Search Results (1,961)

This study addresses the complex challenges associated with flexible mattress (soft mattress) installation in the sharply curved and deep-water sections of the Yangtze River, particularly in the Yaozui revetment reconstruction project. Under extreme hydrodynamic conditions—water depths exceeding 30 m and velocities over 2.5 m/s—the risk of structural failures such as displacement, flipping, or tearing of the mattress becomes significant. To improve construction safety and stability, the study integrates numerical modeling and on-site strain monitoring to analyze the mechanical response of flexible mattresses during deployment. A three-dimensional finite element model based on the catenary theory was developed to simulate stress distributions under varying flow velocities and angles, revealing stress concentrations at the mattress’s upper edge and reinforcement junctions. Concurrently, a real-time monitoring system using high-precision strain sensors was deployed on critical shipboard components, with collected data analyzed through a remote IoT platform. The results demonstrate strong correlations between mattress strain, flow velocity, and water depth, enabling the identification of high-risk operational thresholds. The proposed monitoring and early-warning framework offers a practical solution for managing construction risks in extreme riverine environments and contributes to the advancement of intelligent construction management for underwater revetment works. Full article

In this study, the elastic modulus of CFRP rebars under high-temperature conditions was evaluated in accordance with ASTM D7205 and CSA S806, and the differences between the two standards were compared and analyzed. CFRP rebars with diameters of 10 mm and 13 mm were tested, and tensile specimens were prepared following the procedures specified in both standards. Tensile tests were conducted at temperatures ranging from 25 °C to 650 °C using an electric furnace. Fracture morphology before and after testing, as well as microstructural changes, were examined through scanning electron microscopy (SEM). The results revealed that the ASTM standard determines the elastic modulus based on the initial linear portion of the stress–strain curve before the transition point, whereas the CSA standard includes the post-transition segment. At temperatures below 325 °C, the ASTM-derived modulus exhibited a lower coefficient of variation (COV) compared to the CSA-derived values, indicating a more stable performance. By applying the experimentally obtained modulus values to various prediction models, the model with the lowest average error was identified. These findings confirm that the elastic modulus of CFRP rebars can be reasonably predicted under elevated-temperature conditions using calibrated models. Full article

Previous studies have extensively applied the generalized consolidation theory, which incorporates a two-stress state variable framework, to predict the volumetric behavior of unsaturated expansive soils under varying mechanical stress and matric suction. A key requirement for this approach is a constitutive surface that links the soil void ratio to both net stress and matric suction. A large number of fitting parameters are typically needed to accurately fit a two-variable void ratio surface equation to laboratory test data. In this study, a single-stress state variable framework was adopted to describe the void ratio as a function of effective stress for unsaturated soils. The proposed approach was applied to fit void ratio–effective stress constitutive curves to laboratory test data for two different expansive clays. Additionally, a finite element model coupling variably saturated flow and stress–strain analysis was developed to simulate the volume change behavior of expansive clay subjected to moisture fluctuations. The model utilizes suction stress to compute the effective stress field and incorporates the dependency of soil modulus on volumetric water content based on the proposed void ratio–effective stress relationship. The developed numerical model was validated against a benchmark problem in which a layer of Regina expansive clay was subjected to a constant infiltration rate. The results demonstrate the effectiveness of the proposed model in simulating expansive soil deformations under varying moisture conditions over time. Full article

