Hemp fibers as polymer matrix composites offer sustainability, cost-effectiveness, adaptability, and exceptional mechanical characteristics in materials science and engineering. This study examines hemp fiber-reinforced thermoset matrix composites, integrating walnut shell powder as filler and epoxy resin as matrix, assessing creep, fatigue, wear, and dielectric characteristics according to ASTM standards. The investigation varies the hemp fiber and epoxy resin ratios while keeping the walnut shell content constant. Four laminates (L1, L2, L3, L4) with unique mixtures of hemp fiber, resin, and walnut shell filler were specifically designed. L1 comprises 30% hemp fiber and 70% resin, without walnut filler. L2, L3, and L4 have progressively higher hemp fiber content, 10% walnut filler and varying the resin concentration appropriately. The amount of Epoxy resin in L1, L2, L3 and L4 are 70, 80, 70 and 60%, respectively. The results indicated that composites with walnut shell filler exhibit better dynamic characteristics than composites without it. Creep testing revealed reductions of 85.05%, 87.73%, and 91.41% for L2, L3, and L4 compared to L1. Fatigue life for L2, L3, and L4 increased by 17.98%, 12.97%, and 10.2%, and dielectric constant values rose by 17.02%, 34.04%, and 57.45%, respectively. Wear loss decreased by 12.49%, 13.51%, and 4.39%, while the coefficient of friction increased by 27.14%, 20%, and 8.57% for L2, L3, and L4 compared to L1. • Mix of 10% walnut shell powder filler, 30% hemp fiber, 60% epoxy resin is advised. • The more the proportion of hemp, the higher its creep and fatigue strength. • Mix with walnut shell filler has better dynamic performance than those without it. • Mix of 30% hemp fiber and 70% epoxy resin yields less dielectric value.
The rapid digitization of the real estate and architectural design industries has created a high demand for automated tools capable of parsing 2D raster floor plans. Traditional manual measurement and visual inspection are not only time-consuming but also highly susceptible to human error. In this paper, we propose a comprehensive, end-to-end deep learning framework designed to automatically extract rich semantic information from unstructured 2D floor plan images and provide professional design guidance via Large Language Models (LLMs). Our integrated pipeline employs the state-of-the-art YOLOv8 object detection model to accurately localize and classify 18 distinct architectural symbols and furniture items (e.g., doors, windows, beds, cupboards). Simultaneously, a U-Net architecture with a ResNet34 encoder is utilized for the precise semantic segmentation of structural elements, specifically walls and interior room spaces. To translate pixel-level predictions into actionable real-world metrics, we introduce a robust area calculation algorithm based on user-defined reference scale calibration. Furthermore, to bridge the gap between raw geometric data and actionable architectural intelligence, we introduce an LLM-driven evaluation module utilizing a local Ollama deployment and a Retrieval-Augmented Generation (RAG) pipeline to assess design compliance and quality. To overcome the scarcity of annotated architectural datasets, we implement a systematic data augmentation strategy, expanding a core dataset of 101 manually annotated floor plans to 303 varied instances, thereby significantly enhancing model generalization. Experimental results indicate that our YOLOv8-based detection module achieves a mean Average Precision (mAP50) of 92.3%, while the U-Net segmentation module achieves a mean Intersection over Union (mIoU) of 95.71%. Furthermore, the integrated system is deployed as a user-friendly, interactive web application, acting as an intelligent architectural assistant and demonstrating its practical viability and high efficiency for real-world engineering and architectural applications.
We are developing and operating the laser hammering system (LHS) that is non-destructive remote sensing device for concrete infrastructures. LHS can digitize the hammering test which is current mainstream of the inspection of concrete by using an impact laser (short-pulse laser), laser Doppler vibrometer, scanning system and camera. In this study, long-range LHS (applicable distance of 30 m) and small LHS (160 kg weight, for use on aerial work platforms) are developed for the bridge inspection. Long-range system succeeded on measurement of the concrete specimens of class 2 and 3 defect which were identified by active inspectors, and real defect of class 2 on bridge on use at the distance of 30 m. Small LHS succeeded on generation the surface vibration of the concrete specimens of class 2 and 3 defect which were identified by active inspectors. It indicates Long-range LHS and small LHS satisfied the inspection requirement as the support tool of hammering test prescribed by Japanese government. These devices are available for support to inspectors and digitalization of concrete sound status to achieve smart infra-maintenance.
