings contribute to the safe and reliable design of support structures for deep-buried diversion tunnels, providing technical support for design optimization and long-term operation. Full article

Structural cracks are internal distresses that cannot be observed from pavement surfaces. However, the existing evaluation methods for asphalt pavement structures lack the consideration of these cracks, which are crucial for accurate pavement assessment and effective maintenance planning. This study develops a novel framework combining a three-dimensional (3D) ground penetrating radar (GPR) and finite element modeling (FEM) to evaluate the severity of structural cracks. First, the size and depth development of structural cracks on a four-layer asphalt pavement were determined using the 3D GPR. Then, the range of influence of the structural crack on structural bearing capacity was analyzed based on 3D FEM simulation model. Structural cracks have a distance-dependent diminishing influence on the deflection in the horizontal direction, with the most pronounced effects within a 20-cm width zone surrounding the cracks. Finally, two indices have been proposed: the pavement structural crack index (PSCI) to assess the depth of crack damage and the structural crack reflection ratio (SCRR) to evaluate surface reflection. Besides, PSCI and SCRR are used to classify the severities of structural cracks: none, low, and high. The threshold between none/low damage is a structural crack damage rate of 0.19%, and the threshold between low/high damage is 0.663%. An experiment on a 132-km expressway indicated that the proposed method achieved 94.4% accuracy via coring. The results also demonstrate the strong correlation between PSCI and pavement deflection (R² = 0.92), supporting performance-based maintenance strategies. The results also demonstrate the correlation between structural and surface cracks, with 65.8% of the cracked sections having both structural and surface cracks. Full article

This study examines fatigue crack growth behavior in induction-hardened S38C axle steel with a gradient microstructure. High-frequency three-point bending fatigue tests were conducted to evaluate crack growth rates (da/dN) across three depth-defined regions: a hardened layer, a heterogeneous transition zone, and a normalized core. Depth-resolved da/dN–ΔK relationships were established, and Paris Law parameters were extracted. The surface-hardened layer exhibited the lowest crack growth rates and flattest Paris slope, while the transition zone showed notable scatter due to microstructural heterogeneity and residual stress effects. These findings provide experimental insight into the fatigue performance of gradient-structured axle steels and offer guidance for fatigue life prediction and inspection planning. Full article

The integration of fiber-reinforced cementitious composites (FRCCs) with fiber-reinforced polymer (FRP) bars represents a significant advancement in concrete technology, aimed at enhancing the structural performance of reinforced concrete elements. The incorporation of fibers into cementitious composites markedly improves their mechanical properties, including tensile strength, ductility, compressive strength, and flexural strength, by effectively bridging cracks and optimizing load distribution. Furthermore, FRP bars extend these properties with their high tensile strength, lightweight characteristics, and exceptional corrosion resistance, rendering them ideal for applications in aggressive environments. In recent years, there has been a notable increase in interest from the engineering research community regarding this topic, primarily to solve the issues of aging and deteriorating infrastructure. Researchers have conducted extensive investigations into the structural performance of FRCC and FRP composite systems. This paper presents a systematic literature review that surveys experimental and analytical studies, findings, and emerging trends in this field. A comprehensive search on the Web of Science identified 40 relevant research articles through a rigorous selection process. Key factors of structural performance, such as bond behavior, flexural behavior, ductility performance assessments, shear and torsional performance, and durability evaluations, have been documented. This review aims to provide an in-depth understanding of the structural performance of these innovative composite materials, paving the way for future research and development in construction materials technology. Full article

Pavement performance models are considered a key element in pavement management systems since they can predict the future condition of pavements using historical data. Several indicators are used to evaluate the condition of pavements (such as the pavement condition index, rutting depth, and cracking severity), and the international roughness index (IRI), which is the most widely employed worldwide. This study aimed to develop an accurate IRI prediction model. Ten prediction methods were trained on a dataset of 35 independent variables. The performance of the methods was compared, and the light gradient boosting machine was identified as the best-performing method for IRI prediction. Then, the SHAP was synchronized with the best-performing method to prioritize variables based on their relative influence on IRI. The results suggested that initial IRI, mean annual temperature, and the duration between data collections had the strongest relative influence on IRI prediction. Another objective of this study was to determine the optimal uncertainty model for IRI prediction. In this regard, 12 uncertainty models were developed based on different conformal prediction methods. Gray relational analysis was performed to identify the optimal uncertainty model. The results showed that Minmax/80 was the optimal uncertainty model for IRI prediction, with an effective coverage of 93.4% and an average interval width of 0.256 m/km. Finally, a further analysis was performed on the outcomes of the optimal uncertainty model, and initial IRI, duration, annual precipitation, and a few distress parameters were identified as uncertain. The results of the framework indicate in which situations the predicted IRI may be unreliable. Full article