Search Results (1,961)

Background: Accurate route planning is a core challenge in logistics, particularly for small- and medium-sized enterprises that lack access to costly geospatial tools. This study explores whether usable distance matrices and routing outputs can be generated solely from geographic coordinates without relying on full map-based infrastructure. Methods: A dataset of over 5000 Hungarian postal locations was used to evaluate five models: Haversine-based scaling with circuity, linear regression, second- and third-degree polynomial regressions, and a trained artificial neural network. Models were tested on the full dataset, and three example routes representing short, medium, and long distances. Both statistical accuracy and route-level performance were assessed, including a practical optimization task. Results: Statistical models maintained internal consistency, but systematically overestimated longer distances. The ANN model provided significantly better accuracy across all scales and produced routes more consistent with map-based paths. A new evaluation method was introduced to directly compare routing outputs. Conclusions: Practical route planning can be achieved without GIS services. ML-based estimators offer a cost-effective alternative, with potential for further improvement using larger datasets, additional input features, and the integration of travel time prediction. This approach bridges the gap between simplified approximations and commercial routing systems. Full article

Laminated glass (LG) composite systems are increasingly being utilized in architectural and security applications due to their enhanced strength and safety features. Understanding the structural response of LG systems is crucial for optimizing their performance under blast loads. This paper presents a comprehensive study of an analytical model for predicting the static and dynamic resistance functions of various LG systems used in blast-resistant designs to advance engineering analysis and design methods. The proposed analytical model integrates the strain-rate-dependent interlayer behavior with the glass dynamic increase factors to generate a physically consistent post-fracture membrane resistance, offering a unified framework for deriving the static and dynamic resistance functions directly applicable to single-degree-of-freedom (SDOF) analyses across different LG layups. The developed models were validated statistically using full-scale water chamber results and dynamically against experimental blast field data and the results from shock tube testing. We validated the model’s accuracy for various LG layup configurations, including variations in the glass and interlayer sizes, types, and thicknesses. The established dynamic resistance model was developed by incorporating a strain-rate-dependent interlayer material model. The energy absorption of LG panels, influenced by factors like interlayer thickness and type, is critical for blast design, as it determines the panels’ ability to withstand and dissipate energy, thereby reducing the transmitted forces and deformations to a building’s structure. The dynamic model closely matched the dynamic deflection time histories, with a maximum difference of 6% for all the blast experiments. The static resistance validations across the various LG configurations consistently demonstrated reliable prediction results. The energy absorption comparisons between the analytical and quasi-static LG panel responses ranged from 1% to 17%. These advancements provide higher-fidelity SDOF predictions and clear guidance for selecting the interlayer type and thickness to optimize energy absorption. This will result in enhanced blast resistance and contribute to more effective blast mitigation in glazing system design. Full article

This study investigates the influence of time (ageing) on the uplift capacity of bored piles in cohesionless silty sand through a full-scale field testing programme. Four reinforced concrete piles, two shorter (16 m) and two longer (21 m), were installed and tested under axial tension at two different ageing intervals: 35 days and 165 days post-construction. The load-displacement behaviour, load transfer characteristics, and shaft friction mobilisation were monitored using load cells and embedded strain gauges. Results showed that while all piles exhibited similar ultimate capacities, the aged piles consistently demonstrated stiffer responses and earlier mobilisation of shaft resistance. Extrapolated estimates showed modest increases in estimated ultimate uplift capacity, ranging from 2% to 7%, with ageing. Strain gauge data also indicated more uniform load transfer in the aged piles, suggesting time-dependent improvements in pile-soil interface behaviour. The findings confirm that even in cohesionless silty sand, moderate ageing effects can enhance uplift performance, but the extent of improvement is small and variable. These findings provide a valuable reference for evaluating uplift design assumptions and interpreting field test behaviour in similar soil environments. Full article