Read moreBiochar, a byproduct from the biofuels industry, may be a potential feed additive in ruminant diets due to possible improvements in microbial fermentation. Therefore, the objective of this study was to determine the nutritive value, in vitro digestibility, volatile fatty acid (VFA) production, and gas production of biochar inclusion to an orchard grass (Dactylis glomerata) basal diet. The study was designed as a 3 × 2 factorial arrangement with 3 different biochar sources and 2 biochar processed sizes as the main effects factors. Experimental treatments were biochar from 3 different tree types: 1) Chestnut Oak (Quercus prinus L.; CO), 2) Yellow Poplar (Liriodendron tulipifera; YP), or 3) White Pine (Pinus strobus L.; WP), and processed at 2 different biochar particle sizes: a) μm (Fine) or b) >178 μm (Coarse). Biochar was added to the basal diet of orchard grass hay (872.35 g/kg of DM, 98.31 g/kg of CP, and 704.02 g/kg of aNDF, DM basis) at a rate of 81 g/kg DM. Biochar residual ash content was greater (P < 0.01) for Fine particle size and greater (P < 0.01) for CO and YP biochar sources. Biochar aNDF content exhibited a type × size interaction (P = 0.01) with lower aNDF content in both WP sizes compared with their respective biochar type and size. Gas production was not influenced (P = 0.23) by biochar tree type; however, gas production was increased (P = 0.05) by Fine particle size compared with Coarse biochar. The in vitro true digestibility (IVTD) of orchard grass hay was increased (P = 0.01) by the inclusion of Fine biochar particle size compared with Coarse particle size. Additionally, in vitro CP true digestibility (DCP) exhibited a type × size interaction (P = 0.01). Crude protein digestibility was lower for Fine particle-sized CO and WP biochar sources compared with Coarse particle-sized CO and WP (P ≤ 0.004). However, DCP was not different between Coarse and Fine particlesized YP biochar (P = 0.70). Volatile fatty acids (acetate, propionate, and butyrate) were not altered by biochar type (P ≥ 0.66) or particle size (P≥ 0.19). These results indicate that both tree type and particle size of biochar may need to be carefully considered before incorporating into a ruminant diet. Furthermore, Fine particle-sized biochar may be the most effective to incorporate as a feed additive in a ruminant diet based on digestibility parameters.
Read moreThis study conducted a 1:3 scale model test to investigate the improvement mechanism of damaged steel–concrete transition segments strengthened by UHPC. Meanwhile, a void region was introduced at the bottom of the transition segment to simulate the grouting defect in practical engineering. Then, static and fatigue tests on these transition segments were carried out on different parameters, including non-strengthening, UHPC strengthening and UHPC strengthening combined with void repair. Digital image correlation (DIC) was employed to characterize the global strain field of the transition segment. The experimental results show that UHPC strengthening reduced the relative displacement by 0.06 mm (46.2%), while UHPC strengthening combined with void repair achieved a reduction of 0.13 mm (96%). The average strain at critical points of the transition segment decreased by 76.2% after UHPC strengthening, while a greater reduction of 86.5% was achieved when UHPC strengthening was combined with void repair. In addition, crack propagation was effectively inhibited following UHPC strengthening. The refined finite element analysis results indicated that the predicted damage state at 1.0 P was in good agreement with the experimental observations, and under the 1.3 P overload condition, the difference between calculated and measured loads at the same displacement level was only 2.5%, and most of the stresses remained below the tensile and compressive strengths of UHPC. Finally, the proposed predictive method for the circumferential tensile stress of the transition segment exhibited a prediction error of 5%, indicating satisfactory accuracy.
Read moreABSTRACT This study proposes a new seismic design procedure for mid‐story isolated structures that reduces design complexity, computational effort, and time. In the proposed procedure, referred to as the coupling coefficients (CCs) method, the isolated superstructure and the substructure are initially treated as decoupled and analyzed separately. CCs are then used to capture the interaction effects among seismic isolation, substructure, and superstructure. We first derived the CCs in closed form using basic concepts of modal analysis. Then, we validate these analytical expressions using statistical results obtained through comprehensive numerical simulations. We described the dynamic problem using mass and stiffness ratios. For stiffness ratios () limited to , and stiffness‐to‐mass ratios ( t ) limited to , simplified expressions for modal periods, masses, participation factors, and damping ratios are developed. A reduced damping in the first mode captures the amplification effects of the substructure on the isolated superstructure. An increased damping in the second mode captures the tuned mass damper effects of the isolated superstructure on the substructure. For small stiffness ratios, the seismic demand of the isolation system can be approximated by that of the independent isolated superstructure on the ground, and the demand of the substructure can be approximated by that of the independent substructure, with adjustments made only for the viscous damping effects.
