Search Results (199)

Laminated carbon fiber reinforced polymer (CFRP) beams are widely used in lightweight structures, yet their vibration response depends strongly on laminate architecture, boundary conditions, thickness, and material anisotropy. Previous studies often examined these effects separately or relied on a single analytical or numerical approach. This study presents a multi fidelity framework integrating classical laminate theory (CLT), the Vinson–Sierakowski (VS) equivalent modulus method, and three-dimensional finite element analysis for modal prediction and parametric design of symmetric CFRP laminated beams. Three stacking sequences, [0/0/0/0], [0/45/45/0], and [0/90/90/0], were evaluated under clamped-free (CF) and clamped-clamped (CC) conditions. ANSYS models using quadratic HEX20 solid elements served as the numerical reference. Across 36 validation frequencies, the mean absolute percentage errors were 3.05% for CLT and 2.28% for VS, giving VS a 25.1% lower average error. The [0/0/0/0] laminate produced the highest frequencies. The first numerical frequency increased from 36.37 to 230.20 Hz when the boundary condition changed from clamped-free to clamped-clamped. Increasing thickness from 2 to 8 mm raised the first frequency from 18.20 to 72.62 Hz, while increasing $E_1/E_2$ from 10 to 30 raised it from 30.80 to 53.85 Hz. The framework supports rapid screening, laminate level interpretation, and detailed numerical verification for vibration-oriented composite beam design. Full article

Concrete-filled steel tube (CFST) structures are widely used in modern infrastructure due to their superior strength, ductility, and composite action. However, long-term corrosion of the steel tube, particularly under aggressive environmental conditions, poses significant challenges to their durability and structural performance. This study presents a comprehensive review of corrosion mechanisms and mitigation strategies for CFST structures. The primary corrosion processes, including general corrosion, localized (pitting) corrosion, and circumferential corrosion, are critically examined with emphasis on the influence of chloride ingress, carbonation, marine exposure, and combined environmental actions such as freeze–thaw cycles and sustained loading. The effects of corrosion on structural behavior are analyzed in terms of load-carrying capacity, ductility, buckling resistance, and failure modes. A systematic evaluation of existing mitigation strategies is conducted, encompassing material-based approaches, protective coatings, cathodic protection systems, and structural strengthening techniques such as fiber-reinforced polymer (FRP), fabric-reinforced cementitious matrix (FRCM), and steel jacketing. The comparative performance of these methods is assessed based on effectiveness, cost–benefit considerations, service life extension, and practical implement ability. The review highlights that no single mitigation strategy is universally optimal; instead, integrated approaches combining multiple techniques provide the most effective long-term protection. Key research gaps are identified in the areas of long-term performance monitoring, internal corrosion detection, and durability modeling under combined environmental actions. The findings of this study provide valuable insights for the design, maintenance, and rehabilitation of CFST structures, contributing to the development of more durable and sustainable infrastructure systems. Full article

An effective dermal scaffold is expected to provide a three-dimensional porous architecture that supports fibroblast adhesion, infiltration, and proliferation; evolve structurally to meet the progressive physiological needs of the entire healing process; and absorb without adverse tissue response during tissue repair. This study evaluates a fully synthetic absorbable composite electrospun matrix comprising three polymer components within a single fiber network, each contributing a distinct yet complementary function. Poloxamer 188 provides immediate wettability and conformability; PLGA undergoes progressive hydrolytic degradation over days, enlarging pore dimensions through fiber cleavage; and polydioxanone, as the slowest-degrading component, maintains the fiber network throughout this structural remodeling process. The matrix achieved instantaneous wetting and 91% maximum pore-equivalent diameter enlargement within 7 days, creating a microenvironment associated with progressive cellular accommodation. In vitro, fibroblasts adhered, remained fully viable, and exhibited Day-1 spreading on the 7-day pre-degraded matrices approaching that observed at Day 3 on fresh matrices, consistent with the evolving pore architecture facilitating initial cellular accommodation. In a splinted rat full-thickness wound model, the matrix accelerated wound-area reduction versus the control (Day 14: p < 0.001; Day 21: p < 0.01), was macroscopically undetectable by Day 14, and elicited no adverse foreign-body reaction. Quantitative collagen area fraction analysis (Masson’s trichrome) revealed significantly greater collagen content in the scaffold group at Day 7 (p < 0.05) and Day 28 (p < 0.01) relative to the control, suggesting that the composite matrix provides favorable conditions for collagen accumulation that persists into the remodeling phase. These findings demonstrate that the matrix functions as an effective dermal scaffold by providing an evolving pore architecture that supports fibroblast adhesion and accommodation, accelerating full-thickness repair throughout the healing trajectory, and undergoing safe absorption without adverse reactions, thereby highlighting its promising translational potential for clinical wound management. Full article

