Search Results (1,781)

Surface strain measurements on carbon fiber-reinforced polymer (CFRP) structures using bonded strain gauges are often systematically underestimated due to strain transfer effects associated with the surface resin-rich layer. To investigate this issue, comparative bending experiments were performed on steel and CFRP beams, where the steel beam served as a reference structure with negligible strain transfer loss under equal-curvature conditions. An equal-curvature bending framework was established to ensure identical bending curvature at the strain measurement location for both materials, thereby eliminating the influence of material stiffness on global deformation. In parallel, controlled surface polishing was employed to precisely regulate the thickness of the resin-rich layer on CFRP specimens, enabling systematic evaluation of its influence on strain transfer behavior. Experimental results under equal-curvature conditions reveal a stable strain underestimation in CFRP surface measurements, with an average strain transfer coefficient of approximately 0.968. Furthermore, reducing the resin-rich layer thickness leads to a consistent increase in measured strain. Based on these observations, a practical strain correction model was established to improve the reliability and engineering applicability of surface strain measurements in CFRP structures. Full article

With the development of various emerging structures, concrete-filled steel tubular (CFST) columns have become critical load-bearing components in key infrastructures such as subways and underground utility tunnels. Accurately predicting their ultimate bearing capacity (N_u) is essential for guaranteeing structural safety. To address the limitations of traditional empirical formulas and code-based calculation approaches, this paper proposes a prediction model for ultimate bearing capacity based on the CatBoost algorithm optimized by Random Search. Furthermore, the marginal contribution of each key feature to the prediction results is measured through interpretability analysis. First, a database containing 438 CFST column ultimate bearing capacity test cases was established, with key parameters such as geometric dimensions and material properties as input variables. Second, the predictive performance of six machine learning algorithms—CatBoost, LightGBM, Random Forest (RF), Gradient Boosting (GB), K-Nearest Neighbors (KNN), and XGBoost—was compared. A five-fold cross-validation integrated with a Random Search strategy was employed for joint hyperparameter optimization. The results show that the optimized CatBoost model significantly outperforms other algorithms and conventional design codes, achieving a coefficient of determination (R²) as high as 0.99 and a root mean square error (RMSE) of 174.29 kN. Furthermore, the SHAP (Shapley Additive exPlanations) method was used to perform global and local interpretability analyses of the prediction model. This not only quantified the individual contribution and interaction effects of each feature parameter on the bearing capacity but also revealed that geometric parameters are the primary influencing factor. This finding confirms a high degree of consistency between the prediction mechanism of the data-driven model and classical mechanical theories, effectively validating the model’s reliability. This study provides an efficient and reliable tool for the optimal design and rapid evaluation of CFST columns and establishes a new data-driven paradigm for the design and reinforcement of key components in underground structures. Full article

In this work, kyanite-reinforced alumina ceramics were prepared using the prestress reinforcement method and the particle enhancement method. The effects of different preparation methods on the mechanical properties and microstructures of kyanite-reinforced alumina ceramics were investigated. The results showed that, compared to the pure alumina ceramic, the prestressed alumina ceramic (labeled as P-Al₂O₃) prepared by the prestress reinforcement method exhibited a significant improvement (31% higher than that of pure alumina) in flexural strength. This is mainly attributed to the fact that the compressive stress existing on the surface of P-Al₂O₃ inhibited crack propagation; therefore, the fracture energy and strength were increased. However, due to the numerous pores and cracks in the fracture surface caused by the decomposition reaction of kyanite, the alumina composites fabricated through the particle enhancement method (labeled C-Al₂O₃) displayed lower flexural strength and hardness than those with P-Al₂O₃. Additionally, an increase in kyanite content led to a decrease in properties such as flexural strength, Vickers hardness, density, the elastic modulus, and the thermal expansion coefficient, while resulting in an increase in porosity. This work demonstrates the importance of using a suitable preparation method aligned with the specific composite. Full article

