Search Results (3,996)

Deflection is a crucial indicator for structural safety assessment and maintenance of engineering structures. Traditional deflection inspection methods are confronted with the difficulty in selecting reference points, and therefore these methods are usually applied in short-term monitoring of structures. In this context, a novel strategy for automatic deflection inspection of beam-like composite structures which overcomes the difficulty in selecting reference points is put forward in this article. First, deflection assessment of composite structures using long-gauge fiber optic sensing was theoretically established. The relationship between vertical displacement and monitored average strain is irrelevant to external loads. The approach is applicable to both linear and nonlinear stages of structures, and deflection distribution along the structures can be estimated. Second, a four-point loading experiment on a wood–concrete composite beam which was installed with long-gauge fiber optic sensors was performed to verify the reliability of the deflection inspection method. Deflection was estimated under three conditions: (1) without considering composite action; (2) considering composite action but neglecting interface slip; and (3) considering both composite action and interface slip. Meanwhile, displacement meters were also installed to verify the calculated results. Experimental results indicate that the presented strategy has high precision. Hence, the presented method serves as an innovative option for assessing composite structures in both the short and long term. Full article

The aim of the current study is to determine the nutritional value and the content of the biologically active components in kidney vetch (Anthyllis vulneraria L.). It is established that the dry biomass contains substantial amounts of proteins and carbohydrates, primarily dietary fiber, while the total oil content is relatively low (below 3.0%). The isolated glyceride oil represents the complete lipid fraction derived from all plant parts (leaves, stems, and flowers). The glyceride oil of A. vulneraria is notable for its high levels of biologically active constituents, particularly sterols, tocopherols, and phospholipids. Palmitic (30.3%) and oleic (11.5%) acids dominate the fatty acid profile; β-sitosterol, α-tocotrienol, and α-tocopherol are the major sterol and tocopherol components, respectively. On the other hand, phosphatidylinositol, together with phosphatidic acids, prevails within the phospholipid fraction. Based on the obtained fatty acid composition, several important ratios were calculated—unsaturated fatty acids (UFA)/saturated fatty acids (SFA), saturated fatty acids/monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA)/saturated fatty acids, and n-6/n-3, providing an integrated assessment of the lipid quality. The PUFA/SFA value (0.24) suggests relatively high oxidative stability. In contrast, the n-6/n-3 ratio (0.86) shows a balanced distribution of essential fatty acids, which is associated with favorable nutritional properties. Full article

Currently, clustering algorithms are mainly used to classify fiber-reinforced composite cylinder damage. However, the number of clustering categories is heavily influenced by the evaluation criteria, and the real damage type categorization cannot be determined. Therefore, we propose a semi-supervised algorithm that obtains higher damage classification information with a small number of labels. Specifically, we first performed a phased fiber-reinforced composite cylinder pressurization experiment and collected damage signals through acoustic emission (AE) hits. We analyzed the damage types of the collected burst-type acoustic emission hits (each hit corresponds to a single waveform captured when the hit’s amplitude exceeds the preset threshold) and marked a small number of these hits. Then, we constructed a mean-teacher semi-supervised network structure based on transfer learning, achieving a classification accuracy of 85.92%. Compared to traditional supervised learning and clustering algorithms, the accuracy improved by nearly 30%. Full article