Transient extrusion defects are a fundamental process control challenge in fused granular fabrication (FGF), arising from the finite melt pressurization time of screw-driven extruders at each start–stop event. This study presents an integrated experimental and analytical framework for the characterization and open-loop feedforward compensation of these transient dynamics, demonstrated on two composite thermoplastic feedstocks: a recycled random polypropylene (RPP1) and a 20 wt% wood-fiber-reinforced polypropylene composite (WFPP). Unlike prior filament- or single-material feedforward strategies, this framework derives and statistically validates material-specific compensation parameters across two rheologically distinct feedstocks. Single-layer road experiments were conducted on a custom instrumented FGF platform across a 2³⁻¹ half-fraction factorial design varying melt temperature, print acceleration, and nozzle diameter, with screw speed stepped among 20, 40, and 80 RPM to excite transient states; deposited road geometry was digitized and spatially registered to the synchronized process signals. Main-effects regression confirmed that nozzle diameter is the dominant predictor of mean road width, while screw velocity exerts a significant negative effect attributable to speed-dependent backflow. Prediction-error minimization on the pooled multi-experiment dataset yielded a parsimonious first-order transfer function, G(s) = 0.990/(1 + 1.909s), whose time constant is physically attributed to melt compressibility in the barrel volume upstream of the nozzle restriction. This model was embedded in a G-code post-processor implementing two sequential corrections: a material-specific steady-state slip gain and a discrete linear-advance term parameterized by the identified time constant. For RPP1 at the nominal gain, the print latency interquartile range decreased from 5–20 mm to 2–8 mm without degrading steady-state dimensional accuracy; the combination of nominal gain with active retraction further reduced latency to near-zero. Analysis of covariance (ANCOVA) confirmed that optimal feedforward gains are statistically material-dependent across all three quality metrics (p < 0.05), providing statistical justification for material-specific compensator parameterization. The results establish a practical, hardware-agnostic route to reduce transient deposition defects in pellet-based additive manufacturing, extensible to additional feedstocks. Full article

Carbon fiber-reinforced thermoplastic composites (CFRTPs) have attracted increasing attention in aerospace, transportation, marine engineering, and other advanced manufacturing fields owing to their high specific mechanical properties, impact resistance, weldability, reprocessibility, and potential recyclability. However, the high melt viscosity of thermoplastic matrices, the permeability limitations associated with different reinforcement architectures, and the chemical inertness of carbon fiber surfaces continue to restrict resin impregnation, interfacial bonding, defect control, and forming stability. This review systematically summarizes recent advances in CFRTP manufacturing from the perspective of material-derived processing challenges and interface engineering. First, representative thermoplastic matrix systems and reinforcement architectures are discussed, with emphasis on their effects on processability, crystallization behavior, resin flow, and load transfer. Subsequently, six major forming processes, including hot stamping, injection molding, pultrusion, filament winding, automated fiber placement, and additive manufacturing, are critically compared in terms of processing principles, typical defects, technical limitations, and application boundaries. Particular attention is given to process-induced quality issues such as voids, wrinkling, springback, fiber breakage, warpage, insufficient consolidation, and weak interlayer bonding. Finally, interface engineering strategies, including chemical surface modification, interfacial structural design, and functional interlayer design, are reviewed as practical routes to improve wetting, shorten impregnation pathways, and enhance fiber–matrix load transfer in high-viscosity thermoplastic systems. This review highlights that CFRTP manufacturing should be understood as a coupled materials–processing–interface problem rather than a single forming operation. Future development is discussed with emphasis on reproducible manufacturing, processability-oriented materials, scalable interface engineering, predictive modeling, and standardized structural validation. Full article

A comprehensive experimental dataset for unidirectional carbon fiber pultruded composites is presented, including mechanical testing results, microscopy images, and X-ray computed tomography volumes. In contrast to typical datasets, all measurements consistently describe a single material system, encompassing both the composite and its constituents (carbon fibers and vinyl ester matrix), thereby enabling a comprehensive and coherent multiscale material characterization. X-ray-computed tomography images of samples extracted from three pultruded composite profiles were acquired with a voxel size of 0.55 µm and analyzed to determine the fiber orientation distribution. Scanning electron microscopy with a pixel size of 0.098 µm was used to determine the overall and local fiber volume fractions. Compression testing of 17 composite specimens provided the compressive properties. The tensile and shear properties of the matrix were obtained from tensile and shear tests on seven and four matrix specimens, respectively. The Ramberg-Osgood model was fitted to the matrix’s tensile stress–strain response. Single-fiber tensile testing was conducted on 255 carbon fibers with three gauge lengths to determine fiber properties and Weibull parameters. All mechanical tests were performed up to material failure. The dataset is suitable for semi-analytical predictions and numerical finite-element modeling of composite mechanical behavior. Full article

