Search Results (20,803)

This study seeks to elucidate the precise modulation of laser-assisted cold spray (LACS) particle deposition and to provide guidance for optimizing process parameters in LACS. While LACS has been shown to improve coating quality, the underlying roles of laser-induced thermal softening in particle deformation, impact energy redistribution, and interfacial bonding of 6061 Al alloy remain unclear. Here, multiscale finite element simulations and experiments were combined to investigate single-particle impact and coating build-up under different laser powers. The results indicate that laser assistance enhances thermal softening, leading to stronger radial spreading, more pronounced jetting, and a larger bonding interface. The simulations show that laser heating expands the thermal softening zone and shifts impact energy dissipation from the particle to the substrate, thereby reducing elastic rebound and promoting stable deposition. TEM analysis confirms dynamic recrystallization at the particle interface under all conditions, while higher laser power broadens the recrystallized region from approximately 0.7 μm to about 1.5 μm and promotes grain growth without causing additional oxidation. Moreover, coating porosity decreases from 3.1% to 1.0% with increasing laser power, whereas nanohardness decreases from 1.43 GPa to 1.24 GPa due to the increased contribution of thermal softening. Overall, the study demonstrates that the beneficial effect of laser assistance originates from thermally activated interfacial localization and energy redistribution, offering a mechanistic framework for optimizing the deposition of difficult-to-deposit aluminum alloys. Full article

This study investigates the transient wheel–rail contact mechanics of welded joints in heavy-haul rails via a validated 3D finite element model, and analyzes the stick-slip behavior, dynamic response and elastoplastic characteristics in the base material zone, heat-affected zone and weld bead zone. Results show a distinct contact state transition from stick-slip in the base material to predominant slip within the welded zones, indicating higher wear susceptibility. Dynamic response analysis reveals the highest and lowest contact-point acceleration amplitudes in the base material and heat-affected zone, respectively, due to material heterogeneity. Plastic deformation consistently initiates at the rail surface, where stress and strain concentrate, establishing it as the primary site for damage nucleation. A systematic parametric study shows that plastic deformation can be effectively mitigated by increasing the yield strength and elastic modulus of the welded joint material, or reducing the wheelset velocity, unsprung mass and wheel–rail friction coefficient. In contrast, adjusting the primary suspension and fastener parameters exerts a negligible influence on plastic deformation control. These findings provide a mechanistic basis for optimizing the performance and maintenance of welded joints in heavy-haul rail operations. This study reveals the coupling law of multiple mechanisms among contact behavior, dynamic response and material failure during the damage initiation process of rail welded joints from the mechanistic perspective, which provides a theoretical basis for the structural optimization, condition assessment and maintenance of rail welded joints in heavy-haul railways. Full article

This work proposes a design-oriented numerical modelling approach for predicting the seismic response of multi-storey Cross-Laminated Timber (CLT) buildings. The model is based on a phenomenological approach and is capable of accurately replicating the seismic behaviour of multi-storey CLT wall systems by means of a properly calibrated equivalent wall stiffness, taking into account both connections and panel deformability. An extensive set of multi-parametric linear analyses is performed to calibrate the wall equivalent stiffness by varying significant design parameters such as: CLT wall geometry, connection pattern, seismic mass and level of seismic intensity. An ad hoc iterative procedure is developed in order to calibrate the wall equivalent stiffness in terms of significant design parameters (e.g., principal elastic period, internal forces in the connection elements and inter-storey drifts). The aim of the procedure was to minimise the error between the results obtained with the proposed phenomenological model and those obtained with refined numerical models. The latter were designed to accurately reproduce the actual response of the CLT systems analysed. The results of the multi-parametric analyses are discussed and summarised in a design abacus that allows a direct implementation of the proposed phenomenological model and, therefore, a simple and efficient seismic analysis for CLT buildings. Full article

To explore the dynamic mechanical performance of metal rubber (MR) under high-speed impact loading, cylindrical solid MR specimens with spring coil outer diameters of 2–4 mm and relative densities of 0.2–0.35 have been prepared, and dynamic compression tests have been carried out utilizing the split Hopkinson pressure bar (SHPB) device at strain rates of 400–1000 s⁻¹. The dynamic stress–strain response of MR has been systematically analyzed, and the influences of strain rate, spring coil outer diameter, and relative density on its dynamic elastic modulus and energy absorption properties have also been quantitatively investigated. The results reveal that the dynamic stress–strain relationship of MR under high-speed impact presents significant nonlinearity and distinct strain rate effect. MR specimens with higher relative density, smaller spring coil outer diameter, or higher strain rate exhibit a larger dynamic elastic modulus, while those with higher relative density, larger spring coil outer diameter, or lower strain rate achieve higher energy absorption efficiency. A modified dynamic constitutive model for MR based on the Sherwood-Frost model has been developed by incorporating strain rate, relative density, and spring coil outer diameter as key influencing variables. The results show that the maximum mean relative error between the predicted and experimental data is less than 20%, indicating a favorable accuracy and reliability of the constitutive model. The proposed model can effectively characterize and predict the dynamic mechanical behavior of MR under high-speed impact loading conditions, providing a reliable theoretical basis for the engineering application of MR in impact-resistant structures. Full article