This study investigates the tribological behavior and wear mechanisms of Q235 steel components subjected to abrasive interaction with rice, a critical challenge in agricultural machinery performance and longevity. We employed a comprehensive multi-scale framework, integrating bench-top tribological testing, advanced Discrete Element Method (DEM) coupled with a wear model (DEM-Wear), and detailed surface characterization. Bench tests revealed a composite wear mechanism for the rice–steel tribo-pair, transitioning from mechanical polishing under mild conditions to significant soft abrasive micro-cutting driven by the silica particles inherent in rice during high-load, high-velocity interactions. This elucidated fundamental friction and wear phenomena at the micro-level. A novel, calibrated DEM-Wear model was developed and validated, accurately predicting macroscopic wear “hot spots” on full-scale combine harvester header platforms with excellent geometric similarity to real-world wear profiles. This provides a robust predictive tool for component lifespan and performance optimization. Furthermore, fractal analysis was successfully applied to quantitatively characterize worn surfaces, establishing fractal dimension (Ds) as a sensitive metric for wear severity, increasing from ~2.17 on unworn surfaces to ~2.3156 in severely worn regions, directly correlating with the dominant wear mechanisms. This study offers a valuable computational approach for understanding and mitigating wear in tribosystems involving complex particulate matter, contributing to improved machinery reliability and reduced operational costs. Full article

This study systematically investigates the influence of varying corrosion severity on the bearing capacity of K-shaped circular-section joints, with explicit consideration of weld line positioning. Four full-scale circular-section joint specimens with clearance gaps were designed to simulate localized corrosion through artificially introduced perforations, and axial static loading tests were performed to assess the degradation of structural performance. Experimental results indicate that the predominant failure mode of corroded K-joints manifests as brittle fracture in the weld-affected zone, attributable to the combined effects of material weakening and stress concentration. The enlargement of corrosion pit dimensions induces progressive deterioration in joint stiffness and ultimate bearing capacity, accompanied by increased displacement at failure. A refined finite element model was established using ABAQUS. The obtained load–displacement curve from the simulation was compared with the experimental data to verify the validity of the model. Subsequently, a parametric analysis was conducted to investigate the influence of multiple variables on the residual bearing capacity of the nodes. Numerical investigations indicate that the severity of corrosion exhibits a positive correlation with the reduction in bearing capacity, whereas web-chord members with smaller inclination angles demonstrate enhanced corrosion resistance, when θ is equal to 30 degrees, K_s decreases from approximately 0.983 to around 0.894. Thin-walled joints exhibit accelerated performance deterioration compared to thick-walled configurations under equivalent corrosion conditions. Furthermore, increased pipe diameter ratios exacerbate corrosion-induced reductions in structural efficiency, when the corrosion rate is 0.10, β = 0.4 corresponds to K_s = 0.98, and when β = 0.7, it is approximately 0.965. and distributed micro-pitting results in less severe capacity degradation than concentrated macro-pitting over the same corrosion areas. Full article

Background: Pelemir (Cephalaria syriaca) is a bitter-tasting ancestral legume with a high polyphenol content and emerging potential as a functional food ingredient. This study investigated the acute metabolic effects of pelemir-enriched bread in adults. Methods: In this two-phase non-randomized trial, 60 participants in three groups (n = 20 per group: healthy controls [HCs], individuals with obesity [OB], and individuals with type 2 diabetes [T2D]) consumed regular or pelemir-enriched bread on two separate test days. Postprandial glucose, insulin, C-peptide, GLP-1, PYY, ghrelin, leptin, triglyceride, and IL-6 were measured over 120 min. Subjective appetite ratings were evaluated using visual analog scales (VASs). The incremental area under the curve (iAUC) values were compared using Wilcoxon tests and linear mixed-effects models. Results: Pelemir-enriched bread significantly increased iAUCs for insulin (p = 0.014), C-peptide (p = 0.046), and GLP-1 (p = 0.039) compared to regular bread. There was no significant change in iAUC for glucose. Group-stratified analyses showed a higher postprandial iAUC of glucose, insulin, and C-peptide in the OB group compared to the HC group. VAS-based appetite ratings did not show significant changes in hunger, fullness, or desire to eat, but a borderline significant reduction was observed in prospective food consumption after pelemir-enriched bread (p = 0.050). Conclusions: Acute consumption of pelemir-enriched bread may modulate postprandial insulin and incretin responses. Its modest impact on subjective appetite regulation supports further investigation of pelemir as a functional food rich in polyphenols, especially in populations with metabolic dysfunction. Full article

