Search Results (336)

Subsurface mass concrete infrastructure—including immersed tunnels, dams, and nuclear waste containment systems—frequently faces calcium-leaching risks from prolonged groundwater exposure. An anisotropic stress-leaching damage model incorporating microcrack propagation is developed for underground concrete’s chemo–mechanical coupling. This model investigates stress-induced anisotropy in concrete through the evolution of oriented microcrack networks. The model incorporates nonlinear anisotropic plastic strain from coupled chemical–mechanical damage. Unlike conventional concrete rheology, this model characterizes chemical creep through stress-chemical coupled damage mechanics. The numerical model is incorporated within COMSOL Multiphysics to perform coupled multiphysics simulations. A close match is observed between the numerical predictions and experimental findings. Under high stress loads, calcium leaching and mechanical stress exhibit significant coupling effects. Regarding concrete durability, chemical degradation has a more pronounced effect on concrete’s stiffness and strength reduction compared with stress-generated microcracking. Full article

The 2020 southern Puerto Rico earthquake sequence highlighted the severe seismic vulnerability of informally constructed two-story reinforced concrete (RC) houses. This study examines the failure mechanisms of these structures and assesses the effectiveness of first-floor RC shear-wall retrofitting. Nonlinear pushover and dynamic time–history analyses were performed using fiber-based distributed plasticity models for RC frames and nonlinear macro-elements for second-floor masonry infills, which introduced a significant inter-story stiffness imbalance. A bi-directional seismic input was applied using spectrally matched, near-fault pulse-like ground motions. The findings for the as-built structures showed that stiffness mismatches between stories, along with substantial strength and stiffness differences between orthogonal axes, resulted in concentrated plastic deformations and displacement-driven failures in the first story—consistent with damage observed during the 2020 earthquakes. Retrofitting the first floor with RC shear walls notably improved the performance, doubling the lateral load capacity and enhancing the overall stiffness. However, the retrofitted structures still exhibited a concentration of inelastic action—albeit with lower demands—shifted to the second floor, indicating potential for further optimization. Full article

Cable force distribution in cable-stayed bridges critically impacts structural safety and efficiency, yet traditional optimization methods struggle with unconventional designs due to nonlinear mechanics and computational inefficiency. This study proposes a hybrid approach combining Response Surface Methodology (RSM) and Multi-Objective Particle Swarm Optimization (MOPSO) to overcome these challenges. RSM constructs surrogate models for strain energy and mid-span displacement, reducing reliance on finite element analysis, while MOPSO optimizes Pareto solution sets for rapid cable force adjustment. Validated through an engineering case, the method reduces the main girder’s max bending moment by 8.7%, mid-span displacement by 31.2%, and strain energy by 7.1%, improving stiffness and mitigating stress concentrations. The response surface model demonstrates prediction errors of 0.35% for strain energy and 5.1% for maximum vertical mid-span deflection. By synergizing explicit modeling with intelligent algorithms, this methodology effectively resolves the longstanding efficiency–accuracy trade-off in cable force optimization for cable-stayed bridges. It achieves over 80% reduction in computational costs while enhancing critical structural performance metrics. Engineers are thereby equipped with a rapid and reliable optimization framework for geometrically complex cable-stayed bridges, delivering significant improvements in structural safety and construction feasibility. Ultimately, this approach establishes both theoretical substantiation and practical engineering benchmarks for designing non-conventional cable-stayed bridge configurations. Full article

The vertical stiffness of railway tracks is crucial for ensuring safe and efficient rail transport. Rail-pad dynamic stiffness is a key component influencing track performance. Determining the dynamic stiffness of rail pads poses a challenge because it depends not only on the material and geometry of the rail pad but also on the testing conditions, due to the non-linear material response. To address this issue, a methodology is proposed in this paper to estimate dynamic stiffness using static stiffness measurements. This approach enables the prediction of dynamic stiffness for different situations from a single laboratory test. This study further examines whether this correlation remains valid for different types of rail pads, even when their mechanical behavior has been degraded by temperature, wear, or chemical agents. Experiments were conducted under varying temperatures and on rail pads that underwent mechanical and chemical degradation. The analysis assesses the validity of the static-to-dynamic stiffness correlation under degraded conditions and investigates the influence of each testing condition on the ability to estimate dynamic stiffness from static stiffness and operational parameters. The findings provide insights into the reliability of this predictive model and highlight the impact of degradation mechanisms on the dynamic behavior of rail pads. This research enhances the understanding of rail pad performance and offers a practical approach for evaluating dynamic stiffness. By considering all of the variables used in the analysis, the approach achieves R² values of up to 0.99, which carries significant implications for track design and maintenance. Full article

