Search Results (173)

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 widespread release of microplastics (MPs), especially fibrous microplastics (FMPs) originating from synthetic textiles, poses a growing threat to environmental systems due to their persistence, mobility, and potential for bioaccumulation in aquatic and terrestrial ecosystems. Conventional gravimetric methods (GMs) remain the primary approach for assessing FMP shedding, yet they are hindered by moisture-sensitive filters, false positives from detergents and minerals, environmental contamination, and the labor-intensive manual measurement of individual fibers. To address these limitations, we developed an automated image analysis (AIA) framework that integrates an attention-based U-Net architecture with meta-learning modules to quantify FMP number, length, diameter, and mass from stitched microscopic images of entire filter membranes. This approach enables detection of fibers down to 28 μm in diameter with the spatial resolution of 2.17 µm/pixel, supports both target-color and multi-color analysis, and eliminates the need for manual characterization or extrapolation from partial membrane segments. The method achieved the highest accuracy of approximately 98% in color-specific fiber detection, correctly identifying 257 of 263 white fibers, and demonstrated similarly robust performance for black, red, and green fibers, while minimizing interference from non-target colors, even when their fibers overlapped. Multi-color detection was further validated using effluent water samples containing mixed-color fibers. Overall, the developed system enhances the accuracy, efficiency, and reproducibility of FMP analysis, offering a standardized and scalable approach for environmental monitoring of MP pollution. Full article

Composite laminates experience static and fatigue delamination, presenting significant challenges for failure prediction. This is critical in curved composites, where delamination behavior is complex to predict. In this study, fatigue tests were conducted on curved composite laminates under non-constant mixed-mode conditions. The testing setup involved a four-point bending test using L-shaped, unidirectional carbon-fiber-reinforced polymer curved beam specimens. A Teflon insert placed at the bend was used to initiate delamination. Experimental data acquisition included digital image correlation (DIC) to monitor delamination length during testing. This is important since it enhances subsequent model correlation. A virtual crack closure technique (VCCT)-based method for simulating fatigue-driven delamination under variable mixed-mode conditions was validated against experiments. Delamination growth was modeled using a Paris-like power–law relationship based on the strain energy release rate. The approach was implemented in Abaqus as a user subroutine, incorporating load ratio and mode mixity effects through VCCT-based mode separation. This study demonstrates accurate fatigue delamination prediction and highlights the role of optical measurements in experiments. The model improves our understanding of delamination propagation under varying mode mixity and contributes to structural integrity analysis. The results show how mode mixity influences delamination, impacting the performance and lifecycle of composite structures. Full article

The environmental urgency of reducing Portland cement consumption has driven research into geopolymer concrete (GPC) as a sustainable alternative. However, its inherent brittleness limits structural applications. This study addresses this critical challenge by investigating the efficacy of steel fibers (SF) and polypropylene fibers (PP) in enhancing the mechanical properties of slag-based GPC. Thirteen mixtures, including a control, were designed with varying fiber types, lengths (35/60 mm for SF, 40/60 mm for PP) and dosages (25–75 kg/m³ for SF, 3–9 kg/m³ for PP). Comprehensive tests evaluated workability, flexural/compressive strength, and toughness. Results demonstrated that while both fibers reduced workability (PP > SF), they significantly improved ductility, with SFs increasing toughness by 6–15 times. A key finding was the time-dependent performance: SF enhanced early-age flexural strength by up to 38%, though this benefit declined at 28 days for most mixes under ambient curing. PP fibers reduced flexural strength by 25–40% at 28 days. Compressively, SF increased strength by up to 60%, while PP led to reductions up to 27%. The study conclusively establishes SF’s superiority due to its superior bonding and crack-bridging capabilities, providing essential insights for designing durable fiber-reinforced GPC. This research directly contributes to advancing sustainable construction materials by overcoming a fundamental limitation of geopolymers. Full article