Salmonella is one of the main causes of food-borne illness worldwide. In most cases, Salmonella contamination can be traced back to food processing plants and/or to cross-contamination during food preparation. To avoid food-borne diseases, food processing plants use sanitizers and biocidal to reduce bacterial contaminants below acceptable levels. Despite these preventive actions, Salmonella can survive and consequently affect human health. This study investigates the adaptive capacity of the main Salmonella enterica serotypes isolated from the poultry production line, focusing on their replication, antimicrobial resistance, and biofilm formation under stressors such as acidic conditions, oxidative environment, and high osmolarity. Using growth curve analysis, crystal violet staining, and microscopy, we assessed replication, biofilm formation, and antimicrobial resistance under acidic, oxidative, and osmotic stress conditions. Disinfectant tolerance was evaluated by determining the Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) of sodium hypochlorite. The antibiotic resistance was assessed using the Kirby–Bauer method. The results indicate that, in general, acidic and osmotic stress reduce the growth of Salmonella. However, no significant differences were observed specifically for serotypes Infantis, Heidelberg, and Corvallis. The S. Infantis isolates were the strongest biofilm producers and showed the highest prevalence of multidrug resistance (71%). Interestingly, S. Infantis forming biofilms required up to 8-fold higher concentrations of sodium hypochlorite for eradication. Furthermore, osmotic and oxidative stress significantly induced biofilm production in industrial S. Infantis isolates compared to a reference strain. Understanding how Salmonella responds to industrial stressors is vital for designing strategies to control the proliferation of these highly adapted, multi-resistant pathogens. Full article

Because artificially cemented granular (ACG) materials employ diverse combinations of aggregates and binders—including cemented soil, low-cement-content cemented sand and gravel (LCSG), and concrete—their stress–strain responses vary widely. In LCSG, the binder dosage is typically limited to 40–80 kg/m³ and the sand–gravel skeleton is often obtained directly from on-site or nearby excavation spoil, endowing the material with a markedly lower embodied carbon footprint and strong alignment with current low-carbon, green-construction objectives. Yet, such heterogeneity makes a single material-specific constitutive model inadequate for predicting the mechanical behavior of other ACG variants, thereby constraining broader applications in dam construction and foundation reinforcement. This study systematically summarizes and analyzes the stress–strain and volumetric strain–axial strain characteristics of ACG materials under conventional triaxial conditions. Generalized hyperbolic and parabolic equations are employed to describe these two families of curves, and closed-form expressions are proposed for key mechanical indices—peak strength, elastic modulus, and shear dilation behavior. Building on generalized plasticity theory, we derive the plastic flow direction vector, loading direction vector, and plastic modulus, and develop a concise, transferable elastoplastic model suitable for the full spectrum of ACG materials. Validation against triaxial data for rock-fill materials, LCSG, and cemented coal–gangue backfill shows that the model reproduces the stress and deformation paths of each material class with high accuracy. Quantitative evaluation of the peak values indicates that the proposed constitutive model predicts peak deviatoric stress with an error of 1.36% and peak volumetric strain with an error of 3.78%. The corresponding coefficients of determination R² between the predicted and measured values are 0.997 for peak stress and 0.987 for peak volumetric strain, demonstrating the excellent engineering accuracy of the proposed model. The results provide a unified theoretical basis for deploying ACG—particularly its low-cement, locally sourced variants—in low-carbon dam construction, foundation rehabilitation, and other sustainable civil engineering projects. Full article

A numerical method is proposed for evaluating the axial stress–strain relationship of FRP-confined concrete. In this method, empirical formulae for the compressive strength and strain at peak stress of confined concrete are obtained by fitting experimental data collected from the literature. It is then assumed that when FRP-confined concrete and actively confined concrete are subjected to the same lateral strain and confining pressure at a specific loading stage, their axial stress–strain relationships are identical at that stage. Based on this assumption, a numerical method for the axial stress–strain relationship of FRP-confined concrete is developed by combining the stress–strain model of actively confined concrete with the axial–lateral strain correlation. Finally, the validity of this numerical method is verified with experimental data with various geometric and material parameters, demonstrating a reasonable agreement between predicted stress–strain curves and measured ones. A parametric analysis is conducted to reveal that the stress–strain curve is independent of the specimen length for strong FRP confinement with small failure strains, while the specimen length exhibits a significant effect on the softening branch for weak FRP confinement. Therefore, for weakly FRP-confined concrete, it is recommended to consider the specimen length effect in evaluating the axial stress–strain relationship. Full article