Background: Colon capsule endoscopy (CCE) has seen increased adoption since the COVID-19 pandemic, offering a non-invasive alternative for lower gastrointestinal investigations. However, inadequate bowel preparation remains a key limitation, often leading to higher conversion rates to colonoscopy. Manual assessment of bowel cleanliness is inherently subjective and marked by high interobserver variability. Recent advances in artificial intelligence (AI) have enabled automated cleansing scores that not only standardise assessment and reduce variability but also align with the emerging semi-automated AI reading workflow, which highlights only clinically significant frames. As full video review becomes less routine, reliable, and consistent, cleansing evaluation is essential, positioning bowel preparation AI as a critical enabler of diagnostic accuracy and scalable CCE deployment. Objective: This CESCAIL sub-study aimed to (1) evaluate interobserver agreement in CCE bowel cleansing assessment using two established scoring systems, and (2) determine the impact of AI-assisted scoring, specifically a TransUNet-based segmentation model with a custom Patch Loss function, on both interobserver and intraobserver agreement compared to manual assessment. Methods: As part of the CESCAIL study, twenty-five CCE videos were randomly selected from 673 participants. Nine readers with varying CCE experience scored bowel cleanliness using the Leighton–Rex and CC-CLEAR scales. After a minimum 8-week washout, the same readers reassessed the videos using AI-assisted CC-CLEAR scores. Interobserver variability was evaluated using bootstrapped intraclass correlation coefficients (ICC) and Fleiss’ Kappa; intraobserver variability was assessed with weighted Cohen’s Kappa, paired t-tests, and Two One-Sided Tests (TOSTs). Results: Leighton–Rex showed poor to fair agreement (Fleiss = 0.14; ICC = 0.55), while CC-CLEAR demonstrated fair to excellent agreement (Fleiss = 0.27; ICC = 0.90). AI-assisted CC-CLEAR achieved only moderate agreement overall (Fleiss = 0.27; ICC = 0.69), with weaker performance among less experienced readers (Fleiss = 0.15; ICC = 0.56). Intraobserver agreement was excellent (ICC > 0.75) for experienced readers but variable in others (ICC 0.03–0.80). AI-assisted scores were significantly lower than manual reads by 1.46 points (p < 0.001), potentially increasing conversion to colonoscopy. Conclusions: AI-assisted scoring did not improve interobserver agreement and may even reduce consistency amongst less experienced readers. The maintained agreement observed in experienced readers highlights its current value in experienced hands only. Further refinement, including spatial analysis integration, is needed for robust overall AI implementation in CCE. Full article