Read moreSpecimens with binary (SL, FA) and ternary (T1, T2) concrete mixes (30.5 cm x 12.7 cm x 7.6 cm) were prepared without any chlorides, using a w/cm ratio of 0.41 or lower. Each specimen, reinforced with #3 rebar, have a 0.75 cm concrete cover. The specimens had reservoirs of varying lengths on their top surface. A 10% NaCl solution by weight was introduced into the reservoirs, and electromigration was applied for a period ranging from few weeks to several months to accelerate chloride transport. Corrosion current values were monitored for approximately 1600 days using galvanostatic pulse techniques and converted to mass loss using Faraday’s law. The SL mix specimens showed the highest average corrosion current values, followed by FA, T1, and T2 mix specimens. Despite the prolonged exposure, no visible corrosion such as cracks or surface-reaching corrosion products were observed over the monitoring period.
Read moreSpeech perception relies on multiple acoustic cues whose relative weighting varies across languages. The present study examines how long-term language experience shapes cue weighting in second-language (L2) speech perception, refining an attentional-learning account of cross-linguistic transfer. Native speakers of English, Dutch, Spanish, Korean, and Mandarin completed a cue-weighting task targeting English lexical stress, in which vowel quality, pitch, and duration were orthogonally manipulated. Results revealed robust, dimension-specific differences across first-language (L1) groups that could not be explained solely by the presence or absence of lexical stress or lexical tone in the L1. Instead, cue weighting reflected how acoustic dimensions function within the L1 cue ecology, including their relative contribution to lexical distinctions and the stability and interpretability of these mappings across contexts. Cue redundancy constrained relative cue strength without eliminating attentional sensitivity to secondary dimensions. Machine-learning classification further showed that L1-linked attentional profiles were sufficiently structured to support prediction, even among L2 listeners with substantial English proficiency, demonstrating the persistence of L1-shaped attentional tuning. These findings support a view of cue weighting as reflecting durable, multidimensional attentional priors shaped by long-term experience and highlight the importance of L1 cue ecologies in understanding cross-linguistic transfer in speech perception.
Read moreThe scarcity of high-quality granular materials has led to exploring alternatives like fly ash (FA), an industrial byproduct of coal-fired power plants. Utilizing FA in pavement construction can reduce the reliance on crushed stone aggregates, conserving energy and protecting the environment. However, its use in structural layers (base and subbase) is limited due to fine particles that make it brittle when stabilized. To address this, stone dust (SD) and aggregates (AG) were mixed with FA (noted FA-SA) before cement stabilization to improve gradation and strength. Polypropylene fiber (FI) was added to enhance reinforcement and reduce brittleness. Fatigue failure, caused by repeated loading, is the primary mode of failure in stabilized layers, making the development of a fatigue performance model critical for Mechanistic-Empirical pavement design. This study investigated the fatigue performance of cement-stabilized FA-SA mixtures using cyclic indirect tensile tests. Experimental evaluations, conducted with and without fiber reinforcement, included indirect tensile strength, resilient modulus, and fatigue behavior using a servo-hydraulic testing machine. Results showed three stages of stiffness reduction, with a final modulus drop of 15%-30% compared to the initial modulus, indicating brittle behavior under stress-controlled conditions. A strain-based fatigue model was developed, with strain damage exponents for FA-SA composites stabilized with 4%-6% cement and 0.25%-0.35% fiber ranging from 4.37 to 4.55. These findings enhance the understanding of fatigue performance in FA-based stabilized layers, supporting the design of sustainable road infrastructure. • Three stages of stiffness reduction was identified for fiber-reinforced cement-stabilized fly ash aggregate mixture. • Stiffness modulus reduced to 15%-30% compared to the initial modulus, indicating brittle behavior under stress-controlled conditions. • Strain-based fatigue models were developed.
Read more