Fiber-optic shape sensing enables real-time monitoring of structural deformation across a wide range of applications. For large-scale structures, Brillouin-based distributed sensing, typically implemented through Brillouin Optical Time Domain Analysis (BOTDA), offers an extended range for quasi-static measurements, albeit its limited spatial resolution degrades reconstruction accuracy. This study addresses this fundamental limitation through the introduction of a novel error compensation algorithm, particularly suited for a Brillouin-based shape sensing system, yet agnostic with respect to the sensing technology. The method leverages both the initial and final points of the sensing path, performing both forward and backward reconstructions and fusing the two trajectories by testing several polynomial and exponential weighting strategies. The algorithm is experimentally validated on a 28.91 m four-core shape sensing fiber cable (length = L), interrogated through BOTDA operating at 50 cm spatial resolution, and reconstructed through the Frenet–Serret frame formulation. Calibration procedures include radial-offset tuning and segment alignment via a hotspot reference. A non-trivial S-shaped geometry is adopted as a case study, specifically addressing curvature discontinuities arising from mixed straight and curved segments. Reconstruction accuracy is quantified through a Euclidean-distance-based Figure of Merit (FOMs). The cubic weighting strategy demonstrates improvements exceeding 86% in all FOMs compared to classical methods without compensation. Specifically, it achieves an RMSE of 0.145 m (0.50% of L), a MAE of 0.109 m (0.38% of L), and a maximum error of 0.341 m (1.18% of L). Remarkably, these percentage errors are of the same order of magnitude as those reported in the literature for Fiber Bragg Grating (FBG) and Optical Frequency Domain Reflectometry (OFDR) systems, indicating that the proposed compensation strategy enables BOTDA-based shape sensing to achieve comparable reconstruction accuracy despite its lower spatial resolution. Full article

This study investigated the enhancement mechanisms and optimal mix proportion of basalt fiber (BF) in concrete for ship lock galleries. It focused on improving crack resistance, freeze–thaw resistance, impermeability, and abrasion–erosion resistance under complex hydraulic environments. Single-factor tests first determined the reasonable parameter ranges, which were subsequently used in a three-factor, four-level orthogonal experiment to analyze the effects of the water-to-binder ratio, fiber content, and fiber length on concrete’s mechanical properties. Range analysis of the orthogonal experiment indicated that the water-to-binder ratio was the most dominant factor (R = 57.4), followed by fiber content. Based on this, further durability tests were conducted, including ring restraint cracking, impermeability, freeze–thaw resistance, and abrasion–erosion resistance. Multi-objective optimization was performed using full factorial experiments and a comprehensive performance evaluation system. The final optimal mix proportion was determined as: a water-to-binder ratio of 0.35, a fiber content of 0.2%, and a fiber length of 12 mm. With this mix, the concrete’s ring cracking time was extended by 69.9%, the relative dynamic elastic modulus retention reached 73.0% after 100 freeze–thaw cycles, the relative permeability coefficient was 1.04 × 10⁻⁶ cm/h, and the abrasion–erosion resistance strength increased to 7.05 h·m²/kg, which achieved an optimal synergy among the mechanical properties, key durability indicators, and their workability. Mechanism analysis revealed that BF formed a three-dimensional, randomly distributed fiber network that comprehensively enhanced concrete performance through multi-scale mechanisms, including bridging, pore refinement, and energy dissipation. This research has provided systematic experimental evidence and mix proportion support for the durability design and engineering application of BF concrete in ship lock galleries. Full article

Basalt fiber-reinforced concrete (BFRC) exhibits superior mechanical performance, durability, and environmental benefits, making it a promising material for promoting green and low-carbon construction. This study develops a novel multi-objective mix design optimization method for BFRC under cost and carbon emission constraints, presents a framework that considers tensile strength (f_t) as a core design objective, and establishes high-precision strength prediction models via gene expression programming (GEP). Material cost and carbon emission functions were formulated based on market data, while compressive strength (f_c) and tensile strength (f_t) prediction models were established using using GEP implemented in MATLAB 2018b with seven mix design variables, including cement dosage, aggregate parameters, and basalt fiber (BF) characteristics (diameter, length, and dosage). Multiple constraints covering material quantities, mix ratios, workability, and density were incorporated into the optimization model, which was solved via the non-dominated sorting genetic algorithm II (NSGA-II). The method identifies the optimal cement dosage, aggregate proportions, and BF dosage to maximize tensile strength (f_t) while minimizing cost and carbon emissions. Computational results suggest that within the target strength range of 30–60 MPa, the proposed design yields reductions of 10–20% in carbon emissions and 12–18% in costs compared to conventional methods, offering potential advantages for sustainable construction. Unlike existing multi-objective studies, which focus on compressive strength, this work addresses critical factors of tensile strength (f_t) and prediction inaccuracy, proposing a systematic low-carbon design framework for potential BFRC applications. Full article