Long-fiber thermoplastic (LFT) materials are a versatile category of composite materials that can be directly compounded (LFT-D) in twin screw extruders and compression molded. Originating in the automotive sector, the LFT-D process is becoming increasingly attractive for other industries where low cycle times, lightweight performance and recyclability are required. The purpose of this work is to summarize mechanical properties and findings from the investigations into LFT-D process–microstructure–property relationships and present a design of experiments (DoE) study based on the current state of the art. Primary parameters from LFT-D compounding, screw speed, fiber roving amount and polymer throughput m_p are chosen as DoE factors. Polyamide 6 (PA6) is reinforced with a glass fiber (GF) mass fraction w_f between w_f = 20% and w_f = 60%. Tensile, flexural and impact properties are chosen as DoE output parameters, characterized and discussed in relation to the state of the art. The unique microstructure of LFT-D materials, especially the existence of a charge and flow area as well as the fiber migration, is considered in the discussion. All mechanical properties characterized have a linear relation to w_f. This study demonstrates the interactive relationship between the main factors and w_f, which significantly influences the mechanical properties. This dependence of w_f on the DoE factors is accounted for in advanced response contour plots proposed in this work. Parameter recommendations for the screw speed are reported by ranges of w_f and polymer throughput for the goal of maximum mechanical properties or low coefficient of variations. At w_f < 30% a low screw speed is recommended to improve most mechanical properties as well as the coefficient of variation. Full article

To address the lack of suitable glass systems for silicon nitride (Si₃N₄) surface metallization, which requires high wettability and thermal stability, and robust bonding between the copper layer and the ceramic substrate, a novel Bi₂O₃-TeO₂-B₂O₃-CuO glass system was developed. This study systematically investigated the influence of Bi₂O₃ concentration, glass properties, optimized paste composition, and brazing mechanism using phase analysis, microstructural characterization, particle size statistics, thermal analysis, and tensile testing. An optimal glass composition containing 20 mol% Bi₂O₃ was identified, exhibiting high thermal stability (ΔT = 224 °C) and a coefficient of thermal expansion of 9.63 × 10⁻⁶ °C⁻¹. At a brazing temperature of 750 °C, the glass demonstrated excellent wettability with a contact angle of 27°. A conductive paste comprising 94 wt% Cu and 6 wt% glass yielded a thick film with a minimum resistivity of 6.25 μΩ·cm and a maximum tensile strength of 25.2 MPa. Mechanism analysis revealed that the superior wettability drives the liquid glass phase to form a thin intermediate layer that significantly reinforces adhesion. These findings contribute to the research and development of subsequent novel glass systems with superior performance. Full article

Olive pomace biochar, obtained through the pyrolysis of lignocellulosic biomass, has emerged as a sustainable and multifunctional additive for polymer composites. Its physicochemical properties, including porosity, surface area, and electrical conductivity, can be tailored by controlling feedstock type and pyrolysis conditions. Although mechanical reinforcement and thermal stability improvements are well documented, the influence of biochar on surface-related properties such as wettability and contact angle remains insufficiently explored for environmentally relevant composite systems. In this study, epoxy-based composites containing biochar synthesized at 750 °C were evaluated in terms of their water interaction behavior by monitoring the evaporation dynamics of ultra-pure water droplets (10 μL, 0.055 mS/cm conductivity) at eight time intervals between 20 and 580 s using high-resolution digital microscopy. Image enhancement and segmentation were performed prior to Discrete Cosine Transform (DCT) analysis to describe droplet geometry in the frequency domain. Time-dependent variations in the standard deviations of DCT coefficients were optimized using the Bat Algorithm, resulting in mathematical models capable of accurately representing droplet evolution and surface–fluid interactions. The primary novelty of this study lies in the development of a hybrid experimental–computational framework that integrates droplet-based wettability measurements with signal-domain analysis and metaheuristic optimization. Unlike conventional studies focusing solely on material characterization, this approach establishes quantitative relationships between surface behavior and numerical descriptors derived from DCT and the Bat Algorithm. The proposed methodology provides a data-driven tool for predicting wettability trends in biochar-reinforced composites and supports the development of moisture-resistant materials for coatings, packaging, and thermal insulation applications within the context of sustainable composite design. Full article

