Search Results (299)

The dynamic modulus of asphalt mixtures (|E*|) is a key mechanical parameter in the design of road pavements, yet direct laboratory testing is time- and resource-intensive. This study evaluates two predictive models for estimating |E*| using data from 62 asphalt mixtures containing reclaimed asphalt: a grey relational analysis–multiple linear regression (GRA-MLR) hybrid model and a mechanistic sigmoidal model. The results showed that the GRA-MLR model effectively identifies influential variables but achieved moderate predictive accuracy (R² values varying from 0.4743 to 0.6547). In contrast, the sigmoidal model outperformed across all temperature conditions (R² > 0.96) and produced predictions deviating by less than ±20% from measured values. Temperature-dependent shifts in factor influence were observed, with stiffness and gradation dominating at low temperatures and reclaimed asphalt (RA) content becoming more significant at higher temperatures. While the GRA-MLR model is advantageous, offering rapid assessments and early-stage evaluations, the sigmoidal model offers the precision suited for detailed design. Integrating both models can balance computational efficiency and provide a balanced strategy, with strong predictive reliability to advance mechanistic–empirical pavement design. Full article

The functionalization of textiles with nanomaterials through green synthesis offers a promising pathway for sustainable material innovation. This study explores the in situ green synthesis of silver nanoparticles (AgNPs) onto cotton fabrics using Solanum tuberosum (potato) peel extract as a natural reducing and stabilizing agent. The synthesis conditions were optimized by varying silver nitrate concentration, extract volume, temperature, pH, and reaction time, after which the optimized protocol was applied for fabric treatment. The presence and distribution of AgNPs were confirmed through UV-Visible spectroscopy, Fourier-transform infrared spectroscopy, scanning electron microscopy and dynamic light scattering. The treated fabrics demonstrated strong and durable antibacterial performance, with inhibition zones of 23 ± 0.02 against Escherichia coli and 16 ± 0.01 against Staphylococcus aureus. Notably, antibacterial activity was retained even after 20 washing cycles, demonstrating the durability of the treatment. Mechanical testing revealed a 32.25% increase in tensile strength and a corresponding 10.47% reduction in elongation at break compared to untreated fabrics, suggesting improved durability with moderate stiffness. Air permeability decreased by 8.8%, correlating with the rougher surface morphology observed in Scanning Electron Microscopy images. Thermal analysis showed a decrease in thermal stability relative to untreated cotton, highlighting the influence of AgNPs on degradation behavior. Overall, this work demonstrates that potato peel waste, an abundant and underutilized biomass, can be used as a sustainable source for the green synthesis of AgNP-functionalized textiles. The approach provides a cost-effective and environmentally friendly strategy for developing multifunctional fabrics, while supporting circular economy goals in textile engineering. Full article

Hydrogels with protein–polysaccharide combinations are widely used in the field of tissue engineering, as they can mimic the in vivo environments of native tissues, specifically the extracellular matrix (ECM). However, achieving stability and mechanical properties comparable to those of tissues by employing natural polymers remains a challenge due to their weak structural characteristics. In this work, we optimized the fabrication strategy of a hydrogel composite, comprising gelatin and sodium alginate (Gel-SA), by varying reaction parameters. Magnetite (Fe₃O₄) nanoparticles were incorporated to enhance the mechanical stability and structural integrity of the scaffold. The changes in hydrogel stiffness and viscoelastic properties due to variations in polymer mixing ratio, crosslinking time, and heating cycle, both before and after nanoparticle incorporation, were compared. FTIR spectra of crosslinked hydrogels confirmed physical interactions of Gel-SA, metal coordination bonds of alginate with Ca²⁺, and magnetite nanoparticles. Tensile and rheology tests confirmed that even at low magnetite concentration, the Gel-SA-Fe₃O₄ hydrogel exhibits mechanical properties comparable to soft tissues. This work has demonstrated enhanced resilience of magnetite-incorporated Gel-SA hydrogels during the heating cycle, compared to Gel-SA gel, as thermal stability is a significant concern for hydrogels containing gelatin. The interactions of thermoreversible gelatin, anionic alginate, and nanoparticles result in dynamic hydrogels, facilitating their use as viscoelastic acellular matrices. Full article

This study examines the prestress transmission behavior in near-surface-mounted (NSM) carbon fiber-reinforced polymer (CFRP)-strengthened reinforced concrete structures, with particular emphasis on the effects of temperature. Experimental tests were conducted to evaluate the tensile and shear properties of epoxy adhesives under a range of curing temperatures (20–100 °C) and ambient service temperatures (0–80 °C). The results reveal an inverse exponential relationship between curing time and temperature. Notably, adhesive strength declines significantly above 60 °C and the adhesive loses functionality at 80 °C. Building on these findings, an analytical model was developed to predict prestress transfer length, CFRP strain distribution, and interfacial shear stress. The model incorporates effective bond stiffness and a prestress reduction coefficient to account for varying prestress levels (10–50%). Parametric analyses identify the CFRP elastic modulus, cross-sectional geometry, adhesive thickness, and degree of curing as critical factors influencing prestress transmission. The model’s predictions were validated against experimental data, demonstrating its reliability. Overall, this work provides a theoretical foundation for optimizing the design of NSM CFRP-strengthened structures under complex thermal conditions. Full article