This study aims to investigate the influence of clay mineral content on the rheological properties and long-term deformation stability of clays, and to establish a unified model capable of quantitatively describing the nonlinear rheological behavior of clays with different mineral compositions. Direct shear rheological tests were conducted on specimens prepared with different mixing ratios of bentonite, kaolin, and quartz. Combined with micro-mechanism analysis, the controlling factors of clay rheological behavior were explored. The experimental results show that the creep stress threshold, elastic viscosity, and average plastic viscosity decrease significantly with increasing clay mineral content. The rheological deformation exhibits distinct nonlinear characteristics, and clay mineral content plays a controlling role in the rheological behavior. Based on experimental and mechanistic analysis, a unified rheological model was established, which reflects the material origin of rheology and captures nonlinear rheological characteristics. This model can predict the entire time-history mechanical behavior of clays with different mineral compositions across the three stages of instantaneous deformation, decay rheology, and steady-state rheology under different shear stress levels using a single set of parameters. Validation was performed through direct shear rheological tests under 50 working conditions for five types of clay specimens, demonstrating good consistency between the model calculations and experimental results. The unified rheological model reveals the material origin and physical essence of clay rheology, demonstrates high universality, and advances the understanding of the influence of mineral composition on rheology from the current phenomenological qualitative description to quantitative calculation for the first time, significantly enhancing its engineering application value. This provides a more reliable tool for predicting long-term deformation and assessing the stability of clay foundations. Full article

Objective: To evaluate the biomechanical effects of varying posterior implant inclinations and loading protocols on peri-implant stress distribution in full-arch maxillary rehabilitations using the All-on-Four concept. Methodology: A three-dimensional finite element model of an edentulous atrophic maxilla was developed from a digital point cloud. Four implants were placed according to the All-on-Four protocol: two anterior vertical implants and two posterior implants with inclinations of 0°, 15°, 30°, or 45°. Mini-abutments and a titanium bar prosthesis were included. Material properties were assumed as homogeneous, isotropic, and linearly elastic. Immediate loading was simulated using frictional contacts (µ = 0.3), whereas delayed loading assumed complete osseointegration (bonded contacts). The models were meshed using 10-node quadratic tetrahedral elements (SOLID187) in ANSYS^®. Maximum von Mises stress in cortical bone, cancellous bone, implants, abutments, and the prosthetic bar was assessed. Results: Posterior implant tilt significantly reduced peri-implant stress. Under immediate loading, the highest stress occurred at 0° inclination in the posterior left implant (82.36 MPa) and decreased progressively with increasing tilt, reaching 33.63 MPa at 45° (≈59% reduction). Delayed loading generally produces lower stress magnitudes, particularly at extreme tilts. Anterior implants experienced lower stress levels across all configurations. Comparative analysis demonstrated that immediate loading increased stress at lower angulations, while differences between loading protocols were minimal at higher inclinations. Conclusions: Posterior implant angulation and loading protocol critically influence peri-implant stress distribution. Increased posterior tilt combined with appropriate loading reduces peak cortical bone stresses, supporting biomechanical optimization in All-on-Four maxillary rehabilitations. Full article

Eringen’s integral constitutive relation is more general than its differential counterpart for modeling small-scale effects in micro- and nanostructures; however, it leads to integro-differential governing equations that are difficult to solve, which has limited the practical use of integral formulations. To directly address this gap, this paper introduces a novel symplectic-based numerical method that efficiently and accurately analyzes the free vibration of small-scale Kirchhoff plates governed by Eringen’s integral nonlocal model. The method discretizes the nonlocal integral operator by introducing inter-belt elements for long-range interactions and adopting a truncated influence domain, while balancing computational efficiency and accuracy. The effects of the nonlocal parameter, two-phase mixture parameter, mode numbers, kernel types, and geometric parameters on the natural frequencies are systematically investigated. The results indicate stiffness softening. For a simply supported square nanoplate with side length a = 10 nm, the first-order frequency parameter decreases by approximately 25% as the nonlocal parameter increases from 0 to 4 nm, and higher-order modes exhibit substantially greater sensitivity to nonlocal effects. Convergence and accuracy are validated against published continuum-level solutions and molecular dynamics simulations; relative deviations are below 2% in most cases, and the local limit (l_a = 0) yields errors on the order of 10⁻³. Full article