This study investigates the multi-scale tribo–thermo–viscoelastic performance of a sustainable bio-based FormuLITE epoxy reinforced with single and hybrid carbon nanofillers (0.1 wt.% total loading) under dry sliding up to 50 N. Pin-on-disk tests at 10, 30, and 50 N showed a consistent reduction in contact pressure and wear volume in the order: neat epoxy > 0.1 CNT > 0.1 GNP > 0.1 ND > 0.1 CNT/GNP > 0.1 CNT/ND > 0.1 GNP/ND. At 50 N and 1500 m sliding distance, neat epoxy exhibited a wear volume of 13.43 mm³ and contact pressure of 13.4 N/cm², while the GNP/ND hybrid reduced wear to 4.86 mm³ and contact pressure to 6.2 N/cm², corresponding to reductions of 64% and 54%, respectively. The accelerating wear coefficient decreased from 2.9 × 10⁻⁶ to 8.5 × 10⁻⁷, confirming slower damage accumulation in hybrid systems. Time-dependent contact pressure analysis revealed reduced asymptotic intensity and suppressed mid-cycle pressure spikes, indicating enhanced tribolayer stability. Effective surface hardness increased from 0.18 GPa (neat epoxy) to 0.30 GPa (GNP/ND), while normalized wear decreased from 1.00 to 0.36. Enhanced damping behavior and improved thermal conductivity in hybrid systems promoted stress redistribution and minimized flash-temperature localization. An interfacial energy-partition framework calibrated to experimental wear data quantitatively linked effective driving pressure, tribofilm stabilization, and surface hardness to material removal. The results demonstrate that wear mitigation in sustainable bio-epoxy systems is governed by coupled mechanical, viscoelastic, and thermal energy redistribution, with GNP/ND hybrids providing the most stable tribological interface under severe sliding. The findings contribute to the development of durable and sustainable bio-epoxy composite systems for engineering applications, supporting broader goals of responsible material utilization and sustainable industrial innovation aligned with the United Nations Sustainable Development Goals (SDG 9 and SDG 12). Full article

The steel frame-shear wall composite system has excellent lateral resistance performance in prefabricated steel structure buildings. However, the traditional steel plate concrete shear wall is prone to early buckling of the steel plate and concentrated interface damage under cyclic loading, which limits its energy dissipation capacity. This study presents a steel plate-enhanced reinforced concrete shear wall (SPRCSW) with an internal corrugated steel plate and double-layer steel mesh working together and conducts a selection study based on finite element analysis. Under the same design conditions, the peak bearing capacity in the positive and reverse directions of the SPRCSW is increased by approximately 55.4% and 46.9%, respectively, compared to the ordinary reinforced concrete shear wall, with a ductility coefficient reaching 6.08. The stiffness decline is mild, and the hysteretic curve is complete. Then, this paper forms an SR-SPRCSW composite structural system by combining the new shear wall with a steel frame using semi-rigid joints. Through the comparison of the finite element analysis and low-cycle reverse loading test results of the SR-SPRCSW structure, it is verified that the overall structural system shows good agreement in hysteretic response, skeleton curve characteristics, and failure mode under both research methods, with the peak shear bearing capacity error of less than 1% and the overall bearing capacity deviation controlled within 8%. On this basis, the key parameters of the semi-rigid joints in the SR-SPRCSW structure are analyzed. The results show that the strengthening of the “top and bottom + double web” angle steel joint can raise the peak bearing capacity of the SR-SPRCSW structure by approximately 26.1% and the yield displacement by approximately 29.5%; increasing the strength grade and diameter of high-strength bolts can heighten the initial stiffness and bearing capacity of the overall structure, but ductility slightly decreases; the thickness of the angle steel has a significant impact on the stiffness and deformation capacity of the structure, and a recommended range of values with better comprehensive performance is provided. The findings offer valuable insights for designing seismic-resistant semi-rigid steel frames with steel plate reinforced concrete shear walls and optimizing their parameters. Full article