Lubrication plays a crucial role in reducing gear surface damage and defects such as pitting, wear, and scuffing; therefore, analyzing the influence of lubrication is essential for preventing such failures in gear transmission systems. To this end, the dynamic properties of gear systems were examined, leading to the creation of a thermal elastohydrodynamic lubrication (TEHL) model for the line contact of involute spur gears. This model utilizes a multigrid method to calculate the oil film pressure and thickness. Subsequently, models for meshing stiffness, normal oil film stiffness, and overall normal stiffness were developed using energy methods and lubrication theory. Ultimately, a dynamic model of the spur gear system that incorporated lubrication effects was developed to examine how different operating conditions affect dynamic transmission error, vibration velocity, and dynamic meshing force. The findings revealed that when considering the TEHL effect, the dynamic transmission error along the gear meshing line increases, while both the vibration velocity and dynamic meshing force exhibit a decrease. Furthermore, as speed and load intensify, the amplitudes of dynamic transmission error, vibration velocity, and dynamic meshing force also rise. Notably, an increase in the initial viscosity of the lubricating oil correlates with a decrease in the fluctuation of dynamic transmission error, while the variations in vibration velocity and dynamic meshing force remain relatively insignificant. Full article

Many existing reinforced concrete (RC) frames with brick infill walls are vulnerable to earthquake damage, particularly when the walls contain window openings that reduce the lateral resistance. This study aims to examine the seismic performance of RC frames strengthened with U-shaped precast concrete (PC) wall panels. In the proposed method, the window-containing brick infill walls within the RC frames are replaced with factory-fabricated U-shaped PC wall panels, thereby converting the infill into a strong and rigid structural element while preserving the openings. The panels are anchored to the RC frame using post-installed anchors inserted through predrilled holes, allowing for rapid and secure installation with minimal on-site work. To validate the method, five full-scale, one-bay, one-story RC frames were constructed and tested under reversed cyclic lateral loading. Three frames were strengthened with U-shaped PC wall panels of varying thicknesses and large openings. Displacement-controlled cycles following ACI 374.1-05 (R7.0) were applied, with three cycles at each drift ratio stage, and no axial load was applied to the columns. Compared with the reference specimen with a U-shaped brick wall, the strengthened frames exhibited up to 3.29 times higher lateral strength, 4.39 times higher initial stiffness, and 4.33 times greater energy dissipation capacity. These findings demonstrate that the proposed strengthening technique significantly enhances seismic resistance while maintaining the architectural openings, offering a practical and efficient solution for upgrading low-rise RC buildings. Full article

This paper investigates the nonlinear dynamics of the wheel-side planetary reducer, considering the tooth wear effect. The tooth wear model based on the Archard adhesion wear theory is established, and the impact of tooth wear on meshing stiffness and piecewise-linear backlash of the planetary gear system is discussed. Then, the torsional vibration model and dimensionless differential equations considering tooth wear for the wheel-side planetary reducer are established, in which meshing excitations include time-varying mesh stiffness (TVMS), piecewise-linear backlash, and transmission error. The dynamic responses are numerically solved using the fourth-order Runge–Kutta method. On this basis, the nonlinear dynamics, such as the bifurcation and chaos properties of the wheel-side planetary reducer with tooth wear, are analyzed. Simulation results demonstrate that the existence of tooth wear reduces meshing stiffness and increases backlash. The reduction in the meshing stiffness changes the bifurcation path and chaotic amplitude of the system, inducing chaotic phenomena more easily. The increase in the gear backlash causes a higher amplitude of the relative displacement and more severe vibration. Full article