Non-destructive and destructive test methods are applied to wood to characterize this heterogeneous natural material. There have been multiple studies to characterize and investigate the change after the treatment (impregnation, thermal modification, etc.). In terms of thermal modification, there have been few studies on thermo–vacuum treatment, which is performed in a continuous vacuum atmosphere. With this method, the objective was to attempt to reduce the strength decrease after the thermal treatment. The aim of this study was to estimate the flexural properties of thermo–vacuum-treated Scots pine wood with destructive and acoustic-based non-destructive test methods. Wood was treated at 180 °C and 360 mm Hg. Both treated and untreated samples were cut into small specimens to ensure they were free of defects and were tested with acoustic-based non-destructive (longitudinal vibration and stress wave) and static bending test methods. The results show a decrease in equilibrium moisture content, demonstrating the efficiency of the treatment. When the results were compared with destructive test results, higher correlations (R² > 0.858) were found when estimating the modulus of elasticity (MOE) for both the untreated and treated wood, while lower correlations (R² < 0.440) were found for the modulus of rupture (MOR). When an additional equation was developed, stronger correlations (R² > 0.8986) were obtained between the non-destructive and destructive test results. Full article

Background: The skin microbiome plays a crucial role in maintaining barrier function and preventing inflammaging. Heat-treated probiotics offer stability advantages for topical formulations while potentially maintaining bioactive properties. Objective: To evaluate the safety, molecular mechanisms, and clinical efficacy of heat-treated Lactiplantibacillus plantarum Skinbac™ SB01 and Bifidobacterium animalis spp. lactis Skinbac™ SB05 in reducing visible signs of skin aging. Methods: In vitro studies assessed cytotoxicity (MTT/LDH assays), Aquaporin-3 (AQP3) expression, and reactive oxygen species (ROS) production in Normal Human Epidermal Keratinocytes (NHEK). A 30-day open-label clinical study (n = 20 females, 18–70 years) evaluated three formulations (face cream, serum, and eye contour) using instrumental measurements of hydration, elasticity, density, and roughness parameters. Results: In vitro testing showed a significant increase in AQP3 expression (+22% ± 3%, p = 0.03) and a non-significant reduction in ROS levels (−33% ± 9%, p = 0.06) at 10⁷ TFU/well, with no cytotoxicity observed. Clinical evaluation demonstrated statistically significant improvements: eye contour formulation achieved +10.5% deep skin hydration (p < 0.0001) and −11% average roughness (p < 0.0001); serum showed +28.7% immediate hydration (p < 0.0001); and face cream improved gross skin elasticity by +6.3% (p < 0.01). No adverse events were reported. An independent and methodologically distinct placebo-controlled study was included for contextual support and was not directly compared with the present trial; this study evaluated a related 1% postbiotic formulation and reported statistically significant improvements over placebo in roughness, wrinkle depth, hydration, and biomechanical parameters. Conclusions: This pilot study provides preliminary evidence that heat-treated L. plantarum SB01 and B. animalis spp. lactis SB05 formulations could safely improve skin hydration and reduce roughness parameters. While in vitro results show a significant increase in AQP3 expression and an exploratory (non-significant) reduction in ROS levels, larger controlled trials are warranted to confirm clinical efficacy. Full article