Offline safe reinforcement learning (RL) aims to learn policies from a fixed dataset while maximizing performance under cumulative cost constraints. In practice, deployment requirements often vary across scenarios, necessitating a single policy capable of zero-shot adaptation to different cost thresholds. However, most existing offline safe RL methods are trained under a pre-specified threshold, yielding policies with limited generalization and deployment flexibility across cost thresholds. Motivated by recent progress in conditional sequence modeling (CSM), which enables flexible goal-conditioned control by specifying target returns, we propose Return–Cost Regularized Constrained Decision Transformer (RCDT), a CSM-based method that supports zero-shot deployment across multiple cost thresholds within a single trained policy. RCDT is the first CSM-based offline safe RL algorithm that integrates a Lagrangian-style cost penalty with an auto-adaptive penalty coefficient. To avoid overly conservative behavior and achieve a more favorable return–cost trade-off, a reward–cost-aware trajectory reweighting mechanism and Q-value regularization are further incorporated. Extensive experiments on the DSRL benchmark demonstrate that RCDT consistently improves return–cost trade-offs over representative baselines. Full article

Biodegradable nanocomposite materials possessing self-healing behavior are emerging as an attractive option of being used in advanced mechatronic systems. The current study is focused on a thorough examination of the micromechanical properties of graphene–reinforced polylactic acid (PLA)/polycaprolactone (PCL) composite samples, followed by estimation of their self-healing behavior upon heating. Polymer blend–based nanocomposite materials were prepared using the green and reliable in terms of good nanofiller dispersion melt extrusion method. 3D printed nanocomposite specimens with impeccable flatness were subjected to fine microscratch testing by applying a constant force experimental mode. The surface resistance of the three-component polymer materials against the lateral movement of the stylus fulfilling the scratch and the impact of the dual-phase PLA/PCL ratio on the nanocomposite mechanical performance were estimated by calculation of the coefficient of friction (COF = F_x/F_z). COF values in the range of 0.8–1.4 indicated excellent nanocomposite resilience against scratch. Creating a heterogeneous polymer system that combines phase-separated soft and hard domains with close melt and glass transition temperatures, respectively, may facilitate the physical flow of macromolecular chains into voids or free volume areas. This aspect can be critical in the achievement of thermally–induced self-healing properties of the composite material. Scanning electron microscopy (SEM) imaging of the microscratches, made before and after Joule heating of the polymer samples, revealed a significant degree of surface recovery and a sensible reduction in the width of the adjusted scratch grooves. Full article

The research gap addressed in this study is the lack of a transparent and quantitative evaluation of the governing parameters influencing deflection behavior in reinforced concrete (RC) beams reinforced with glass fiber-reinforced polymer (GFRP) bars. The objective of this study is to identify and quantify the relative importance of the key parameters controlling deflection in GFRP-reinforced RC beams, which exhibit fundamentally different behavior compared to steel-reinforced beams due to the linear-elastic response of GFRP bars until rupture. To achieve this objective, the method integrates explainable artificial intelligence (XAI) techniques, including SHapley Additive exPlanations (SHAP), Pearson correlation heatmap, scatter plot analysis, and sensitivity analysis—with experimental structural data obtained from beams with three different concrete strength classes. The main contribution of this study is the quantitative ranking and interpretation of the governing parameters affecting deflection behavior through a transparent and data-driven framework. Key parameters—including elastic modulus (Ec), compressive strength (fck), creep coefficient (φ), failure moment (Mexp), effective moment of inertia (Ieff), and applied load (P)—were evaluated. The results consistently indicate that stiffness- and capacity-related parameters dominate the deflection response. Sensitivity analysis reveals that the failure moment (Mexp) is the most influential parameter, contributing approximately 23% of the total relative influence on deflection, followed by compressive strength (fck) and cracking-related parameters. Pearson correlation heatmap and scatter plot analyses further confirm strong relationships between deflection and Ec, fck, φ, and Ieff. The proposed framework improves the interpretability of deflection prediction in GFRP-reinforced RC beams and provides a transparent basis for serviceability-based structural design and performance-oriented assessment. Full article