Exoskeletons transfer loads to the human body via physical human–exoskeleton interfaces (pHEI). However, the human–exoskeleton interaction remains poorly understood, and the mechanical properties of the pHEI are not well characterized. Therefore, we present a novel methodology to precisely characterize pHEI interaction stiffnesses under various loading conditions. Forces and torques were applied in three orthogonal axes to the upper arm pHEI of 21 subjects using an electromechanical apparatus. Interaction loads and displacements were measured, and stiffness data were derived as well as mathematically described using linear and non-linear regression models, yielding all the diagonal elements of the stiffness tensor. We find that the non-linear nature of pHEI stiffness is best described using exponential functions, though we also provide linear approximations for simplified modeling. We identify statistically significant differences between loading conditions and report median translational stiffnesses between 2.1 N/mm along and 4.5 N/mm perpendicular to the arm axis, as well as rotational stiffnesses of 0.2 N·m/° perpendicular to the arm, while rotations around the longitudinal axis are almost an order of magnitude smaller (0.03 N·m/°). The resulting stiffness models are suitable for use in digital human–exoskeleton models, potentially leading to more accurate estimations of biomechanical efficacy and discomfort of exoskeletons. Full article

The tensile strength of the umbilical cord (UC) is influenced by its composition—including collagen, elastin, and hyaluronan—contributing to its unique biomechanical properties. This experimental in vitro study aimed to evaluate the UC’s mechanical behavior under varying strain rates and to characterize its viscoelastic response. Twenty-nine UC specimens, each 40 mm in length, were subjected to uniaxial tensile testing and randomly assigned to three traction speed groups: Group A (n = 10) at 8 mm/min, Group B (n = 7) at 12 mm/min, and Group C (n = 12) at 16 mm/min. Four different parameters were analyzed: the ultimate tensile strength and its corresponding elongation, the elastic modulus defined as the slope of the linear initial portion of the stress–strain plot, and the elongation at the end of the test (at break). While elongation and elongation at break did not differ significantly between groups (one-way ANOVA), Group C showed a significantly higher ultimate tensile strength (p = 0.047). A linear relationship was observed between test speed and stiffness (elastic modulus), with the following regression equation: y = 0.3078e^4.425x. These findings confirm that the UC exhibits nonlinear viscoelastic properties and strain-rate-dependent stiffening, resembling non-Newtonian behavior. This novel insight may have clinical relevance during operative deliveries, where traction speed is often overlooked but may play a role in preserving cord integrity and improving neonatal outcomes. Full article

This study addresses the limitations of conventional evaluation methods caused by low porosity, strong heterogeneity, and complex pore structures in tight sandstone reservoirs. Through integrated rock physics experiments and multi-physical field modeling, the research systematically investigates the coupled response mechanisms between electrical and elastic parameters. The experimental approach includes pore structure characterization, quantitative mineral composition analysis, resistivity and polarizability measurements under various saturation conditions, P- and S-wave velocity testing, and scanning electron microscopy (SEM) imaging. The key findings show that increasing porosity leads to significant reductions in resistivity and elastic wave velocities, while also increasing surface conductivity. Specifically, clay minerals enhance surface conductivity through interfacial polarization effects and decrease rock stiffness, which exacerbates wave velocity attenuation. Furthermore, resistivity exhibits a nonlinear negative correlation with water saturation, with sharp increases at low saturation levels due to the disruption of conductive pathways. By integrating the Modified Generalized Effective Medium Theory of Induced Polarization (MGEMTIP) and Kuster–Toksöz models, this study establishes quantitative relationships between porosity, saturation, and electrical/elastic parameters, and constructs cross-plot templates that correlate elastic wave velocities with resistivity and surface conductivity. These analyses reveal that high-porosity, high-saturation zones are characterized by lower resistivity and wave velocities, coupled with significantly higher surface conductivity. The proposed methodology significantly improves the accuracy of reservoir evaluation and enhances fluid identification capabilities, providing a solid theoretical foundation for the efficient exploration and development of tight sandstone reservoirs. Full article