Carbon nanotube yarns (CNTYs) have received more consideration recently due to their excellent specific mechanical, electrical and thermal properties, making them promising materials for different applications. Until now, the axial properties of the yarn have been thoroughly investigated; however, the transverse or radial properties, orthogonal to the fiber axis, remain relatively unknown due to the challenges associated with their measurement. In this study, the transverse or radial response of the CNTY including its elastic modulus was determined using Atomic Force Microscopy (AFM) and Raman Spectroscopy. Determining transverse properties in fibrous materials presents challenges owing to their geometry, inherent anisotropy, whereby mechanical characteristics exhibit directional disparities; i.e., the properties in the transverse direction may be several orders of magnitude smaller than those in the axial direction. To overcome these difficulties, AFM was utilized to perform nanoindentation experiments, where a tipless flexible cantilever probe was used to apply a controlled force to the CNTY surface. The resulting indentation depth was then analyzed to determine the transversal elastic modulus. Preliminary findings indicate that the transverse elastic modulus of the CNTYs ranges from 10–54 kPa for strain levels below 3%. Complementary Raman spectroscopy provided insight into the bulk-scale mechanical behavior of CNTYs. Incremental compressive loading between microscope slides induced nonlinear upshifts in the 2D Raman band (from ~2686.6 to 2691.4 cm⁻¹), indicating nanoscale tube realignment, inter-tube densification, and compaction. From lateral diameter measurements under load, a stress–strain curve was constructed, revealing three distinct regimes: one with an initial elastic modulus of 3.12 MPa (0.3–11.2% strain), another one with an elastic modulus increasing to 8.46 MPa (11.2–14.4%), and finally one with an elastic modulus peaking at 16.86 MPa beyond 14.4% strain. Together, these methods delineate the hierarchical and anisotropic nature of CNTYs, validating the importance of multiscale mechanical characterization for their deployment in piezoresistive sensors and multifunctional composites. This study establishes a robust framework for quantifying the transverse mechanical response of CNTYs. Full article

In this study, the tensile properties, low-cycle fatigue behavior, and microscopic fatigue-failure mechanisms of 316H stainless steel in the temperature range of 600–800 °C were systematically investigated by means of tensile tests, high-temperature low-cycle fatigue tests, and scanning electron microscopy (SEM) analysis of fatigue fracture surfaces. Based on experimental data fitting, a life prediction model for the material in the high-temperature regime was established. The results indicate that the mechanical behavior of 316H stainless steel under both static and cyclic loading is significantly influenced by temperature and strain amplitude. Compared with its room-temperature properties, at 800 °C, the elastic modulus of 316H stainless steel decreases by approximately 30%, the tensile strength drops by about 60%, while the elongation after fracture increases by roughly 100%. Within the temperature range of 600–800 °C, the fatigue performance deteriorates with the increasing temperature, and the cyclic hardening rate accelerates as the temperature rises. The fracture mode in the instantaneous fracture zone of the fatigue fracture surface transitions from predominantly transgranular fracture to a mixed mode of transgranular and intergranular fracture as the temperature increases to 800 °C. Under higher strain amplitudes (around 0.6%), 316H stainless steel exhibits Masing behavior and dynamic strain aging (DSA). Correspondingly, the crack-initiation mode on the fatigue fracture surface shifts from a single surface source to multiple surface sources. A three-parameter model was employed to fit the strain–amplitude versus fatigue–life relationships of 316H stainless steel in the 600–800 °C range, showing good agreement with the experimental data, with most data points falling within a factor-of-two error band. Full article

This paper presents an experimental and numerical study on the effect of steel fiber distribution on the flexural behavior of self-compacting mortars (FRSCMs). Six FRSCM mixtures were modeled in ABAQUS as prismatic specimens (40 × 40 × 160 mm³) subjected to static three-point bending. The methodology involved two steps: (i) preparation of six mortar variants composed of three layers with different hooked steel fiber dosages (20, 30, and 40 kg/m³ for M20, M30, and M40) assembled in various configurations to study fiber distribution effects; (ii) numerical modeling of prismatic specimens in ABAQUS, using structured meshing with C3D8R hexahedral elements. Each layer was meshed separately with aligned nodes to ensure proper assembly. Our results highlight the strong influence of fiber distribution: despite identical fiber content (90 kg/m³ of hooked steel fibers), flexural strength varied across beam configurations. Layered casting led to an increase in flexural strength of up to 71.83% compared to the reference. The numerical predictions closely matched the experimental results, with relative errors ranging from 1% to 8.13% for most variants, demonstrating the reliability of the model. The larger discrepancies observed for specimens M324 and M342 are attributed to the limitation of the study to the elastic domain, as damage and plasticity effects were not included in the simulations. The distribution and orientation of fibers (particularly steel fibers) in a cementitious matrix, namely concrete or cement mortar, has been the subject of several studies aimed at determining the best mechanical performance of fiber-reinforced concrete. The proposed modeling approach of bending mechanical behavior allows us to predict the effects of fiber distribution in fluid mortars and reinforced self-compacting mortars, thereby reducing the need for extensive experimental testing. It also represents a significant improvement over existing approaches reported in the literature. Full article