Accurately modelling and simulating the stiffness modulus of asphalt mixtures is essential for reliable pavement design and performance prediction under varying environmental and loading conditions. The preceding is commonly achieved through master curves, which relate stiffness to loading frequency at a reference temperature. However, conventional master curves face two primary limitations. Firstly, temperature is not treated as a state variable; instead, its effect is indirectly considered through shift factors, which can introduce inaccuracies due to their lack of thermodynamic consistency across the entire range of possible temperatures. Secondly, conventional master curves often encounter convergence difficulties when calibrated with experimental data constrained to a narrow frequency spectrum. In order to address these shortcomings, this investigation proposes a novel formulation known as the Thermo-Stiffness Integration (TSI) model, which explicitly incorporates both temperature and frequency as state variables to predict the stiffness modulus directly, without relying on supplementary expressions such as shift factors. The TSI model is built on thermodynamics-based principles (such as Eyring’s rate theory and activation free energy) and leverages the time–temperature superposition principle to create a physically consistent representation of the mechanical behaviour of asphalt mixtures. This manuscript presents the development of the TSI model along with its application in a case study involving eight asphalt mixtures, including four hot-mix asphalts and four warm-mix asphalts. Each type of mixture contains recycled concrete aggregates at replacement levels of 0%, 15%, 30%, and 45% as partial substitutes for coarse natural aggregates. This diverse set of materials enables a robust evaluation of the model’s performance, even under non-traditional mixture designs. For this case study, the TSI model enhances computational stability by approximately 4 to 45 times compared to conventional master curves. Thus, the main contribution of this research lies in establishing a valuable mathematical tool for both scientists and practitioners aiming to improve the design and performance assessment of asphalt mixtures in a more physically realistic and computationally stable approach. Full article

Vascularization remains a critical challenge in tissue engineering, limiting graft survival, integration, and clinical translation. Although bioprinting enables spatial control over vascular architectures, many existing approaches prioritize geometric precision over biological performance. Bioprinted vasculature can be understood as a dynamic and time-dependent system that requires tissue-specific maturation. Within this framework, hydrogel systems act as active microenvironments rather than passive scaffolds. Hydrogel platforms vary from natural matrices and synthetic polymers to bioinspired or stimuli-responsive systems, each offering tunable control over stiffness, degradation, and biochemical signaling needed for vascular maturation. The design requirements of large and small vessels differ in terms of mechanical demands, remodeling capacity, and host integration. A key limitation in current models is the absence of time-resolved evaluation, as critical processes such as lumen formation, pericyte recruitment, and flow-induced remodeling occur progressively and are not captured by static endpoints. Advancements in bioprinting technologies are evaluated based on their capacity to support hydrogel-mediated vascularization across varying length scales and structural complexities. A framework for functional assessment is proposed, and translational challenges related to immunogenicity, scalability, and regulatory requirements are discussed. Such integration of hydrogel-driven biological cues and bioprinting fidelity is critical to advancing vascularized constructs toward clinical translation. Full article

This paper presents a real-time framework for bilateral gait reconstruction and adaptive joint control using sparse inertial sensing. The system estimates full lower-limb motion from a single-side inertial measurement unit (IMU) by applying a pipeline that includes signal smoothing, temporal alignment via Dynamic Time Warping (DTW), and motion modeling using Gaussian Mixture Models with Regression (GMM-GMR). Contralateral leg trajectories are inferred using both ideal and adaptive symmetry-based models to capture inter-limb variations. The reconstructed motion serves as reference input for joint-level control. A classical Proportional–Integral–Derivative (PID) controller is first evaluated, demonstrating satisfactory results under simplified dynamics but notable performance loss when virtual stiffness and gravity compensation are introduced. To address this, an adaptive fuzzy PID controller is implemented, which dynamically adjusts control gains based on real-time tracking error through a fuzzy inference system. This approach enhances control stability and motion fidelity under varying conditions. The combined estimation and control framework enables accurate bilateral gait tracking and smooth joint control using minimal sensing, offering a practical solution for wearable robotic systems such as exoskeletons or smart prosthetics. Full article

This paper focuses on the failure mechanism of a pre-stressed CFRP cantilever beam under laser ablation. During testing, a mass was applied to the CFRP cantilever beam to achieve a pre-stressed state, and the laser power densities varied from 500 to 1500 W·cm⁻². Corresponding scanning electron microscope (SEM) tests were also performed on the ablation zone and fracture surface to analyze the failure mechanism. The results showed that the CFRP beam failed in compression at the bottom surface, which was due to a decrease in local stiffness and strength caused by heat softening, rather than by ablation damage on the top surface. The failure time decreased from 19.64 s to 6.52 s as the power density (500–1500 W·cm⁻²) and pre-stress loading (300–750 N·cm) increased, indicating that pre-stress loading has a more significant influence on the failure time of CFRP beams compared to power density. Full article