Tissue engineering enables autologous reconstruction of human tissues, addressing limitations in tissue availability and immune compatibility. Several tissue engineering techniques, such as self-assembly, rely on or benefit from extracellular matrix (ECM) secretion by fibroblasts to produce biomimetic scaffolds. Models have been developed for use in humans, such as skin and corneas. Ascorbic acid (vitamin C, AA) is essential for collagen biosynthesis. However, AA is chemically unstable in culture, with a half-life of 24 h, requiring freshly prepared AA with each change of medium. This study aims to demonstrate the functional equivalence of 2-phospho-L-ascorbate (2PAA), a stable form of AA, for tissue reconstruction. Dermal, vaginal, and bladder stroma were reconstructed by self-assembly using tissue-specific protocols. The tissues were cultured in a medium supplemented with either freshly prepared or frozen AA, or with 2PAA. Biochemical analyses were performed on the tissues to evaluate cell density and tissue composition, including collagen secretion and deposition. Histology and quantitative polarized light microscopy were used to evaluate tissue architecture, and mechanical evaluation was performed both by tensiometry and atomic force microscopy (AFM) to evaluate its macroscopic and cell-scale mechanical properties. The tissues produced by the three ascorbate conditions had similar collagen deposition, architecture, and mechanical properties in each organ-specific stroma. Mechanical characterization revealed tissue-specific differences, with tensile modulus values ranging from 1–5 MPa and AFM-derived apparent stiffness in the 1–2 kPa range, reflecting the nonlinear and scale-dependent behavior of the engineered stroma. The results demonstrate the possibility of substituting AA with 2PAA for tissue engineering. This protocol could significantly reduce the costs associated with tissue production by reducing preparation time and use of materials. This is a crucial factor for any scale-up activity. Full article

III-Nitride semiconductors (BN, AlN, GaN, and InN) exhibit exceptional electronic and mechanical properties that render them indispensable for high-performance optoelectronic, power, and high-frequency device applications. This study implements first-principles Density Functional Theory (DFT) calculations to elucidate the influence of hydrostatic pressure on the electronic, elastic, and mechanical properties of these materials in the wurtzite crystallographic configuration. Our computational analysis demonstrates that the bandgap energy exhibits a positive pressure coefficient for GaN, AlN, and InN, while BN manifests a negative pressure coefficient consistent with its indirect-bandgap characteristics. The elastic constants and derived mechanical properties reveal material-specific responses to applied pressure, with BN maintaining superior stiffness across the pressure range investigated, while InN exhibits the highest ductility among the studied compounds. GaN and AlN demonstrate intermediate mechanical robustness, positioning them as optimal candidates for pressure-sensitive applications. Furthermore, the observed nonlinear trends in elastic moduli under pressure reveal anisotropic mechanical responses during compression, a phenomenon critical for the rational design of strain-engineered devices. The computational results provide quantitative insights into the pressure-dependent behavior of III-N semiconductors, facilitating their strategic implementation and optimization for high-performance applications in extreme environmental conditions, including high-power electronics, deep-space exploration systems, and high-pressure optoelectronic devices. Full article

The current study demonstrates the buckling properties of composite laminates reinforced with MWCNT fillers using a novel higher-order shear and normal deformation theory (HSNDT), which considers the effect of thickness in its mathematical formulation. The hybrid HSNDT combines polynomial and hyperbolic functions that ensure the parabolic shear stress profile and zero shear stress boundary condition at the upper and lower surface of the plate, hence removing the need for a shear correction factor. The plate is made up of carbon fiber bounded together with polymer resin matrix reinforced with MWCNT fibers. The mechanical properties are homogenized by a Halpin–Tsai scheme. The MATLAB R2019a code was developed in-house for a finite element model using C⁰ continuity nine-node Lagrangian isoparametric shape functions. The geometric nonlinear and linear stiffness matrices are derived using the principle of virtual work. The solution of the eigenvalue problem enables estimation of the critical buckling loads. A convergence study was carried out and model efficiency was corroborated with the existing literature. The model contains only seven degrees of freedom, which significantly reduces computation time, facilitating the comprehensive parametric studies for the buckling stability of the plate. Full article

This study introduces a rigid–flexible coupled constant force actuator integrated with Active Disturbance Rejection Control (ADRC) to tackle the rigidity–compliance trade-off in precision force-sensitive applications. The actuator utilizes compliant hinges to decrease contact stiffness by three orders of magnitude (${10}^6\to {10}^3 \mathrm{N}/\mathrm{m}$), facilitating effective force management through millimeter-scale placement (0.1∼1 mm) and inherently mitigating high-frequency disturbances. The ADRC framework, augmented by an Extended State Observer (ESO), dynamically assesses and compensates for internal nonlinearities (such as friction hysteresis) and external disturbances without necessitating accurate system models. Experimental results indicate enhanced performance compared to PID control: under dynamic disturbances, force deviations are limited to $\pm 0.2 \mathrm{N}$ with a 98.5% reduction in mean absolute error, a 96.3% increase in settling speed, and 99% suppression of oscillations. The co-design of mechanical compliance with model-free control addresses the constraints of traditional high-stiffness systems, providing a scalable solution for industrial robots, compliant material processing, and medical device operations. Validation of the prototype under sinusoidal perturbations demonstrates reliable force regulation (settling time $<0.56 \mathrm{s}$, errors $<0.5 \mathrm{N}$), underscoring its relevance in dynamic situations. This study integrates theoretical innovation with experimental precision, enhancing intelligent manufacturing systems via adaptive control and structural synergy. Full article