Ultra-high-performance concrete (UHPC) exhibits significantly superior compressive and tensile properties compared to conventional concrete, demonstrating substantial application potential in bridge engineering. This study conducted full-scale bending tests on a 30 m prestressed UHPC-NC composite box girder within an actual engineering context. The testing flexural capacity $M_t=\mathrm{34,469.2} \mathrm{k}\mathrm{N}·\mathrm{m}$ exceeded the design requirement $M_d=\mathrm{18,138.0} \mathrm{k}\mathrm{N}·\mathrm{m}$, with $M_t/M_d=1.90$. Finite element modeling (FEM) was employed to analyze and predict experimental outcomes, revealing a simulated flexural capacity of approximately 37,597.1 $\mathrm{k}\mathrm{N}·\mathrm{m}$. The finite element models further explored failure mode transitions governed by the loading position while the concentrated load-to-support distance exceeds 9.62 m (shear span to effective depth ratio λ = 6.3), and the box girder fails in flexure; while less than 9.62 m, the box girder fails in shear. The flexural capacity of the test girder was also estimated using Response-2000 software and the recommended formulas from the Chinese code T/CCES 27-2021 (Technical specification for ultra-high-performance concrete girder bridge). The Response-2000 software yielded a flexural capacity estimate of $M_r=\mathrm{30,816.1} \mathrm{k}\mathrm{N}·\mathrm{m}$. The technical specification provided two estimating results: (with safety factors) $M_{u1}=\mathrm{25,414.4} \mathrm{k}\mathrm{N}·\mathrm{m}$ and (without safety factors) $M_{u2}=\mathrm{33,810.9} \mathrm{k}\mathrm{N}·\mathrm{m}$. All estimated values of Response-2000 and Chinese code were rationally conservative ($M_r,{ M}_{u1}, M_{u2}<M_t$). Comparative analysis demonstrates that Abaqus FEM accurately simulates the flexural behavior of the prestressed UHPC-NC composite box girders. Both Response-2000 calculations and the Chinese code T/CCES 27-2021 provide critical references for similar applications of prestressed UHPC-NC composite box girders. Full article

To effectively improve the anti-progressive collapse performance of steel frames, a novel reinforced joint, named the welded steel-frame joints strengthened by outer corrugated plates, was proposed. Firstly, the finite element model was validated according to previous test results. The anti-progressive collapse behavior of the novel reinforced joint was analyzed based on the validated modeling method. Effects of the central angle, corrugated plate thickness, corrugated plate width, length of circular arc, and welding angle on the anti-progressive collapse behavior of the reinforced joint were discussed. The design suggestions of the corrugated plates are presented. Finally, the effectiveness of the outer corrugated plates was further verified through one full-scale beam–column joint case and three plane frames. The results show that compared with the specimen strengthened by inner corrugated plates, the peak load and ultimate displacement of the joint strengthened by outer corrugated plates increased by 17.0% and 16.3%, respectively. Compared with the traditional full-scale beam–column joint, the load-bearing capacity and ultimate displacement of the joint strengthened by outer corrugated plates designed under reasonable suggestions significantly increased. Simply from the perspective of joints, the design suggestions were highly effective. Compared with the traditional plane steel-frame case with a total height of six floors, the bearing capacity and ultimate displacement of the plane steel-frame case strengthened by outer corrugated plates increased by 19.8% and 38.3%, respectively. The outer corrugated plates demonstrated a more pronounced effect in enhancing the collapse resistance for middle floors. Overall, the novel type of joint had a simple form and clear mechanical principles, which fully exerted the catenary capacity of the steel beams. The outer corrugated plates significantly improved the anti-progressive collapse performance of steel-frame structures. Full article

The purpose of this study was to design a Pt/TiO₂–ZrO₂ catalytic-based treatment system to remove ethanol and oxygen (O₂) from a gaseous feed stream. The ultimate target application was the conversion of ethanol and O₂ to carbon dioxide (CO₂) and water (H₂O) from a feed stream of CO₂ in a commercial beer brewing operation. Bench-scale reactions were performed at 250 °C and 300 °C, representing two temperatures under practical consideration for a full-scale catalytic reactor. The target gaseous feed stream would be expected to have a relatively low (near-stoichiometric) concentration of O₂, so the effect of O₂ concentration was also studied. On the bench scale, ethanol was completely converted to CO₂ under low flow rate conditions, and the reactions proceeded through volatile and non-volatile reaction intermediates. Results from the bench-scale tests were used to make predictions for designing a pilot-scale catalytic reactor under conditions of high and low O₂ concentration. A pilot-scale reactor was constructed and installed in a commercial brewing facility, and results from testing the pilot-scale reactor are also presented. The pilot-scale system reduced the feed stream ethanol concentrations by 99.9% while concomitantly reducing the O₂ concentrations over the course of a six-day demonstration period without generating unacceptable levels of byproducts. Full article