Composites are widely used in the building sector for high-rise building load-bearing components, bridge decks, prefabricated structural panels, and seismic-resistant members, where excellent mechanical performance and structural durability are critical. As specialized advanced composites, variable stiffness composites (VSCs) have gained increasing engineering applications due to their excellent overall performance. Nevertheless, exploring the fracture characteristics of composite materials, especially VSCs, remains a significant challenge. In particular, cracks in composite components can adversely affect structural integrity and durability. In this study, a dynamic fracture phase-field model for VSCs is developed within the framework of elastic dynamics to investigate crack propagation behavior of VSCs under dynamic loads. The proposed model is first validated by experimental results of fracture behavior of single-edge cracked FRC laminae. Then, the proposed model is employed to systematically study the effects of three fiber orientation design variables and internal defects on the fracture behavior of VSCs. Additionally, fiber trajectories are optimized for different pore distribution configurations. The results demonstrate that the model effectively captures the fracture behavior of VSCs and that optimizing these three design parameters enables the fabrication of high-performance VSCs with enhanced crack propagation resistance. This work provides fundamental insights for the design of curvilinearly fiber-reinforced composites and lays a solid theoretical foundation for the practical application of VSCs in building engineering. Full article

Pasture ecosystems are a key component of livestock production in arid and semi-arid regions, where forage availability and nutritive value are often associated with animal performance under grazing conditions. This study aimed to provide an exploratory assessment of pasture productivity, forage nutritive value, and beef cattle productivity across contrasting natural–climatic settings in Kazakhstan. The study was conducted under commercial production conditions on five farms representing different grazing environments during the 2024–2025 grazing seasons. Because each zone was represented by a single farm, the study should be interpreted as an observational assessment of farm-level patterns rather than as a fully replicated experimental comparison. Pasture productivity and forage chemical composition, including crude protein, fiber, and dry matter content, varied among farms and seasons. Average daily gain ranged from 316.7 to 900 g day⁻¹ depending on the study site and year of observation. Exploratory statistical analyses indicated variability among the studied systems; however, pairwise comparisons did not reveal statistically significant differences in animal productivity among farms (p > 0.05). Correlation analyses revealed moderate positive associations between average daily gain, crude protein content, and pasture yield, although these relationships were not statistically significant after adjustment for multiple comparisons. Similarly, linear models incorporating forage nutritive value indicators and study site did not identify statistically significant predictors of animal productivity within the current dataset. Overall, the results describe patterns of variation in pasture characteristics and animal productivity observed under extensive grazing conditions in continental environments. Given the observational design and limited replication at the farm level, the findings should be interpreted cautiously and regarded as preliminary. The study provides baseline information for future investigations of pasture–livestock interactions in arid and semi-arid grazing environments. Full article

The in-plane shear performance of carbon fiber-reinforced polymer (CFRP) composites is critical for structural design but is challenged by significant property scatter. This study aims to achieve individualized prediction of the complete shear stress–strain curve for each composite specimen using only a single early-stage digital image correlation (DIC) strain field. Systematic in-plane shear tests were conducted on 45 laminated carbon fiber/epoxy specimens with synchronized full-field DIC data and macroscopic load–displacement records. A lightweight encoder–decoder convolutional neural network was developed, taking a single DIC strain contour map at 0.2% global strain as input and mapping it directly to the full-range stress–strain curve up to failure for that specific specimen. Data augmentation and Dropout regularization mitigated the small-sample challenge. The proposed model achieved strong predictive performance across the five-fold cross-validation yielded a mean R² of 0.926 ± 0.022 and a mean RMSE of 6.37 ± 1.14 MPa for stress. Individual specimen predictions on the test set yielded an average R² of 0.945, with a minimum of 0.821, confirming robust capability across scattered properties. Residual analysis elucidated error characteristics across deformation stages. This research provides a novel paradigm for non-destructive, early-stage individualized assessment of composite mechanical properties, with applications in structural health monitoring and probabilistic design. Full article