This study evaluates the multi-physical effects of fiber type, length, and dosage on the fresh properties, mechanical performance, and environmental impact of roller-compacted concrete (RCC). Industrial steel (S), polypropylene (PP), and waste steel (WS) fibers with lengths of 30 mm and 60 mm were incorporated into RCC mixtures at volume fractions ranging from 0% to 1.25%. The experimental program included Vebe consistency tests, mechanical strength assessments, and fracture energy measurements, complemented by a simplified cradle-to-gate Global Warming Potential (GWP) analysis. Furthermore, Taguchi and ANOVA methods were employed to statistically determine the hierarchy of influential parameters. The statistical analysis revealed that fiber dosage was the most dominant factor, contributing approximately 68–78% to the variation in compressive, splitting tensile, and flexural strengths, whereas fiber type governed the consistency. Experimentally, S and WS fibers significantly enhanced the post-cracking behavior and fracture energy compared to the brittle control mix, although they imposed a greater penalty on workability than PP fibers. Notably, at comparable dosages, WS fibers exhibited mechanical interlock and toughness performance nearly identical to industrial steel fibers. The environmental analysis demonstrated that replacing industrial steel fibers with WS fibers reduces the embodied carbon by approximately 240 kgCO₂-eq/m³ at the maximum dosage, without compromising mechanical reliability. These findings suggest that waste steel fibers offer a superior performance-to-carbon ratio, making them a viable sustainable alternative for heavy-duty RCC pavements where crack control is prioritized. Full article

Polyvinyl alcohol (PVA) fibers are commonly added to fiber-reinforced geopolymer composites (FRGC) to enhance their properties; however, systematic research on the dynamic mechanical properties of polyvinyl alcohol fiber-reinforced geopolymer composites (PVA-FRGC) is still required. In this study, an orthogonal experimental design was adopted to investigate the effects of the fly ash/slag ratio, fiber length, and fiber volume content on the dynamic mechanical properties (dynamic compressive strength, fragmentation degree, and energy absorption capacity) of PVA-FRGC. A split Hopkinson pressure bar (SHPB) was used to test the dynamic mechanical properties of the material. The results indicate that the fly ash/slag ratio, fiber length, and fiber volume content all exert significant effects on the dynamic compressive strength and energy absorption capacity of PVA-FRGC. The addition of PVA fibers significantly improves the dynamic compressive strength of PVA-FRGC, which reaches 157.52 MPa, 183.26 MPa, and 210.68 MPa under three different strain rates ranging from 75.4 s⁻¹ to 179.6 s⁻¹, respectively. Although the energy absorption capacity of PVA-FRGC is not significantly improved, the integrity of the specimens after fragmentation is remarkably enhanced. Specifically, under the three load levels, the average particle sizes of PVA-FRGC are 241.43%, 245.04%, and 127.80% higher than those of plain geopolymers, respectively. Considering the comprehensive dynamic mechanical properties, a fly ash/slag ratio of 5:5, a fiber length of 9 mm, and fiber volume content of 2.0% can be regarded as the local optimal mix proportion. Full article

Background/Objectives: The aim of this study was to investigate the longitudinal visual field (VF) and circumpapillary retinal nerve fiber layer thickness (cpRNFLT) changes in open-angle glaucomatous (OAG) participants with unilateral peripapillary intrachoroidal cavitation (PICC) and to identify factors associated with VF progression. Methods: Sixty eyes of 30 OAG patients with unilateral PICC were included in this retrospective longitudinal observational study. Humphrey 24–2 VF testing and optical coherence tomography scanning were performed in all eyes over a period exceeding 5 years. VF progression was assessed using mean deviation (MD) and superior and inferior total deviation (TD) slopes. Structural progression was evaluated using global, superior, and inferior cpRNFLT thinning rates. Longitudinal changes were compared between PICC eyes and their contralateral non-PICC eyes. Factors associated with superior or inferior TD slopes were analyzed using linear mixed-effects models. The following variables were included as explanatory variables: age, sex, intraocular pressure, axial length, Bruch’s membrane opening (BMO) and scleral flange opening (SFO) area, SFO/BMO offset magnitude, disk tilt, disk rotation, baseline superior or inferior TD, baseline corresponding cpRNFLT, and the presence of PICC. Results: MD slope was −0.24 ± 0.35 dB/year in PICC eyes and −0.35 ± 0.53 dB/year in contralateral eyes. There was no significant difference in MD slope, superior and inferior TD slope, or the rate of cpRNFLT thinning (all p > 0.05). In multivariable analysis, the presence of PICC was associated with slower progression in the corresponding superior VF (p = 0.037), whereas greater SFO/BMO offset magnitude was associated with faster progression (p = 0.047). Conclusions: OAG eyes with PICC exhibited modest functional and structural progression over 5 years, comparable to that of contralateral non-PICC eyes. The presence of PICC was associated with slower corresponding superior VF progression, whereas greater myopia-associated structural change was related to faster progression. Our findings characterize the clinical course of eyes with pronounced myopic ONH deformation, highlighting the importance of detailed ONH structural assessment in the management of myopic glaucoma. Full article