Noise barriers are commonly used to reduce the adverse effects of traffic noise in both urban and suburban settings. While conventional systems constructed from concrete and steel provide reliable acoustic and structural performance, they raise sustainability concerns due to high embodied energy and carbon emissions. Glued-laminated (glulam) timber has emerged as a sustainable alternative, offering a reduced carbon footprint, aesthetic appeal, and effective acoustic performance. However, the crashworthiness of timber-based noise wall systems remains under investigated, particularly with respect to the safety criteria established in the 2016 edition of the American Association of State Highway and Transportation Officials (AASHTO) Manual for Assessing Safety Hardware (MASH). This study presents the full-scale crash testing and evaluation of glulam rubrail and noise wall systems under MASH Test Level 3 (TL-3) impact conditions. Building on a previously tested system compliant with National Cooperative Highway Research Program (NCHRP) Report 350, modifications were made to increase rubrail dimensions to meet higher lateral design loads. Three full-scale vehicle crash tests were conducted using 1100C and 2270P vehicles at 100 km/h and 25 degrees, covering both front- and back-mounted wall configurations. All tested systems demonstrated acceptable structural performance, effective vehicle redirection, and compliance with MASH 2016 occupant risk criteria. There was no penetration or potential for debris intrusion into the occupant compartment, and all measured occupant risk values remained well below allowable thresholds. Minimal damage to structural components was observed. The results confirm that the modified glulam noise wall system meets current impact safety standards and is suitable for use along high-speed roadways. This work supports the integration of sustainable materials into roadside safety infrastructure without compromising crash performance. Full article

Miniaturized pressure sensors fabricated via micro-electro-mechanical systems (MEMSs) technology are ubiquitous in modern applications. However, the massively produced MEMS pressure sensors, prior to being practically used, need to be calibrated one by one to eliminate or minimize nonlinearity and zero drift. This paper presents a systematic design for the testing and calibration process of MEMS-based absolute pressure sensors. Firstly, a numerical analysis is carried out using finite element method (FEM) simulation, which verifies the accuracy of the temperature control of the physical calibration system. The simulation results reveal a slight non-uniformity of temperature distribution, which is then taken into consideration in the calibration algorithm. Secondly, deploying a home-made calibration system, the MEMS pressure sensors are tested automatically and rapidly. The experimental results show that each batch, which consists of nine sensors, can be calibrated in 80 min. The linearity and temperature coefficient (TC) of the pressure sensors are reduced from 46.5% full-scale (FS) and −1.35 × 10⁻⁴ V·K⁻¹ to 1.5% FS and −8.8 × 10⁻⁷ V·K⁻¹. Full article

