Search Results (1,836)

Surface and sub-surface atomic configurations are critical for catalysis as they host the active sites governing electrochemical processes. This study employs density functional theory (DFT) calculations and Monte Carlo simulations combined with the cluster-expansion approach to investigate atom distribution and Pt segregation in Pt-Fe alloys across varying Pt/Fe ratios. Our simulations reveal a strong tendency for Pt atoms to segregate to the surface layer while Fe atoms enrich the sub-surface region. Crucially, the calculations predict the stability of a periodic Pt₂Fe alloy surface model, characterized by specific defect structures, at low platinum content and low annealing temperatures. Electronic structure analysis indicates that forming this Pt₂Fe surface alloy lowers the d-band center of Pt atoms, weakening CO adsorption and thereby enhancing resistance to CO poisoning. Although defect-induced strains can modulate the d-band center, crystal orbital Hamilton population (COHP) analysis confirms that such strains generally strengthen Pt-CO interactions. Therefore, the theoretical design of Pt₂Fe alloy surfaces and controlling defect density are predicted to be effective strategies for enhancing catalyst resistance to CO poisoning. This work highlights the advantages of periodic Pt₂Fe surface models for anti-CO poisoning and provides computational guidance for designing efficient Pt-based electrocatalysts. Full article

The increasing demand for electricity in multi-tenanted residential areas has placed unforeseen strain on sub-transformers, particularly in dense urban environments. This strain compromises overall grid performance and challenges utilities with shifting and rising peak demand periods. This study presents a novel approach to enhance the operation of a virtual power plant (VPP) comprising a microgrid (MG) integrated with renewable energy sources (RESs) and energy storage systems (ESSs). By employing an advanced monitoring and control system, the proposed topology enables efficient energy management and demand-side control within apartment complexes. The system supports controlled electricity distribution, reducing the likelihood of unpredictable demand spikes and alleviating stress on local infrastructure during peak periods. Additionally, the model capitalizes on the large number of tenancies to distribute electricity effectively, leveraging locally available RESs and ESSs behind the sub-transformer. The proposed research provides a systematic framework for managing electricity demand and optimizing resource utilization, contributing to grid reliability and a transition toward a more sustainable, decentralized energy system. Full article

Current asphalt pavement structural design methods often lack a strong quantitative link to materials’ mixtures and mechanical properties and typically ignore the significant tensile–compressive disparities of materials, resulting in notable analysis errors. This study employed the dual-modulus theory to numerically analyze flexible base asphalt pavements under varied configurations, revealing how critical structural responses and fatigue life evolve. This examination also determined optimal layer mixes through mechanical parameter modeling for integrated material–structure design. The results showed that fundamental responses and fatigue life vary nonlinearly with thickness and modulus. The effect of modulus outweighed that of thickness, with the effects of the tensile modulus being more pronounced than compressive ones, and surface transverse strain being most sensitive to both. The recommended compressive–tensile modulus ratios were about 1.5, 2.0, and 1.2 for upper, lower, and base layers, respectively. By using this integrated design method, the optimized pavement structures achieved superior stress distribution, significantly extending the base service life. As a result, more realistic design lifetimes were obtained. Full article

Fe³⁺-incorporated hydrogels are particularly valuable for wearable devices due to their tunable mechanical properties and ionic conductivity. However, conventional immersion-based fabrication fundamentally limits hydrogel performance because of heterogeneous ion distribution, ionic leaching, and scalability limitations. To overcome these challenges, we report a novel one-pot strategy where controlled amounts of Fe³⁺ are directly added to polyacrylamide-sodium acrylate (PAM-SA) precursor solutions, ensuring homogeneous ion distribution. Combining this with Photoinduced Electron/Energy Transfer Reversible Addition–Fragmentation Chain Transfer (PET-RAFT) polymerization enables efficient hydrogel fabrication under open-vessel conditions, improving its scalability. Fe³⁺ concentration achieves unprecedented modulation of mechanical properties: Young’s modulus (10 to 150 kPa), toughness (0.26 to 2.3 MJ/m³), and strain at break (800% to 2500%). The hydrogels also exhibit excellent compressibility (90% strain recovery), energy dissipation (>90% dissipation efficiency at optimal Fe³⁺ levels), and universal adhesion to diverse surfaces (plastic, metal, PTFE, and cardboard). Finally, these Fe³⁺-incorporated hydrogels demonstrated high effectiveness as strain sensors for monitoring finger/elbow movements, with gauge factors dependent on composition. This work provides a scalable, oxygen-tolerant route to tunable hydrogels for advanced wearable devices. 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