Natural fibers have attracted increasing attention as eco-friendly and sustainable additives for improving the durability and mechanical performance of asphalt mixes. This paper presents a critical state-of-the-art review of the use of six kinds of natural fibers in asphalt mixes. This paper reviews the impact of six natural fibers such as lignin fiber, bamboo fiber, bagasse fiber, corn stalk fiber, basalt fiber, and wool fiber on the properties of bitumen binders and mixes. It examines the influence of these fibers on the physical properties, rheological properties, and fatigue performance of bitumen binders. In addition, the influence of fibers on the moisture stability, anti-cracking, and high- and low-temperature performance of asphalt concrete was analyzed. The review demonstrated that the recommended lengths of natural fibers in asphalt mixes are as follows: lignin fiber 0.8–1.2 mm, bamboo fiber 4–20 mm, sugarcane bagasse fiber 5–12 mm, corn stalk fiber 3 mm, and basalt fiber 6–30 mm. Adding lignin fiber and corn stalk fiber enhanced the high-temperature characteristic of bitumen. The high- and low-temperature properties of the binder were improved by adding bamboo fiber. The addition of basalt fiber and bamboo fiber can increase rutting resistance and fatigue life. Additionally, incorporating the bamboo fiber, bagasse fiber, basalt fiber and wool fiber improved the low-temperature cracking and fatigue resistance of the bitumen mixture. The high-temperature properties of the bitumen mixes were enhanced by using basalt fibers, lignin fibers, bamboo fibers and bagasse fibers. The moisture resistance of bitumen mixes were reinforced by the incorporation of basalt fibers, lignin fibers and bamboo fibers. In general, incorporating natural fibers provided a technical method for improving the performance of asphalt concrete in road applications. Full article

Accurate prediction of the mechanical performance of fiber-reinforced cement mortars (FRCM) is challenging because fiber geometry and properties vary widely and interact with the cement matrix in a non-trivial way. In this study, we propose an interpretable, computationally light framework that combines principal component analysis (PCA) with multiple linear regression (MLR) to predict compressive strength (Cs) and flexural strength (Fs) from mix proportions and fiber parameters. The literature-based dataset of 52 mortar mixes reinforced with polypropylene, steel, coconut, date palm, and hemp fibers was compiled and analyzed, covering Cs = 4.4–78.6 MPa and Fs = 0.75–16.7 MPa, with fiber volume fraction V_f = 0–15% and fiber length F_l = 4.48–60 mm. PCA performed on the full dataset showed that PC1–PC2 explain 53.4% of the total variance; a targeted variable-selection strategy increased the captured variance to 73.0% for the subset used for regression model development. MLR models built using PC1 and PC2 achieved good accuracy in the low-to-mid strength range, while prediction errors increased for higher-strength mixes (approximately Cs ≳ 60 MPa and Fs ≳ 10 MPa). On an independent validation dataset (n = 10), the refined model achieved mean absolute percentage errors of 11.3% for Fs and 18.5% for Cs. The proposed PCA-MLR approach provides a transparent alternative to more complex data-driven predictors, and it can support preliminary screening and optimization of fiber-reinforced mortar designs for durable structural and repair applications. Full article