The fractional Whitham–Broer–Kaup model governs nonlinear wave propagation in memory-dependent media, including porous structures, viscoelastic fluids, and irregular seabeds, yet the full dynamical spectrum from quasi-periodicity to deterministic chaos, the role of stochastic forcing, and reliable identification from noisy data remains insufficiently explored, particularly how the fractional order $\beta$ influences these regimes. This study addresses these gaps through a comprehensive, multi-method dynamical analysis of a representative nonlinear oscillator embodying key FWBK features. Three-dimensional attractor visualizations, return maps, and surrogate data tests demonstrate a transition from quasi-periodic toroidal attractors to fully developed chaos via torus breakdown, confirming that observed complexity originates from deterministic nonlinearity. Poincaré sections reveal multistability and KAM-type structures, where coexisting attractors depend on initial conditions, while increasing noise progressively disrupts coherent dynamics. The OGY control method effectively stabilizes unstable periodic orbits across chaotic regimes with minimal perturbation, and Lyapunov analysis indicates that stochastic forcing attenuates chaos while enhancing dissipation. The Fokker–Planck framework shows that noise reshapes probability landscapes, driving transitions from unimodal to bimodal distributions. Comparative analysis of SINDy, JMAP and VBA highlights trade-offs in interpretability, computational efficiency, and uncertainty quantification, while an integrated Bayesian–PCE–Sobol approach quantifies parametric uncertainty and reveals time-dependent sensitivity variations. Additionally, the overlapping of soliton solutions extracted via the enhanced modified Sardar sub-equation method reveals structural relationships among soliton families and their stability under interaction. Soliton branches that maintain high overlap under noise correspond to stable regimes, while those losing coherence indicate the onset of chaos. Furthermore, while the reduced dynamics in $\eta$-space are independent of $\beta$, the fractional order controls spatial compression and temporal scaling in physical coordinates, directly influencing observable wave localization. These results imply that fractional effects can modify chaos transitions, support controllability through OGY, and influence noise–instability interactions depending on $\beta$. This framework provides a robust, transferable methodology for analyzing and controlling nonlinear oscillatory systems under deterministic and stochastic conditions, with direct applications to FWBK-based models in coastal engineering, fiber optics, and quantum interference systems. Full article

Basalt-fiber-reinforced recycled aggregate concrete (BFRAC) produced with 100% recycled coarse aggregate is still constrained by the inferior quality of recycled aggregate and the difficulty of optimizing fiber reinforcement parameters. This study investigated the effects of basalt fiber length configuration and dosage on the mechanical performance and pore structure of recycled aggregate concrete incorporating recycled coarse aggregate subjected to two-step pretreatment with nano-silica and cement slurry. Four fiber length configurations, namely 6, 12, and 24 mm and a mixed-length system, were evaluated at volume fractions of 0.1, 0.2, and 0.3%. The reinforcing effect was assessed through compressive strength, splitting tensile strength, scanning electron microscopy, mercury intrusion porosimetry, and statistical analysis. The pretreatment improved recycled aggregate quality, reducing water absorption from 4.97% to 3.11% and crushing index from 20.5% to 13.4%. Basalt fiber incorporation generally enhanced mechanical performance, although the response depended on fiber length and dosage. At 28 days, BF24V1 achieved the highest compressive strength, whereas BFmixV1 exhibited the best overall performance by combining high compressive strength with the highest splitting tensile strength. Relative to the average performance of the corresponding single-length mixtures at the same dosage, the mixed-length system showed a positive synergistic effect. Microstructural observations indicated that this behavior was associated with more effective crack bridging and refinement of the pore-size distribution. The results demonstrate that a low-dosage mixed-length basalt fiber system provides an effective route for upgrading pretreated waste-derived aggregate into higher-performance recycled aggregate concrete. Full article

The increasing accumulation of glass-fiber-reinforced polymer (GFRP) waste poses significant environmental challenges, calling for effective and scalable recycling strategies. In this work, a solvent-assisted cold mixing process was employed to incorporate very high amounts of GFRP (up to 75 wt%) into recycled expanded polystyrene (ePS). The composites were deeply characterized, with particular attention to the role of particle size distribution and filler content. The results demonstrated that GFRP granulometry played a key role in determining composite performance. Intermediate particle sizes (0.25 mm) provided the best balance between dispersion, interfacial interaction, and mechanical properties, whereas excessively fine fractions introduced defects and reduced impact resistance (from 0.7 to 2.0 kJ/m² going from dust to 0.25 mm at 75 wt%). Notably, the solvent-assisted approach has been widely recognized as an effective strategy to ensure homogeneous dispersion even at high filler contents, allowing subsequent melt processing without re-agglomeration. Recycled composites retained most of their chemical and mechanical properties after reprocessing, with only moderate performance losses mainly related to fiber fragmentation. Overall, this study demonstrates an effective and sustainable route for the simultaneous valorization of ePS and GFRP waste, enabling the production of highly loaded composites with preserved functionality and improved resource efficiency. Full article