Al-Mg-Si (6XXX) series aluminum alloys are widely applied in aerospace and transportation industries. However, exploring how varying compositions affect alloy properties and deformation mechanisms is often time-consuming and labor-intensive due to the complexity of the multicomponent composition space and the diversity of processing and heat treatments. This study, inspired by the Materials Genome Initiative, employs high-throughput experimentation—specifically the kinetic diffusion multiple (KDM) method—to systematically investigate how the pop-in effect, indentation size effect (ISE), and creep behavior vary with the composition of Al-Mg-Si alloys at room temperature. To this end, a 6016/Al-3Si/Al-1.2Mg/Al KDM material was designed and fabricated. After diffusion annealing at 530 °C for 72 h, two junction areas were formed with compositional and microstructural gradients extending over more than one thousand micrometers. Subsequent solution treatment (530 °C for 30 min) and artificial aging (185 °C for 20 min) were applied to simulate industrial processing conditions. Comprehensive characterization using electron probe microanalysis (EPMA), nanoindentation with continuous stiffness measurement (CSM), and nanoindentation creep tests across these gradient regions revealed key insights. The results show that increasing Mg and Si content progressively suppresses the pop-in effect. When the alloy composition exceeds 1.0 wt.%, the pop-in events are nearly eliminated due to strong interactions between solute atoms and mobile dislocations. In addition, adjustments in the ISE enabled rapid evaluation of the strengthening contributions from Mg and Si in the microscale compositional array, demonstrating that the optimum strengthening occurs when the Mg-to-Si atomic ratio is approximately 1 under a fixed total alloy content. Furthermore, analysis of the creep stress exponent and activation volume indicated that dislocation motion is the dominant creep mechanism. Overall, this enhanced KDM method proves to be an effective conceptual tool for accelerating the study of composition–deformation relationships in Al-Mg-Si alloys. Full article

To address the unclear coupling mechanism between thermal elastohydrodynamic lubrication (TEHL) and dynamic behaviors in planetary gear systems, a novel tribo-dynamic model for dual-star planetary gears considering TEHL effects is proposed. In this model, a TEHL surrogate model is first established to determine the oil film thickness and sliding friction force along the tooth meshing line. Subsequently, the dynamic model of the dual-star planetary gear transmission system is developed through coordinate transformations of the dual-star gear train. Finally, by integrating lubrication effects into both time-varying mesh stiffness and time-varying backlash, a tribo-dynamic model for the dual-star planetary gear transmission system is established. The study reveals that the lubricant film thickness is positively correlated with relative sliding velocity but negatively correlated with unit line load. Under high-speed conditions, a thickened oil film induces premature meshing contact, leading to meshing impacts. In contrast, under high-torque conditions, tooth deformation dominates meshing force fluctuations while lubrication influence diminishes. By establishing a test bench for the planetary gear transmission system, the obtained simulation conclusions are verified. This research provides theoretical and experimental support for the design of high-reliability planetary gear systems. Full article

In space gravitational wave detection, various physical effects in the spacecraft, such as self-gravity, electricity, and magnetism, will introduce undesirable parasitic stiffness. The coupling noise between stiffness and the motion states of the test mass critically affects the performance of scientific detection, making accurate stiffness identification crucial. In response to the question, this paper proposes a method to optimize the test mass motion state for enhancing stiffness identification performance. First, the dynamics of the test mass are studied and a recursive least squares algorithm is applied for the implementation of on-orbit stiffness identification. Then, the motion state of the test mass is parametrically characterized by multi-frequency sinusoidal signals as the variable to be optimized, with the optimization objectives and constraints of stiffness identification defined based on convergence time, convergence accuracy, and engineering requirements. To tackle the dual-objective, computationally expensive nature of the problem, a multigranularity surrogate-assisted evolutionary algorithm with individual progressive constraints (MGSAEA-IPC) is proposed. A fuzzy radial basis function neural network PID (FRBF-PID) controller is also designed to address complex control needs under varying motion states. Numerical simulations demonstrate that the convergence time after optimization is less than 2 min, and the convergence accuracy is less than 1.5 × 10⁻¹⁰ s⁻². This study can provide ideas and design references for subsequent related identification and control missions. Full article

Roller bearing manufacturing errors have been proven to be critical factors affecting the vibrations of gear systems. Waviness is one main form of manufacturing error affecting the operational performance and life of bearings. However, most previous studies did not completely incorporate the effects of the uneven bearing waviness on the flexible gear system vibrations. To characterize the contribution of the uneven bearing waviness on the vibrations of the gear system, a gear transmission system dynamics model considering shaft flexibility was established. The evenness sinusoidal waviness model (SWM) and uneven sinusoidal waviness model considering the time-varying contact (SWMS) were compared. The influences of the time-varying gear meshing stiffness excitations and flexibilities of shafts on the vibrations of the gear system were considered. A dynamic model was established, and the vibrations of the flexible gear system with the SWM and SWMS were compared. The vibrations induced by different amplitudes and orders of bearing waviness were analyzed. Note that the waviness of the bearing has a great influence on the system vibrations. The vibrations of the flexible gear system intensified with the increase in the bearing waviness order and amplitude. The vibrations from the gear system with the SWMS were bigger than those of the SWM. This paper introduces an alternative dynamic modeling model enabling the vibration analysis of the flexible gear system with evenness and uneven bearing waviness. Full article