Hemp and linseed are nutritionally valuable commodities that exhibit considerable varietal differences in composition. Nutrient composition was evaluated in 12 hemp and 11 linseed varieties, including commercially cultivated varieties from the EU Common Catalogue and newly bred lines, to assess varietal variability. Field experiments were conducted under uniform agronomic conditions in the Czech Republic during a single growing season using field-block samples. Analyses included proximate composition (dry matter, crude protein, fat, fiber, ash), fatty acid and amino acid profiles, carotenoids, vitamins, and cannabinoid content. Statistical evaluation was performed using a General Linear Model with Duncan’s multiple range test (p < 0.05). Significant differences were observed across most parameters, indicating substantial inter-varietal variability under the experimental conditions. Fat content ranged from approximately 200 to 377 g/kg in both oilseeds, with lipids dominated by polyunsaturated fatty acids, particularly linoleic (n-6) and α-linolenic (n-3) acids. Hemp and linseed show potential as alternative plant protein sources in animal nutrition, but further digestibility and feeding studies are needed to confirm their suitability as partial soybean meal substitutes. Varietal selection may contribute to improved nutritional quality while influencing levels of undesirable constituents such as Δ⁹-THC in hemp. Full article

Engineered cementitious composite (ECC) is a high-performance strain-hardening material widely used in durable infrastructure, yet its complex multi-parameter interactions make accurate mixture design and performance prediction challenging. This study aims to establish an EDFrame, which is an integrated prediction framework for engineered cementitious composite (ECC). First, two original datasets of ECC’s tensile stress and strain are collected from the comprehensive and authoritative literature, comprising 18 features and 10 categories of single or hybrid fibers. Data augmentation is then performed using a constraints-modified Conditional Tabular Generative Adversarial Network (Tuned-CTGAN), with two traditional methods for comparison. A One-Dimensional Convolutional Neural Network with a residual module (1D-Residual CNN) is developed to predict tensile stress and strain, and its performance was compared against five popular machine learning models. The interpretability of the proposed model has been achieved through Partial Dependence Plot (PDP) and Kernel SHAP analyses. The results demonstrate that Tuned-CTGAN effectively generates reliable synthetic data, significantly improving the R² of 1D-Residual CNN from 0.8658 to 0.9128 for tensile stress and from 0.8433 to 0.9378 for tensile strain, outperforming all compared models. PDP analysis identifies optimal fiber content (1.5–2%) and fiber length (12–20 mm) ranges for enhanced tensile performance, while SHAP analysis reveals fiber length and diameter as the most critical features influencing tensile stress and strain, respectively. The proposed EDFrame provides a robust and interpretable solution for ECC performance prediction, supporting efficient and accurate mixture design in engineering practice. Full article

High-performance fiber-reinforced cementitious composite (HPFRCC) has shown considerable potential as a strengthening material for improving the crack resistance, integrity, and deformation capacity of masonry structures. In aging concrete hollow block masonry walls subjected to long-term eccentric compression, material degradation may lead to premature cracking, local crushing, stiffness deterioration, and reduced safety margins, thereby adversely affecting structural reliability and service performance. However, studies on the eccentric compression behavior of HPFRCC-strengthened concrete hollow block masonry walls with simulated material degradation remain limited. In this study, experimental, finite element, and theoretical analyses were conducted on three HPFRCC-strengthened specimens with an eccentricity ratio of 0.5y, namely a 30 mm double-sided strengthened specimen, a 45 mm double-sided strengthened specimen, and a 30 mm single-sided strengthened specimen. The failure modes, load–displacement responses, lateral deformation, strain development, and DIC strain distribution characteristics were investigated. The results showed that, under the test conditions considered in this study, the double-sided strengthened specimens exhibited higher load-bearing capacity, greater stiffness, and better structural integrity than the single-sided strengthened specimen. Among them, the 45 mm double-sided strengthened specimen reached the highest peak load of 1643 kN, whereas the 30 mm double-sided strengthened specimen exhibited a gentler post-peak response, more dispersed crack development, and better deformation compatibility. The finite element results were generally consistent with the experimental results; the ratios of the experimental to numerical peak loads ranged from 0.96 to 1.01, while the corresponding peak displacement ratios ranged from 1.02 to 1.09. Within the parameter range considered in the numerical analysis, increasing the strengthening thickness was generally beneficial to the eccentric compression capacity. The proposed preliminary sectional bearing capacity model showed acceptable agreement with the test results for the specimens considered in this study; however, its broader applicability requires further validation using additional specimens. Full article