Ancient pagodas are prone to damage or even collapse under seismic loading due to material aging and structural characteristics. To enhance the seismic performance of ancient pagodas, a seismic-strengthening design method for retrofitting ancient pagodas with embedded glass fiber reinforced polymer (GFRP) bars is proposed. The limit values of the story drift angle of ancient pagodas are statistically analyzed to determine the story drift angles at the elastic and elastic-plastic limit points. The corresponding solutions are proposed in view of the primary problems in the seismic reinforcement design of the ancient pagoda, such as the calculation of seismic shear force, the distribution of seismic shear force, and the calculation of shear bearing capacity. The seismic fortification target for the ancient pagoda is proposed with consideration of the special requirements of cultural heritage protection. The two-stage design method is further proposed to achieve the seismic fortification target. Taking the 1/8-scale model of the Xiaoyan Pagoda with cracks as an example, the design method proposed in the paper is used to carry out the reinforcement design with embedded GFRP bars. The proposed design method can provide a theoretical basis and technical reference for the seismic reinforcement of the ancient pagoda. Full article

To investigate the dynamic impact performance of carbon fiber reinforced polymer (CFRP)-confined recycled concrete, this study designed four series comprising 80 specimens with parameters including strain rate, recycled coarse aggregate replacement ratio, and number of CFRP confinement layers. Split Hopkinson Pressure Bar (SHPB) impact tests were conducted to analyze the dynamic failure mode, stress–strain responses under dynamic loading, and variation in compressive strength of the CFRP-confined concrete specimens. Additionally, a modified Weibull statistical model and fractal theory were employed to analyze the dispersion characteristics of dynamic compressive strength. The results show that the dynamic compressive strength exhibits clear strain-rate sensitivity. The presence of CFRP confinement does not alter the fundamental shape of the stress–strain curves under different strain rates. The proposed modified Weibull statistical model accurately predicts the distribution of dynamic compressive strength at varying strain rates, with an average prediction error of 3.4% and a maximum error of 5.3%. Fractal dimension can quantitatively characterize the evolution trend and degree of crack-induced damage. Within the strain rate range of 52.85–138.42 s⁻¹, the fractal dimension of unconfined ordinary concrete specimens increases from 1.647 to 2.138; for unconfined recycled concrete, it increases from 1.612 to 2.158. The fractal dimension for CFRP-confined ordinary concrete specimens increases from 1.524 to 1.938, and for CFRP-confined recycled concrete specimens, from 1.503 to 2.019. The fractal dimension increases with the increase of strain rate, reflecting a typical strain rate effect. Full article

Polycyclic aromatic hydrocarbons (PAHs) are widespread, persistent pollutants that can be sequestered within human adipose tissue due to their lipophilic nature. While this accumulation poses toxicological risks depending on dose and individual susceptibility, the specific morphological impact of chronic PAH storage on tissue architecture remains poorly defined. Here, we performed a histopathological and morphometric analysis on human subcutaneous adipose tissue samples characterized by high pyrene levels. We evaluated tissue organization, collagen distribution, the presence of inflammatory, neural, and vascular alterations and adipocyte morphometry to assess the structural response to PAH sequestration. Despite high pyrene concentrations, PAH-positive tissues maintained preserved overall architecture with normal collagen distribution, absence of lymphocytic infiltration, low macrophages, unaltered nerve fiber patterns, without evidence of vascular remodeling. Morphometry revealed smaller adipocyte area in PAH-positive samples, although not statistically significant. Our experimental data indicate that high PAH accumulation does not necessarily induce subcutaneous adipose tissue remodeling, suggesting that biochemical or metabolic alterations might occur even in the absence of evident histological changes. Further studies, with a broadened cohort, are needed to define the threshold at which PAHs’ presence translates into permanent tissue damage. Full article