The structural units with different characteristic scales in gradient nanostructured (GS) 316L stainless steel act synergistically to achieve the matching of strength and plasticity, and the intrinsic plasticity of nanoscale and ultrafine grains is fully demonstrated. The macroscopic stress–strain responses of each material unit in the GS surface layer can be measured directly by tension or compression tests on microspecimens. However, the experimental results based on microspecimens do not reflect either the extraordinary strengthening effect caused by non-uniform deformation or the intrinsic plasticity of nanoscale and ultrafine grains. In this paper, a method for constructing depth-dependent constitutive relationships of GS materials was proposed, which combines strain hardening parameter (hardness) with physics-informed neural networks (PINNs). First, the microhardness distribution on the specimen cross-sections was measured after stretching to different strains, and the hardness–strain–force test data were used to construct the depth-dependent PINNs model for the true strain–hardness relationship (PINNs_εH). Hardness–strain–force test data from specimens with uniform coarse grains were used to pre-train the PINNs model for hardness and true stress (PINNs_Hσ), on the basis of which the depth-dependent PINNs_Hσ model for GS materials was constructed by transfer learning. The PINNs_εσ model, which characterizes the depth-dependent constitutive relationships of GS materials, was then constructed using hardness as an intermediate variable. Finally, the accuracy and validation of the PINNs_εσ model were verified by a three-point flexure test and finite element simulation. The modeling method proposed in this study can be used to determine the position-dependent constitutive relationships of heterogeneous materials. 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

Beach Sand Mycobiome is currently among the most important health challenges for viticulture in the world. Remarkably, the study of fungal communities in coastal beach sand and recreational waters remains underexplored despite their potential implications for human health. This research aimed to assess the prevalence of fungal species and the antifungal susceptibility profiles of fungi recovered from the beaches of the Persian Gulf and the Sea of Oman. Sand and seawater samples from 39 stations distributed within 13 beaches along the coastline were collected between May and July 2023. The grown isolates were identified at the species level based on morphological characteristics and DNA sequencing. Antifungal susceptibility testing was performed according to the Clinical Laboratory Standards Institute guidelines. Of 222 recovered isolates, 206 (92.8%) filamentous fungi and 16 (7.2%) yeast strains were identified. Sand-recovered fungi comprised 82.9%, while water-originated fungi accounted for 17.1%. The DNA sequencing technique categorized 191 isolates into 13 genera and 26 species. The most recovered genus was Aspergillus (68.9%), and Aspergillus terreus sensu stricto was the commonly identified species (26.14%). Voriconazole was the most effective antifungal drug against Aspergillus species. Research on fungal contamination levels at these locations could provide a foundation for establishing regulatory frameworks to diminish fungal risks, thereby enhancing public health protection. The ecological significance of fungal communities in sandy beaches to human infections remains to be explored, and earlier reports in the literature may motivate researchers to focus on detecting this mycobiome in natural environments where further investigation is warranted. Ultimately, our discovery serves as a reminder that much remains to be learned about pathogenic fungi and underscores the need for vigilance in areas where emerging pathogens have not yet been identified. Full article