To address issues such as web and bottom plate cracking and insufficient bending capacity in in-service prestressed concrete box girder bridges, this study proposes internal prestressing and section enlargement composite reinforcement. Firstly, taking a bridge of Shenhai Expressway as the background project, the combined reinforcement method is designed and the reinforcement effect is analyzed by MIDAS/Civil. Secondly, through numerical analysis, the influence of the bond shrinkage of self-compacting concrete with different mix ratios on the stress of the web of the original box girder is analyzed, and the interface between the new and old concrete is carried out. The analysis of the loss of the new prestress on the bonding surface of the new and old concrete is carried out by parameters such as the interface planting rate, the interface shear stiffness and the reinforcement structure. Furthermore, the theoretical calculation method of prestress loss rate of new and old concrete bonding interface is obtained. The results show that the flexural capacity of the normal section of the main beam is significantly improved after reinforcement, and the surplus coefficient is 1.18, which meets the requirements of the secondary safety level, and the mid-span deflection is improved by 34.28%, which verifies the effectiveness and feasibility of the combined reinforcement method. When the content of fly ash is 54%, the bond shrinkage strain and shrinkage stress of self-compacting concrete are reduced to the lowest level, which has the least influence on the existing box girder structure. It is suggested that the reinforcement ratio between the new and old concrete interface is 0.6%, and the interface roughness is 0.9 mm, which can increase the shear resistance of the new and old concrete interface and effectively reduce the transfer loss of prestress at the interface. Error analysis shows that the proposed semi-empirical calculation method has high accuracy with a deviation of less than 10%. Full article

Standard compatibility-based truss models, including the Disturbed Stress Field Model (DSFM), often underestimate the shear strength and deformation capacity of reinforced-concrete (RC) beam-column joints. This study investigates the origin of this bias through a systematic inverse identification framework and derives joint-core constitutive relationships tailored to the highly confined, nonuniform stress states of joints. Inverse analyses show that improving confinement effectiveness alone leads to unrealistic parameter saturation and cannot reproduce the measured energy absorption, indicating that conventional compression-softening formulations remain excessively punitive for joint cores. When confinement activation and softening are identified simultaneously, a clear mechanism shift emerges: unlike panel-based theories that link softening to tensile-cracking measures (principal strain ratio), joint softening is overwhelmingly governed by the principal compressive strain, consistent with crushing-dominated damage accumulation. Based on these trends, unified power-law expressions are proposed for both passive confinement activation and damage-induced softening as functions of principal compressive strain only, adhering to a parsimonious formulation without auxiliary variables such as concrete strength or reinforcement ratio ($R^2\approx 0.89$). The model is validated on an independent database of 113 specimens, including high-strength concrete and exterior joints, eliminating the systematic conservatism of the standard DSFM and improving the mean experimental-to-predicted strength ratio from 0.85 to 1.01 while reducing the coefficient of variation from 34.5% to 13%. The proposed formulation supports more reliable joint shear backbone predictions for seismic assessment of RC frame buildings. Full article

Carbon fiber-reinforced thermoplastic (CFRTP) composites are now widely used in many fields. Ultrasonic welding (UW) is a key technology for joining these materials. The control mode of UW has a great effect on the quality of the welded joints. However, there is still not enough research comparing the different welding control modes. This paper investigates the effects of the time control, energy control, and displacement control modes on the ultrasonic welding quality of carbon fiber-reinforced polycarbonate (CF/PC). A flat PC film is used as the energy director (ED). The evaluation focuses on the lap-shear strength (LSS), macro- and micro-morphology, fracture surface characteristics and power–displacement curves of the welding process. Furthermore, significant differences are observed in the temperature field evolution and joint failure modes across the different control modes and process parameters. Results indicate that the displacement control mode achieves the highest joint quality and process stability, yielding a maximum LSS of 30.6 MPa. A correlation analysis reveals that the displacement–energy relationship exhibits the strongest coupling, and the Pearson correlation coefficient r is 0.896. Full article

To address the practical requirements for in situ equipment restoration, this study investigates a portable and cost-effective approach for the localized repair of SAE 10SAE 1045 components using a 1Cr13 martensitic stainless steel coating prepared via an arc-based additive manufacturing (WAAM) process. The microstructural evolution and tribological response of the layers were analyzed, with a focus on the effects of discrete thermal cycling and controlled solidification inherent to portable arc equipment. The WAAM process produced a refined martensitic matrix with a microhardness of 551.94 HV0.2, which is 2.26 times that of the substrate. Under dry sliding conditions, the 1Cr13 coating exhibited a lower friction coefficient and a reduced wear volume compared to the untreated SAE 1045, primarily through the mitigation of severe plastic deformation. This additive route provides a millimeter-scale reinforcement layer with metallurgical integrity suitable for heavy-duty service, aiming to offer a practical reference for the low-cost, on-site restoration of industrial components. Full article