The continued upscaling of offshore wind turbines (OWTs) necessitates the development of foundation systems capable of sustaining increased lateral loads. As monopiles remain the most widely used foundation type for OWTs, a detailed investigation into their lateral behavior and soil flow under operational loading is warranted. This study utilized a nonlinear three-dimensional finite element model (FEM) to assess the lateral performance of monopiles supporting a 5 MW turbine in clayey soils. The results revealed that the lateral capacity and deformation behavior are governed primarily by soil shear strength and the monopile’s length-to-diameter ratio (L/D). In softer soils, increasing the L/D ratio led to notable enhancements in lateral resistance, up to fivefold, as well as significant reductions in pile head displacement and rotation. In contrasts, monopiles in stiff clay exhibited distinct failure patterns and less sensitivity to L/D variations. Soil deformation patterns at the ultimate state varied depending on stiffness, indicating distinct failure mechanisms in soft and stiff clays. These findings highlight the importance of incorporating realistic soil behavior and geometric influences in monopile foundation design for large OWTs. Full article

As an important part of national transportation infrastructure, the operation status of bridges is directly related to transportation safety and social stability. Structural deflection, which reflects the deformation behavior of bridge systems, serves as a key indicator for identifying stiffness degradation and the progression of localized damage. The accurate modeling and forecasting of deflection are thus essential for effective bridge health monitoring and intelligent maintenance. To address the limitations of traditional methods in handling multi-source data fusion and nonlinear temporal dependencies, this study proposes an enhanced iTransformer-based prediction model, termed LDAiT (LSTM Differential Attention iTransformer), which integrates Long Short-Term Memory (LSTM) networks and a differential attention mechanism for high-fidelity deflection prediction under complex working conditions. Firstly, a multi-source heterogeneous time series dataset is constructed based on wireless sensor network (WSN) technology, enabling the real-time acquisition and fusion of key structural response parameters such as deflection, strain, and temperature across critical bridge sections. Secondly, LDAiT enhances the modeling capability of long-term dependence through the introduction of LSTM and combines with the differential attention mechanism to improve the precision of response to the local dynamic changes in disturbance. Finally, experimental validation is carried out based on the measured data of Xintian Yellow River Bridge, and the results show that LDAiT outperforms the existing mainstream models in the indexes of R², RMSE, MAE, and MAPE and has good accuracy, stability and generalization ability. The proposed approach offers a novel and effective framework for deflection forecasting in complex bridge systems and holds significant potential for practical deployment in structural health monitoring and intelligent decision-making applications. Full article

This article presents a mathematically grounded approach to increasing the operational reliability of current collectors in electric transport systems by ensuring a constant contact force between the collector shoe and the power rail. The core objective is achieved through the development and analysis of a mechanical system incorporating spring and cam elements, which is specifically designed to provide a nearly invariant contact pressure under varying operating conditions. A set of equilibrium equations was derived to determine the stiffness ratios of the springs and the geometric conditions under which the contact force remains constant despite wear or displacement. Additionally, the paper introduces a method for synthesizing the cam profile that compensates for nonlinear spring deformation, ensuring force constancy over a wide range of movement. The analytical results were validated through parametric simulations, which assessed the influence of wear depth, rail inclination, and external vibrations on the system’s force output. These simulations, executed within a numerical framework using scientific computing tools, demonstrated that the deviation of the contact force does not exceed a few percent under typical disturbances. Experimental verification further confirmed the theoretical predictions. The study exemplifies the effective use of mathematical modeling, nonlinear mechanics, and numerical methods in the design of energy transmission components for transport applications, contributing to the development of robust and maintainable systems. Full article

The attenuation of bolt preload is a critical factor leading to bolt fatigue failure, whereas the study of the nonlinear attenuation behavior of preload and its mechanism during installation is an inevitable challenge in engineering practice. The attenuation of the preload of a bolt is mainly related to the stiffness of the bolt body as well as the stiffness of the connected parts. This study aimed to develop an experimental system to analyze the nonlinear attenuation behavior of preload during bolt tightening. First, a simulation system replicating the bolt installation process was constructed in a laboratory setting, incorporating blade and pitch bearing specimens identical to those used in a 10 MW wind turbine, restoring the stiffness coupling characteristics of the “composite-metal bearing” heterogeneous interface at the blade root through a 1:1 full-scale simulation system for the first time. Second, ultrasonic preload measurement equipment was employed to monitor preload variations during the bolt tightening process. Finally, the instantaneous preload decay rate of the wind turbine blade-root bolts and the over-draw coefficient were quantified. Experiments have shown that the preload decay rate of commonly used M36 leaf root bolts is 11–16%. If a more precise value is required, each bolt needs to be calibrated. These findings provide valuable insights for optimizing bolt installation procedures, enabling precise preload control to mitigate fatigue failures caused by abnormal preload attenuation. Full article