In this study, we present a flexible piezoelectric nanogenerator based on a zinc oxide (ZnO)/polyvinylidene fluoride (PVDF) nanocomposite electrospun onto a hemisphere-patterned PDMS substrate. The nanogenerator was fabricated by replicating a silicon mold with inverted hemispheres into PDMS, followed by direct electrospinning of ZnO-dispersed PVDF nanofibers. Varying the ZnO concentration from 0.6 to 1.4 wt% allowed us to evaluate its effect on structural, dielectric, and piezoelectric properties. The nanogenerator containing 0.8 wt% ZnO exhibited the thinnest fibers (371 nm), the highest β-phase fraction (85.6%), and the highest dielectric constant (35.8). As a result, it achieved the maximum output voltage of 7.30 V, with excellent signal consistency under an applied pressure of 5 N. Comparisons with pristine PVDF- and ZnO/PVDF-only devices demonstrated the synergistic effect of ZnO loading and patterned PDMS on the enhancement of piezoelectric output. The hemisphere-patterned PDMS substrate improved the mechanical strain distribution, interfacial contact, and charge collection efficiency. These results highlight the potential of ZnO/PVDF/PDMS hybrid nanogenerators for use in wearable electronics and self-powered sensor systems. Full article

In practical engineering, buildings are predominantly subjected to combined forces, and reinforced concrete (RC) beams serve as the primary load-bearing components of buildings. However, there is a paucity of research on the torsional effects of RC beams, particularly concerning the torsional failure mechanisms of large-size beams. To address this gap, this paper establishes a meso-scale numerical analysis model for RC beams reinforced with Carbon Fiber Reinforced Polymer (CFRP) sheets under combined bending and torsion pressures. The research analyzes how the fiber ratio and torsion-bending ratio govern torsion-induced failure characteristics and size effects in CFRP-strengthened RC beams. The results indicate that an increase in the fiber ratio leads to accumulated damage distribution in the RC beam, a gradual decrease in CFRP sheet strain, and an increase in peak load and peak torque, albeit with diminishing amplitudes; as the torsion-bending ratio increases, crack distribution becomes more concentrated, the angle between cracks and the horizontal direction decreases, overall peak load decreases, peak torque increases, and CFRP sheet strain increases; and the nominal torsional capacity of CFRP-strengthened RC beams declines with increasing size, exhibiting a reduction of 24.1% to 35.6%, which distinctly demonstrates the torsional size effect under bending–torsion coupling conditions. A modified Torque Size Effect Law is formulated, characterizing in quantitative terms the dependence of the fiber ratio and the torsion-bending ratio. Full article

This paper, based on the Johnson–Cook damage model, investigates the damage mechanism of high-strength steel tailor welded blanks (TWBs) (Usibor1500P and Ductibor500) during the forming process. Initially, specimens with varying notch sizes were designed and fabricated to perform uniaxial tensile tests to determine their mechanical properties. Then, the deformation process of the notched specimens was simulated using finite element software, revealing the distribution and variation of stress triaxiality at the fracture surface. By combining both experimental and simulation data, the parameters of the Johnson–Cook (J–C) damage model were calibrated, and the effects of temperature, strain rate, and stress triaxiality on material fracture behavior were further analyzed. Based on finite element analysis, the relevant coefficients for stress triaxiality, strain rate, and temperature were systematically calibrated, successfully establishing a J–C fracture criterion for TWB welds, Usibor1500P, and Ductibor500 high-strength steels. Finally, the calibrated damage model was further validated through the Nakajima-type bulge test, and the simulated Forming Limit Diagram (FLD) closely matched the experimental data. The results show that the analysis based on the J–C damage model can effectively predict the fracture behavior of tailor welded blanks (TWB) during the forming process. This study provides reliable numerical predictions for the damage behavior of high-strength steel laser-customized welded sheets and offers a theoretical basis for engineering design and material performance optimization. Full article

The potential damage to aviation products caused by vibration and shock during road transportation has long been overlooked, despite structural failure under dynamic loading emerging as a critical technical challenge affecting product reliability. For aviation components, both stress and vibration analysis are essential prerequisites prior to formal assembly. This study investigates a symmetric vertical tail, a common aviation structure, employing an innovative model group analysis method to characterize its dynamic stress and strain distributions under real transportation conditions. Experimental measurements of vibration acceleration and impact loads during transport served as input data for constructing a numerical model based on stress and vibration theory. The model elucidates the mechanical responses of the tail in both modal and vibrational states, enabling effectively evaluation of dynamic vibrations on the tail and its critical subcomponents during road transport. The findings provide actionable insights for optimizing aviation component packaging design, mitigating vibration-induced damage, and enhancing transportation safety. Full article