The polytetrafluoroethylene/aluminum (PTFE/Al) granular composite, a common formulation in impact-initiated energetic materials, undergoes mechanochemical coupling reactions under sufficiently strong dynamic loading. This investigation discusses the dynamic properties and the constitutive relationship of the PTFE/Al granular composite to provide a preliminary guide for the research on mechanical properties of a series of composite materials based on PTFE/Al as the matrix. Firstly, the 26.5Al-73.5PTFE (wt.%) composite specimens are prepared by preprocessing, mixing, molding, high-temperature sintering, and cooling. Then, the quasi-static compression and Hopkinson bar tests are performed to explore the mechanical properties of the PTFE/Al composite. Influences of the strain rate of loading on the yield stress, the ultimate strength, and the limited strain are also analyzed. Lastly, based on the experimental results, the material parameters in the Johnson–Cook constitutive model are obtained by the method of piecewise fitting to describe the stress–strain relation of the PTFE/Al composite. Combining the experimental details and the obtained material parameters, the numerical simulation of the dynamic compression of the PTFE/Al composite specimen is carried out by using the ANSYS/LS-DYNA platform. The results show that the computed stress–strain curves present a reasonable agreement with the experimental data. It should be declared that this research does not involve the energy release behavior of the 26.5Al-73.5PTFE (wt.%) reactive material because the material is not initiated within the strain rate range of the dynamic test in this paper. Full article

Bamboo scrimber is an environmentally friendly biomass building material with excellent mechanical properties. However, it is susceptible to delamination failure of the transverse fibers under compression, which limits its structural performance. To address this problem, this study utilizes steel tubes to encase bamboo scrimber, forming a novel bamboo scrimber-filled steel tubular column. This configuration enables the steel tube to provide effective lateral restraint to the bamboo material. Axial compression tests were conducted on 18 specimens, including bamboo scrimber columns and bamboo scrimber-filled steel tubular columns, to investigate the effects of steel ratio and loading mode (full-section and core loading) on the axial compression performance. The test results indicate that the external steel tubes significantly enhance the structural load-bearing capacity and deformation capacity. Primary failure modes of the composite columns include shear failure and buckling. The ultimate stress and strain of the structure are positively correlated with the steel ratio; as the steel ratio increases, the ultimate stress of the specimens can increase by up to 19.2%, while the ultimate strain can increase by up to 37.7%. The core-loading specimens exhibited superior load-bearing capacity and deformation ability compared to the full-section-loading specimens. Considering the differences in the curves for full-section and core loading, the steel tube confinement coefficient was introduced, and the predictive models for the ultimate stress and ultimate strain of the bamboo scrimber-filled steel tubular column were developed with accurate prediction. Full article

The deformation behavior of polymers is influenced not only by service conditions such as temperature and the strain rate but also significantly by the formation process. However, existing simulation frameworks typically treat injection molding and the in-service mechanical response separately, making it difficult to capture the impact of the thermal history on large deformation behavior. In this study, the deformation behavior of injection-molded polycarbonate (PC) was investigated by accounting for its thermal history during formation, achieved through combined experimental characterization and constitutive modeling. PC specimens were prepared via injection molding followed by annealing at different molding/annealing temperatures and durations. Uniaxial tensile tests were conducted using a Zwick universal testing machine at strain rates of 10⁻³–10⁻¹ s⁻¹ and temperatures ranging from 293 K to 353 K to obtain stress–strain curves. The effects of the strain rate, testing temperature, and annealing conditions were thoroughly examined. Building upon a previously proposed phenomenological model, a new constitutive framework incorporating thermal history effects during formation was developed to characterize the large deformation behavior of PC. This model was implemented in ABAQUS/Explicit using a user-defined material subroutine. Predicted stress–strain curves exhibit excellent agreement with the experimental data, accurately reproducing elastic behavior, yield phenomena, and strain-softening and strain-hardening stages. Full article