Mountain glaciers are the most direct and sensitive indicators of climate change. In the context of global warming, monitoring changes in glacier elevation has become a crucial issue in modern cryosphere research. The Global Ecosystem Dynamics Investigation (GEDI) is a full-waveform laser altimeter with a multi-beam that provides unprecedented measurements of the Earth’s surface. Many studies have investigated its applications in assessing the vertical structure of various forests. However, few studies have assessed GEDI’s performance in detecting variations in glacier elevation in land ice in high-mountain Asia. To address this limitation, we selected the Southeastern Tibetan Plateau (SETP), one of the most sensitive areas to climate change, as a test area to assess the feasibility of using GEDI to monitor glacier elevation changes by comparing it with ICESat-2 ATL06 and the reference TanDEM-X DEM products. Moreover, this study further analyzes the influence of environmental factors (e.g., terrain slope and aspect, and altitude distribution) and glacier attributes (e.g., glacier area and debris cover) on changes in glacier elevation. The results show the following: (1) Compared to ICESat-2, in most cases, GEDI overestimated glacier thinning (i.e., elevation reduction) to some extent from 2019 to 2021, with an average overestimation value of about −0.29 m, while the annual average rate of elevation change was relatively close, at −0.70 ± 0.12 m/yr versus −0.62 ± 0.08 m/yr, respectively. (2) In terms of time, GEDI reflected glacier elevation changes at interannual and seasonal scales, and the trend of change was consistent with that found with ICESat-2. The results indicate that glacier accumulation mainly occurred in spring and winter, while the melting rate accelerated in summer and autumn. (3) GEDI effectively monitored and revealed the characteristics and patterns of glacier elevation changes with different terrain features, glacier area grades, etc.; however, as the slope increased, the accuracy of the reported changes in glacier elevation gradually decreased. Nonetheless, GEDI still provided reasonable estimates for changes in mountain glacier elevation. (4) The spatial distribution of GEDI footprints was uneven, directly affecting the accuracy of the monitoring results. Thus, to improve analyses of changes in glacier elevation, terrain factors should be comprehensively considered in further research. Overall, these promising results have the potential to be used as a basic dataset for further investigations of glacier mass and global climate change research. Full article

The large-scale trajectory simulation serves as a fundamental basis for the mission planning of a rocket-powered vehicle swarm. However, the traditional flight trajectory calculation method for a rocket-powered vehicle, which employs strict dynamic and kinematic models, often struggles to meet the temporal requirements of mission planning. To address the challenges of timely computation and intelligent optimization, a segmented training strategy, derived from the domain knowledge of the multi-stage flight characteristics of a rocket-powered vehicle, is integrated into the deep neural network (DNN) method. A high-precision trajectory prediction model that fuses multi-DNN is proposed, which can rapidly generate high-precision trajectory data without depending on accurate dynamic models. Based on the determination of the characteristic parameters derived from rocket-powered trajectory theory, a homemade dataset is constructed through a traditional computation method and utilized to train the DNN model. Extensive and varying numerical simulations are given to substantiate the predictive accuracy, adaptability, and stability of the proposed DNN-based method, and the corresponding comparative tests further demonstrate the effectiveness of the segmented strategy. Additionally, the real-time computational capability is also confirmed by computing the simulation of generating full trajectory data. Full article

Hydrogen-fueled internal combustion engines present a promising pathway for reducing carbon emissions in urban transportation by allowing for the reuse of existing vehicle platforms while eliminating carbon dioxide emissions from the exhaust. However, operating these engines with lean air–fuel mixtures—necessary to reduce nitrogen oxide emissions and improve thermal efficiency—leads to significant reductions in power output due to the low energy content of hydrogen per unit volume and slower flame propagation. This study investigates whether integrating a mild hybrid electric system, operating at 48 volts, can mitigate the performance losses associated with lean hydrogen combustion in a small passenger vehicle. A complete simulation was carried out using a validated one-dimensional engine model and a full zero-dimensional vehicle model. A Design of Experiments approach was employed to vary the electric motor size (from 1 to 15 kW) and battery capacity (0.5 to 5 kWh) while maintaining a fixed system voltage, optimizing both the component sizing and control strategy. Results showed that the best lean hydrogen hybrid configuration achieved reductions of 18.6% in energy consumption in the New European Driving Cycle and 5.5% in the Worldwide Harmonized Light Vehicles Test Cycle, putting its performance on par with the gasoline hybrid benchmark. On average, the lean H₂ hybrid consumed 41.2 kWh/100 km, nearly matching the 41.0 kWh/100 km of the gasoline P0 configuration. Engine usage analysis demonstrated that the mild hybrid system kept the hydrogen engine operating predominantly within its high-efficiency region. These findings confirm that lean hydrogen combustion, when supported by appropriately scaled mild hybridization, is a viable near-zero-emission solution for urban mobility—delivering competitive efficiency while avoiding tailpipe CO₂ and significantly reducing NO_x emissions, all with reduced reliance on large battery packs. Full article