Background: Extracellular vesicles (EVs) are increasingly explored as nanocarriers in drug delivery; however, selecting an appropriate loading strategy for a given small-molecule cargo still relies largely on empirical, resource-intensive parallel screening within EV formulation workflows. Despite the widespread application of passive incubation, electroporation, saponin-mediated permeabilization, freeze–thaw cycling, and sonication, there is currently no mechanistically grounded, descriptor-informed framework that enables rational prioritization of loading methods during the early design stage of EV-based dosage forms, leading to inefficient trial-and-error experimentation. Methods: We assembled a chemically diverse dataset of 21 compounds with experimentally determined loading efficiencies across five EV loading methods and calculated seven mechanistically motivated physicochemical descriptors (LogP, molecular weight, aqueous solubility, hydrogen bond donors/acceptors, polar surface area, and formal charge) for each drug. Separate Elastic Net regression models were trained for each loading strategy. Model performance was evaluated using leave-one-out cross-validation, a predefined external validation set (n = 4), and 50 repeated random train–test splits. The analysis emphasized decision-level ranking of loading methods rather than the precise prediction of absolute efficiencies. The applicability domain was assessed via leverage analysis to define the supported chemical space for prospective implementation in EV-based formulation development. Results: As anticipated for biologically heterogeneous EV systems, continuous regression performance remained modest (LOOCV R² = 0.06–0.41). In contrast, decision-level accuracy for identifying the experimentally optimal loading method was consistently high across validation schemes (internal: 76.5%; predefined external: 75%; repeated random validation: 80.5 ± 16.8%). Mechanical disruption methods (freeze–thaw and sonication) demonstrated comparatively greater predictive stability, while misclassification patterns suggested potential nonlinear behavior for highly polar, ionizable cargos. All compounds resided within the leverage-defined applicability domain, confirming adequate descriptor-space representation. Conclusions: This study establishes a mechanistically interpretable, descriptor-based decision-support framework capable of reliably prioritizing EV loading strategies for small-molecule cargos beyond empirical chance without altering standard protocols. By reframing the modeling objective from high-precision efficiency prediction to robust ranking of candidate methods, the approach offers a practical tool to triage between commonly used techniques, thereby reducing experimental burden in early-stage EV formulation development. The framework provides a quantitative basis for integrating molecular-descriptor-guided method selection into rational EV-based drug delivery design and can be expanded with membrane-specific descriptors and larger datasets. Full article

The geometry of ballasted railway tracks is crucial for ensuring railway safety and efficiency. This paper introduces the use of innovative steady-state algorithms designed to compute plastic strains in linear geotechnical structures like railway ballast layers, within Finite Element Methods (FEMs). Facing the specificities of moving loads, traditional step-by-step algorithms, while simple and adaptable, are computationally expensive and time-consuming. In contrast, the proposed steady-state algorithms leverage an Eulerian approach to describe the movement of loads significantly reducing computational time while maintaining accuracy. This paper proposes these algorithms as a methodological improvement and demonstrates the applicability and efficiency of the method for non-periodic structures, as well as for periodic structures, such as railway tracks with evenly spaced sleepers. This paper demonstrates the applicability and efficiency of theses algorithms through comparative studies with traditional methods on typical railway structures. The results show that the presented algorithm not only matches the accuracy of step-by-step methods but also drastically reduces computation time and data storage requirements. This advancement has practical applications for railway infrastructure managers, enabling more efficient and accurate predictions of track geometry evolution and preventing incidents through improved maintenance strategies. Full article

The highly competitive nature of the online food delivery (OFD) market faces a serious retention problem, with acquiring new users typically being much more expensive than retaining existing users. Traditional prediction methods that rely primarily upon static transactional metrics such as recency and frequency are often unable to capture the psychological ‘disconfirmation’ which occurs prior to churn. To fill this gap, this study proposes a framework based on Expectation-Confirmation Theory (ECT). Unsupervised K-Means clustering was employed to classify a simulated and filtered dataset with 1500 customer records containing behaviour, geography, etc. This framework also couples sentiment analysis from BERT, allowing it to identify psychological “silent” attrition. Heterogeneous cohorts, which exhibit different psychological antecedents (utilitarian versus hedonic), were identified. The empirical results of our analyses demonstrated that Random Forest Classifiers with segment-specific features outperform baseline transactional models (F1 = 0.76) with an F1 Score of 0.89. The visual analytic interface developed provides a holistic view of the consumption process than traditional prediction models, including prescriptive, automated segment-based mitigation strategies. Our findings contradict the assumption that the “frequency–loyalty” model applies to all users. High-frequency discretionary users are found to be elastic in terms of retention and will experience significant churn. By utilising the automated action log, managers can plan targeted, highly efficient retention strategies rather than blanket discounting approaches. Full article