The shape, size, and interfacial transition zone (ITZ) of aggregates significantly impact the nonlinear mechanical behavior of concrete. This study investigates concrete’s mechanical response and damage mechanisms by developing a three-dimensional, three-phase mesoscale model comprising coarse aggregates, mortar, and ITZ to explore the compressive performance of concrete. A method for simulating the random distribution of aggregates based on three-dimensional grid partitioning is proposed, where the value of each grid point represents the maximum aggregate radius that can be accommodated if the point serves as the aggregate center. Aggregates are generated by randomly selecting grid points that meet specific conditions, avoiding overlapping distributions and significantly improving computational efficiency as the generation progresses. This model effectively enhances the precision and efficiency of aggregate distribution and provides a reliable tool for studying the random distribution characteristics of aggregates in concrete. Additionally, an efficient discrete element model (DEM) was established based on this mesoscale model to simulate the compressive behavior of concrete, including failure modes and stress–strain curves. The effects of aggregate shape and maximum aggregate size on the uniaxial compressive failure behavior of concrete specimens were investigated. Aggregate shape has a particular influence on the compressive strength of concrete, and the compressive strength decreases with an increase in maximum aggregate size. Combined with existing experimental results, the proposed mesoscale model demonstrates high reliability in analyzing the compressive performance of concrete, providing valuable insights for further research on the mechanical properties of concrete. Full article

Due to the frequent occurrence of coarse-grained structures in large hydrogenation tube sheets, their hydrogen resistance and corrosion resistance deteriorate, significantly shortening their service life. Therefore, microstructure evolution must be strictly controlled during the forging process. High-temperature compression tests were simulated using a Gleeble-1500D thermal simulator to investigate the hot deformation behavior of 14Cr1Mo pressure vessel steel under deformation conditions of 1050–1250 °C and strain rates of 0.01–1 s⁻¹. Based on the experimental data, the flow stress curve of 14Cr1Mo steel was obtained, and its thermal deformation behavior was analyzed. Furthermore, the dynamic recrystallization (DRX) kinetic model and grain size model of 14Cr1Mo steel were established. These models were then integrated into the finite element software Forge^® to validate the accuracy of the DRX models. The results showed excellent agreement between the simulated and experimentally measured grain sizes, with a maximum deviation of less than 8%, confirming the high accuracy of the dynamic recrystallization models. These models provide a theoretical basis for finite element simulation and microstructure control in the manufacturing of super-large pressure vessel tube sheet forgings. Full article

The mesoscopic-scale discrete element method (DEM) modeling approach demonstrated high compatibility with macroporous recycled concrete (MRC). However, existing DEM models failed to adequately balance modeling accuracy and computational efficiency for recycled aggregate (RA), replicate the three distinct interfacial transition zone (ITZ) types and pore structure of MRC, or establish a systematic calibration methodology. In this study, PFC 3D was employed to establish a randomly polyhedral RA composite model and an MRC model. A systematic methodology for parameter testing and calibration was proposed, and compressive test simulations were conducted on the MRC model. The model incorporated all components of MRC, including three types of ITZs, achieving an aggregate volume fraction of 57.7%. Errors in simulating compressive strength and elastic modulus were 3.8% and 18.2%, respectively. Compared to conventional concrete, MRC exhibits larger strain and a steeper post-peak descending portion in stress–strain curves. At peak stress, stress is concentrated in the central region and the surrounding arc-shaped zones. After peak stress, significant localized residual stress persists within specimens; both toughness and toughness retention capacity increase with rising porosity and declining compressive strength. Failure of MRC is dominated by tension rather than shear, with critical bonds determining strength accounting for only 1.4% of the total. The influence ranking of components on compressive strength is as follows: ITZ (new paste–old paste) > ITZ (new paste–natural aggregates) > new paste > old paste > ITZ (old paste–natural aggregates). The Poisson’s ratio of MRC (0.12–0.17) demonstrates a negative correlation with porosity. Predictive formulas for peak strain and elastic modulus of MRC were established, with errors of 2.6% and 3.9%, respectively. Full article