The mechanical properties and real-time damage evolution of sustainable concrete (SC) containing 100% recycled concrete aggregate (RCA) under the combined action of hybrid steel and polyolefin fibers were studied. Inspired by solving the massive effects on the environment from construction waste, as well as to improve the lower mechanical performance of lower-grade RCA, the effect of combining high-stiffness hooked-end steel fibers and flexible macro-polyolefin fibers within RCA was investigated. Six different mix designs were considered: plain, single-fiber (100% steel and 100% polyolefin) and three hybrid composites with varying fractions of the steel/polyolefin fibers (25/75, 50/50, and 75/25). Compressive, tensile and flexural strengths were determined by mechanical testing. During compressive testing, the damage evolution was monitored using low-cost acoustic emission (AE) as a non-destructive technique. Cumulative hits analysis, amplitude distributions, and the statistical b-value parameter were used for damage characterization. The results show that steel fiber significantly increased compressive strength (an increase of up to 13.8%), and the 50/50 hybrid mix showed a high synergistic effect, yielding the highest tensile (4.86 MPa) and flexural (25.54 MPa) strengths. AE analysis identified different damage fingerprints: Based on amplitude analysis, steel-fiber composites exhibited high-amplitude events (which may be attributable to fiber pull-out); polyolefin-fiber composites generated medium-amplitude events (may have resulted from distributed microcracking); and hybrid mixes displayed a mixed amplitude distribution. The b-value analysis provided insight into progressive damage and revealed that the hybrid fibers induce stable, diffuse damage that prevents the brittle failure of plain recycled aggregate concrete (RAC). The results show that hybrid fiber reinforcement can be a reliable approach to enhance the mechanical performance and crack resistance of RAC. Furthermore, low-cost acoustic emission (AE) serves as an effective non-destructive method for monitoring damage progression within the material. Full article

The spatial organization of microscale fillers is critical for macroscopic performance, yet precise control over their distribution and orientation remains a major challenge in direct ink writing. Here, we present an acoustofluidic capillary nozzle that integrates acoustic manipulation into direct ink writing, enabling programmable in situ assembly of functional fillers during extrusion. By coupling a piezoelectric transducer with a commercial glass capillary, stable acoustic standing waves are established within the flow channel, driving suspended filler particles toward pressure nodes via acoustic radiation forces. Simulations and experiments systematically investigate how capillary geometry and material properties influence acoustic energy distribution and particle assembly behavior. In particular, rectangular capillaries generate stable multi-node standing waves, inducing periodic alignment of nickel-coated carbon fibers into ordered conductive bundles. This acoustically programmed microstructure reduces the percolation threshold from 8 wt% to 2 wt% and enhances electrical conductivity by up to 32.1-fold at identical filler contents. Meanwhile, the composites exhibit pronounced anisotropic conductivity and maintain excellent mechanical flexibility, with stable electromechanical performance under 16% bending strain and cyclic loading. This work demonstrates a simple and scalable acoustofluidic nozzle platform for programmable microstructure engineering in direct ink writing, offering new opportunities for fabricating high-performance multifunctional composites. Full article

Non-uniform fiber deposition remains a critical limitation in electrospun poly(lactic acid) (PLA) coating systems. In the present study, experimental characterization was combined with numerical simulations to evaluate the influence of electrospinning parameters on fiber morphology, coating uniformity, and thickness distribution. A 3% PLA solution was electrospun under different processing conditions by varying the applied voltage, needle-to-collector distance, flow rate, and deposition time. The resulting coatings were further analyzed using numerical simulations performed with ANSYS Fluent 2020 R2 software. The results demonstrated that both solution-related and operational parameters strongly influence fiber morphology and spatial deposition behavior. Increasing the applied voltage promoted the formation of thinner fibers; however, excessively high voltage values generated jet instability associated with fiber fragmentation and spray formation. Furthermore, the deposited fibrous layers showed preferential accumulation in the central region of the collector, together with a gradual decrease in coating thickness toward the peripheral areas. A strong correlation was observed between the numerical simulations and the experimental results, confirming the reliability of the proposed modeling approach. Among the investigated conditions, the optimal electrospinning parameters were identified as an applied voltage of 16 kV, a needle-to-collector distance of 17 cm, and a flow rate of 2.5 mL/h. These conditions enabled the formation of homogeneous PLA nanofibers with minimal structural defects and improved substrate adhesion. The combined experimental and numerical approach provides valuable insight into the optimization of electrospinning parameters governing fiber formation and deposition behavior. Full article