The intralaminar and interlaminar mode I initiation fracture toughness of unidirectional IM7/8552 carbon/epoxy composites were re-evaluated using only the published experimental data. Classical statistics, two-parameter Weibull analysis (location fixed at zero), non-parametric kernel density estimation (KDE), bootstrap resampling (10,000 replications), and bootstrap-based uncertainty quantification were applied to the fatigue-precracked (FPC) initiation values (n = 12) and the corresponding R-curves. The pooled FPC mean initiation toughness was 0.1982 kJ/m² (COV = 8.50%). Weibull fitting yielded a shape parameter β = 12.33 and scale η = 0.2058 kJ/m², providing a B-basis value of 0.1715 kJ/m² (90% reliability) and an A-basis value of 0.1417 kJ/m² (99% reliability). The Kolmogorov–Smirnov test confirmed statistical equivalence between intralaminar and interlaminar groups (p > 0.05), validating the use of a single initiation toughness for both crack planes when sharp fatigue-precracked starter cracks are employed. Intralaminar R-curves exhibited significantly steeper propagation, rising to approximately 0.385 kJ/m² at Δa = 30 mm due to extensive fiber bridging, whereas interlaminar R-curves reached a near-plateau after 12–15 mm. Bootstrap 95% confidence bands quantified the higher uncertainty associated with the intralaminar R-curve. Teflon-insert data produced artificially high initiation values and unstable growth, confirming that only fatigue-precracked results are suitable for design allowables. This study demonstrates that a single, statistically robust initiation toughness (B-basis = 0.1715 kJ/m²) can be used interchangeably for intra- and interlaminar cracking in progressive-damage models and preliminary design analysis of IM7/8552 structures. The open-source statistical workflow (KDE + bootstrap) developed here is transferable to other small-sample composite datasets, though the numerical B-basis value (0.1715 kJ/m²) is specific to IM7/8552 and should not be generalized without validation. Full article

The modeling accuracy of rice straw remains limited, and discrete element method (DEM) simulations of its compression are computationally intensive. To address these challenges, this study systematically investigated the physical characteristics of rice straw and proposed an innovative DEM and parameter calibration approach. Uniaxial compression tests were conducted on individual straw stalks, and key DEM parameters were systematically calibrated using Plackett–Burman experiments, steepest ascent trials, and Central Composite design. The calibrated parameters were validated against single-straw compression tests, showing a relative error of only 1.9% between simulated and measured peak loads, indicating high model fidelity. Building on this foundation, vibration-assisted compression bench tests were performed on bulk straw, further validating the scaled-up DEM and its parameters. The evolution of normal forces and porosity during compression was analyzed by comparing experimental results with simulations, confirming the model’s accuracy in capturing straw compaction behavior. Finally, a comparison of computational efficiency between the scaled-up and original DEMs revealed that the scaled-up model reduced computation time by approximately 67.4% and 65.2%, respectively, significantly improving simulation efficiency. This study provides a robust methodology for modeling flexible agricultural fibers and establishes a foundation for efficient numerical simulation of straw compression. Full article

Saskatoon berry (SB), a traditional food of Indigenous people, has been associated with cardiometabolic benefits in animal models; however, its effects on humans remain unclear. This study investigated the effects of dried SB consumption on cardiometabolic outcomes, gut microbiota, and short-chain fatty acids (SCFAs) profiles in healthy adults. In a 10-week, single-arm, and open-label trial, 20 healthy adults consumed 40 g/day of freeze-dried whole SB. Biochemical measures, physical exams, dietary records, participant feedback, and fecal samples were collected before and after the intervention. Gut microbiota composition and fecal SCFAs were profiled using 16S-rRNA sequencing and gas chromatography–mass spectrometry, respectively. SB intake significantly reduced fasting plasma glucose, total cholesterol (TC), low-density lipoprotein-cholesterol (LDL-c), non-high-density lipoprotein-cholesterol (non-HDL-c), systolic blood pressure, and high-sensitivity C-reactive protein, while increasing dietary fiber intake. Fiber intake was negatively correlated with TC, LDL-c and non-HDL-c (p < 0.05). The relative abundance of fecal Prevotellaceae increased after SB consumption and was positively correlated with multiple fecal SCFAs (p < 0.05–0.0001), while being negatively associated with lipid profiles and blood pressure. No adverse cardiovascular, hepatic, or renal dysfunction were observed; however, the significant increase in sugar intake may pose a risk for elevated blood glucose. Therefore, limiting other high-sugar foods during SB supplementation may be advisable for individuals with glucose intolerance. Overall, SB intake improved glucose and lipid metabolism and lowered blood pressure and inflammatory markers in healthy adults. These cardiometabolic benefits may be mediated by fiber and anthocyanins in SB and through modulation of gut microbiota and SCFA production; however, further confirmation is needed in subsequent randomized controlled trials. Full article