Deep-sea oil and gas pipelines undergo significant plastic strain during reel-lay installation. Additionally, the static strain aging phenomenon that occurs during service can further deteriorate the mechanical properties of the pipelines. This study investigates the plastic deformation mechanism of reel-lay pipeline steel by subjecting the test steel to 5% pre-strain followed by aging treatment at 250 °C for 1 h. The present study systematically correlates the evolution of mechanical properties with microstructural changes through microstructural characterization techniques such as EBSD, TEM, and XRD. The results demonstrate that after pre-straining, the yield strength of the experimental steel increases due to dislocation strengthening and residual stress generation, while its uniform elongation decreases. Although no significant changes in grain size are observed macroscopically, microstructural characterization reveals a substantial increase in dislocation density within the matrix, forming dislocation cells and walls. These substructures lead to a deterioration of the material’s work hardening capacity. Following aging treatment, the tested steel exhibits further increased yield strength and reduced uniform elongation. After aging treatment, although the dislocation density in the matrix slightly decreases and dislocation tangles are somewhat reduced, the Cottrell atmosphere pinning effect leads to a further decline in work hardening capability, ultimately resulting in the deterioration of plasticity in reel-lay pipeline steel. The instantaneous hardening exponent curve shows that the work hardening phenomenon becomes more pronounced in the tested steel after strain aging as the tempering temperature increases. Full article

In this research, a single composite-type stretchable triboelectric nanogenerator (TENG) is proposed for efficient energy harvesting and handwriting recognition. The composite TENGs were fabricated by blending dielectric barium titanate (BT) and conductive carbon nanotubes (CNTs) in varying amounts into a styrene–butadiene rubber matrix. The energy harvesting efficiency depends on the type and amount of fillers, as well as their dispersion within the matrix. Stearic acid modification of BT enables near-nanoscale filler distribution, resulting in high energy conversion efficiencies. The composite achieved power efficiency, power density, charge efficiency, and charge density values of 1.127 nW/N, 8.258 mW/m³, 0.146 nC/N, and 1.072 mC/m³, respectively, under only 2% cyclic compressive strain at 0.85 Hz. The material performs better at low stress–strain ranges, exhibiting higher charge efficiency. The generated charge in the TENG composite is well correlated with the compressive stress, which provides a minimum activation pressure of 0.144 kPa, making it suitable for low-pressure sensing applications. A flat composite with dimensions of 0.02 × 6 × 5 cm³ can produce a power density of 26.04 W/m³, a charge density of 0.205 mC/m³, and an output voltage of 10 V from a single hand pat. The rubber composite also demonstrates high accuracy in handwriting recognition across different individuals, with clear differences in sensitivity curves. Repeated attempts by the same person show minimal deviation (<5%) in writing time. Additionally, the presence of reinforcing fillers enhances mechanical strength and durability, making the composite suitable for long-term cyclic energy harvesting and wearable sensor applications. Full article

Accurate calibration of mesoscopic contact model parameters is essential for ensuring the reliability of Particle Flow Code in Three Dimensions (PFC3D) simulations in geotechnical engineering. Trial-and-error approaches are often used to determine the parameters of the contact model, but they are time-consuming, labor-intensive, and offer no guarantee of parameter validity or simulation credibility. Although conventional machine learning techniques have been applied to invert the contact model parameters, they are hampered by the difficulty of selecting the optimal hyperparameters and, in some cases, insufficient data, which limits both the predictive accuracy and robustness. In this study, a total of 361 PFC3D uniaxial compression simulations using a linear parallel bond model with varied mesoscopic parameters were generated to capture a wide range of rock and geotechnical material behaviors. From each stress–strain curve, eight characteristic points were extracted as inputs to a multi-objective Automated Machine Learning (AutoML) model designed to invert three key mesoscopic parameters, i.e., the elastic modulus (E), stiffness ratio (k_s/k_n), and degraded elastic modulus (E_d). The developed AutoML model, comprising two hidden layers of 256 and 32 neurons with ReLU activation function, achieved coefficients of determination (R²) of 0.992, 0.710, and 0.521 for E, k_s/k_n, and E_d, respectively, demonstrating acceptable predictive accuracy and generalizability. The multi-objective AutoML model was also applied to invert the parameters from three independent uniaxial compression tests on rock-like materials to validate its practical performance. The close match between the experimental and numerically simulated stress–strain curves confirmed the model’s reliability for mesoscopic parameter inversion in PFC3D. Full article