This article describes the interactions between radon emissions and tectonic movements that accompany seismic activity as a function of time. The interpretation is based on advanced data analysis methods, such as Fourier wavelet transform, SGolay correlation analysis, and time-based data categorization. The dataset comprised the measurement results of ²²²Rn activity concentrations and the effects of the tectonic activity of rock masses acquired from two water-tube tiltmeters and five SRDN-3 radon probes. The analysis included four seismic events with moderate and light magnitudes (≥4.0), with a hypocenter at a depth of 1–10 km, located approximately 75 km from the research site. Each seismic shock had a different distribution of rock mass phases recorded by the integrated (probe-tiltmeter) measurement system. The results indicate that at the research site, the radon-tectonic signal is best identified between 25 and 48 h and between 49 and 72 h before the seismic shock. Positive correlations between the tectonic signal and the radon signal associated with the tension phase in the rock mass and negative correlations between the tectonic signal and the radon signal associated with the compression phase allow the description of the behavior of the rock mass before the seismic shock. Mixed correlations (positive and negative) indicate that both the stress and strain phases of the rock mass are recorded. The observed correlations seem particularly promising, as they can be recorded already 1–3 days before the seismic event, allowing an appropriately early response to the expected seismic event. Full article

Curved plate forming is essential in shipbuilding but traditionally relies on manual methods with low efficiency. Achieving automation in curved plate forming requires robust methods to generate processing solutions. This paper introduces a novel method for deriving the processing routes and strain distributions necessary to form complex curve plate using integrated heating and mechanical rolling forming equipment. The key aspects of this method include analyzing the target surface and solving for the required processing strains based on finite element analysis, discretizing the strain paths and refining them into engineering-feasible processing routes, deriving processing schemes from the calculated strains, and predicting and validating the processing schemes using the inherent strain method. The method is validated by applying it to typical surface of ship hull plates. Key outcomes demonstrate the method’s effectiveness and applicability: (1) The proposed method effectively establishes a quantitative relationship between the target surface geometry, processing routes, and the required processing strains. (2) By analyzing various target surface cases, the method demonstrates wide applicability. Standardized procedures can be applied to different surface shapes to derive the necessary processing routes and strains, thereby laying a solid foundation for the automation of curved hull plate forming. (3) Experimental forming tests on typical curved surfaces confirm that the processing schemes based on the proposed strain generation method can reliably achieve the desired geometries, showcasing the method’s capability to guide practical forming processes. The comparison between the formed and target shapes shows that the processing deviation of the schemes generated by this method remains within 5 mm, demonstrating high accuracy. Full article

This study establishes a multiphysics coupling model of acoustics, mechanics, and electrostatics through COMSOL, systematically explores the sound field distribution and stress–strain characteristics of tailing particles in sand silos under different frequencies of ultrasonic radiation, and proposes an optimization scheme for the sound field. The simulation results show that under 28 kHz ultrasonic radiation, the amplitude of sound pressure in the sand silo (173 Pa) is much lower than that at 40 kHz (1220 Pa), which can avoid damaging the original settlement mode of the tail mortar. At the same time, the periodic fluctuation amplitude of its longitudinal sound pressure is significantly greater than 25 kHz, which can promote settlement by enhancing particle tensile and compressive stress, achieving the best comprehensive effect. The staggered placement scheme of the transducer eliminates upward disturbance in the flow field by changing the longitudinal opposing sound field to oblique propagation, reduces energy dissipation, and increases the highest sound pressure level in the compartment to 130 dB. The sound pressure distribution density is significantly improved, further enhancing the settling effect. This study clarifies the correlation mechanism between ultrasound parameters and tailings’ settling efficiency, providing a theoretical basis for parameter optimization of ultrasound-assisted tailing treatment technology. Its results have important application value in the optimization of tailings settling in metal mine tailing filling. Full article