Global vegetable production exceeded 1.2 billion tons in 2022, with bell pepper (Capsicum annuum) accounting for 37 million tons, a crop of high value due to its versatility, commercial demand, and nutritional properties. In the Dominican Republic, greenhouse vegetable production has experienced accelerated growth over the last 23 years, reaching over 10 million m² of infrastructure and increasing pepper production from 9122 to 32,000 tons. However, limitations in technical information regarding nutritional management and substrate use persist, despite the extensive empirical experience of producers and technicians. This study evaluated the effect of three fertigation programs (low, medium, and high doses: FP1, FP2, and FP3) and three substrates (carbonized rice husk- CRH, coconut fiber-CF, and a 1:1 Mix) on 180 plants grown for 141 days in a greenhouse, using a completely randomized split-plot design. Growth, physiological, quality, and yield indicators were measured. Principal Component Analysis (PCA) explained 88% of the variability, showing that FP2 and FP3, combined with BRH and the 1:1 Mix, generated greater plant height, stem diameter, chlorophyll content, and canopy development, while FP1 and CF were associated with lower performance. Regarding fruit quality, the BRH and 1:1 Mix substrates yielded higher values for length, width, and weight, whereas °Brix content responded primarily to fertigation doses. Total yield confirmed this pattern, highlighting FP3–BRH as the best combination evaluated and FP1–CF as the one with the lowest productivity. Full article

To overcome the limitations of existing automatic modulation classification (AMC) methods that mainly target single-signal scenarios in radio-over-fiber (RoF) system, a mixed-signal AMC scheme based on phase noise-insensitive high-order cumulants (PNI-HOC) and distribution characteristics is proposed. The approach enables accurate classification of mixed signals in RoF system. Specifically, a PNI-HOC algorithm is first introduced to mitigate the influence of laser linewidth-induced phase noise. Then, distribution characteristics derived from the signal amplitude histogram are extracted to construct a two-dimensional characteristics space. These characteristics are subsequently fed into decision tree and support vector machine (SVM) classifiers for signal identification. To validate the effectiveness of the scheme, a 10 GBaud RoF system with a 70 km fiber link is implemented. The simulation results show that, compared with the conventional high-order cumulant method, the approach solely based on amplitude histogram distribution characteristics and the scheme based on deep neural networks (DNN) classifier using histogram characteristics, the proposed scheme achieves significantly higher classification accuracy at low optical signal–noise ratios (OSNRs). In particular, when the fiber length is 70 km and the OSNR is ≥16 dB, the classification accuracy of mixed signals is consistently maintained at 100%. Furthermore, the robustness of the proposed method is verified under various system impairments, including laser phase noise, chromatic dispersion and nonlinear effects, amplified spontaneous emission noise, multipath fading, etc., confirming its superior and stable performance. Full article

In this study, the aim was to improve the mechanical and durability properties of kaolin clay (KC)-based soil by stabilizing it with geopolymer and natural fiber. In the production of the geopolymer, rice husk ash (RHA) was used as a binder, sodium metasilicate (SMS) as an activator, and another hemp fiber (HF)was used for soil stabilization. Within the scope of the presented study, RHA and SMS were used at three different rates (5%, 7.5%, and 10%), while HF was used in six different volumes (0.5%, 1%, 1.5%, 2%, 2.5%, and 3%) and two different lengths (6 and 12 mm). The study also examined how much water was in the combinations, which was measured at the optimum level and at −5, +5, and +10 compared to the optimum level. The unconfined compressive strength (UCS) was used to check the mechanical qualities of the test specimens and 5- and 10-cycle freeze–thaw (F-T) tests to check the durability properties. The test results indicated that the mixed formulation with 5% RHA, 10% SMS, 2.5% HF, and the optimum water content resulted in the best results for both the UCS and F-T tests. The SEM investigation for this mix found that the microstructural properties for the specimen were directly related to the dense gel phases and the strong fiber–matrix bonding. According to the carbon emissions (CO₂-e) and carbon index (CI) analysis from the mix component analyses, it was found that the HF-strengthened geopolymer is a sustainable solution for soil stabilization. The optimum mixture achieved a UCS of 1202 kPa (4.5 times higher than untreated soil), while the strength losses after 10 freeze–thaw cycles were reduced to below 10% in optimized compositions. The carbon index (CI) decreased by up to 65%, demonstrating the strong sustainability benefits of the proposed system. The novelty of this study lies in the combined use of hemp fiber (HF) and rice husk ash (RHA)–sodium metasilicate (SMS)-based geopolymer for kaolin clay stabilization, which has not been comprehensively investigated in previous research. Unlike traditional studies focusing on either geopolymer or natural fiber reinforcement alone, this work simultaneously evaluates the mechanical performance, freeze–thaw durability, microstructural evolution, and carbon footprint to develop a fully sustainable soil improvement framework. Full article