Background/Objectives: Patient-specific subperiosteal implants are increasingly used to treat severely atrophic ridges due to advances in digital planning and additive manufacturing. This study aimed to evaluate the effects of material type and implant configuration on stress distribution in subperiosteal implant systems and to compare their overall biomechanical performance using a multi-criteria decision framework. Methods: A three-dimensional model of a severely atrophic maxilla was reconstructed to simulate four clinical scenarios combining two configurations (one-piece and two-piece) and two materials (titanium and 60% carbon fiber-reinforced polyetheretherketone). Finite element analysis was conducted to assess stress distribution within the implant body, fixation screws, prosthetic framework, and surrounding bone under vertical and oblique loading conditions. Maximum and minimum principal stresses were evaluated in bone, whereas von Mises stresses were calculated for implant components. The resulting biomechanical indicators were subsequently integrated using an entropy weight–TOPSIS multi-criteria decision analysis. Results: Principal stresses in the surrounding bone showed minimal variation between titanium and 60% carbon fiber-reinforced polyetheretherketone across all configurations. Implant configuration had a more pronounced effect on implant body stress. Under oblique loading, the two-piece configuration demonstrated substantially higher implant stresses than the one-piece design, whereas under vertical loading, lower implant stresses were observed in the two-piece configuration. The multi-criteria analysis ranked the one-piece titanium model highest under oblique loading and the two-piece titanium model highest under vertical loading. Conclusions: Implant configuration and loading direction influenced biomechanical behavior more than material selection in patient-specific subperiosteal implants. Full article

Many machine-learning tasks involve structured data whose geometry, local feature distributions, and global organization interact in ways that are not well captured by existing methods based on vectorization, graph metrics, or homological signatures. We introduce Fiber Bundle Learning (FBL), a topological framework that represents each data sample as a discrete fiber bundle and extracts a classification signature combining persistent homology, local feature geometry, and gluing structure. FBL builds a base space from the coarse geometry of each object, models local feature patches as fibers, and estimates transition maps between neighboring fibers to construct a discrete connection. From this representation, FBL computes a set of invariants: persistent homology of the base, fibers, and total space; holonomy obtained by transporting fiber states along cycles; curvature-like quantities measuring transition inconsistency; and discrete analogues of characteristic classes. These components are assembled into a fixed-length feature vector that can be used with any standard classifier. We show that FBL yields a signature with three desirable theoretical properties: stability under perturbations of geometry and local features, invariance under isometries and global fiber reparameterizations, and robustness to sampling noise. Our synthetic experiments show that FBL distinguishes twisted from untwisted bundles with identical homology, a distinction classical topological methods fail to capture. Additional tests quantify the system’s resistance to noise, its invariance to geometric transformations, and the contribution of each signature component. Taken together, our results indicate that representing data through fiber bundle structure may provide an effective tool for classifying complex, multi-level objects. Full article

Viscose-derived carbon fibers (VDCFs) are lightweight and flexible textile materials with strong potential for electromagnetic interference (EMI) shielding; however, their performance is governed by surface chemistry. This study aims to tailor the functional properties of VDCFs via process-driven sulfurization. The fibers were treated with sulfur vapor at 400–800 °C under argon, followed by rapid quenching, enabling controlled sulfur incorporation (0.5–12 mmol g⁻¹). Structural and chemical analyses (XRD, SEM–EDS, ATR–FTIR, and TPD–MS) revealed temperature-dependent sulfur incorporation and evolution of sulfur-containing surface functionalities. Sulfurization at 400–500 °C favored the formation of thermally labile sulfur species, tentatively assigned to mercapto-, sulfide-, and polysulfide-type groups, whereas higher treatment temperatures promoted more thermally stable sulfur-containing functionalities associated with the carbon framework. Two desorption regimes (120–250 °C and 250–500 °C) indicate the coexistence of weakly and strongly bound sulfur species. Importantly, sulfurization preserved fibrous morphology while increasing surface roughness and defect density, enhancing interfacial activity. The treatment temperature was identified as the key factor controlling sulfur loading and distribution, with sulfur content continuing to decrease above 600 °C, albeit at a reduced rate. Electromagnetic characterization in the X-band (8–12 GHz) showed a transition toward reflection-dominated EMI shielding, with reflectivity increasing from 87% for pristine fibers to 94–95% for sulfurized samples at 10 GHz, accompanied by corresponding decreases in transmission and absorption. These results demonstrate a clear processing–structure–property relationship and highlight sulfur-functionalized VDCFs as efficient textile components for EMI shielding. Full article