Search Results (1,679)

Bike-sharing services contribute to reducing emissions and conserving natural resources within urban transportation systems. They also promote public health by encouraging physical activity and generate economic benefits through shorter travel times, lower transportation costs, and decreased demand for parking infrastructure. This paper examines the use of shared micro-mobility services in the Italian cities of Florence and Bologna, based on an analysis of GPS origin–destination data and associated temporal coordinates provided by the RideMovi company. Given the still-limited number of studies on free-floating and electric-scooter-sharing systems, the objective of this work is to quantify the performance of electric bikes and e-scooters in bike-sharing schemes and compare it to traditional, muscular bikes. Trips were reconstructed starting from GPS data of origin and destination of the trip with a shortest path criteria that considers the availability of bike lanes. Results show that e-bikes are from 22 to 26% faster on average with respect to muscular bikes, extending trip range in Bologna but not in Florence. Electric modes attract more users than traditional bikes, e-bikes have from 40 to 128% higher daily turnover in Bologna and Florence and e-scooters from 33 to 62% higher in Florence with respect to traditional bikes. Overall, turnover is fairly low, with less than two trips per vehicle per day. The performance is measured in terms of trip duration, speed, and distance. Further characteristics such as daily turnover by transport mode are investigated and compared. Finally, spatial analysis was conducted to observe demand asymmetries in the two case studies. The results aim to support planners and operators in designing and managing more efficient and user-oriented services. Full article

Evaluating transit-oriented development (TOD) efficiency in metro station areas remains challenging, as the traditional “Node–Place” model gives limited consideration to guiding factors and struggles to account for inter-regional flows under spatial heterogeneity. To address these limitations, this study develops an enhanced “Node–Place–Accessibility” model by introducing an accessibility dimension to better capture station-level connectivity and walkability. DepthmapX and a convex space approach were applied to quantify station-area accessibility, reflecting passengers’ perceived spatial distance during transfers. The model establishes a TOD measurement framework based on spatial coupling and functional connectivity, enabling the identification of factors influencing metro ridership across different spatial scales. Moran’s I was employed to describe spatial agglomeration and a local spatial clustering method integrating both passenger flow and built-environment (BE) characteristics was constructed to reveal differentiated spatial patterns. The Multiscale Geographically Weighted Regression (MGWR) model was further employed to quantify the spatially varying impacts of BE factors on ridership. Results indicate that the improved model provides stronger discriminative power in identifying “balanced stations,” and that BE conditions exert significant impact on metro ridership, particularly in areas with strong coordination among TOD components. Among the BE dimensions, design granularity exerts a more substantial impact on ridership than connectivity, density, and accessibility. This methodology provides large cities with a reliable tool for formulating targeted strategies that promote positive interactions between transportation and land use, thereby supporting sustainable urban development. Full article

This paper focuses on mixed seeds of Vicia villosa and Avena sativa, with their discrete element model and contact parameters being systematically calibrated and validated to provide reliable theoretical support for the structural design and parameter optimization of the air-assisted seed delivery system. The physical properties of both seed types, including triaxial dimensions, density, moisture content, Poisson’s ratio, and shear modulus, were first measured. The Hertz–Mindlin (no slip) contact model and the multi-sphere aggregation method were employed to construct the discrete element models of Vicia villosa and Avena sativa, with preliminary calibration of the intrinsic model parameters. Poisson’s ratio, elastic modulus, collision restitution coefficient, static friction coefficient, and rolling friction coefficient between the seeds and PLA plastic plate were determined through uniaxial compression, free fall, inclined sliding, and inclined rolling tests. Each test was repeated five times, and the calibration criterion for contact parameters was based on minimizing the relative error between simulation and experimental results. Based on this, experiments on the packing angle of mixed seeds, steepest slope, and a three-factor quadratic rotational orthogonal combination were conducted. The inter-seed collision restitution coefficient, static friction coefficient, and rolling friction coefficient were set as the experimental factors. A total of 23 treatments were designed with repetitions at the center point, and a regression model was established for the relative error of the packing angle with respect to each factor. Based on the measured packing angle of 28.01° for the mixed seeds, the optimal contact parameter combination for the mixed seed pile was determined to be: inter-seed collision restitution coefficient of 0.312, static friction coefficient of 0.328, and rolling friction coefficient of 0.032. The relative error between the simulated packing angle and the measured value was 1.32%. The calibrated inter-seed contact parameters were further coupled into the EDEM–Fluent gas–solid two-phase flow model. Simulations and bench verification tests were carried out under nine treatment combinations, corresponding to three fan speeds (20, 25, and 30 m·s⁻¹) and three total transport efficiencies (12.5, 17.5, and 22.5 g·s⁻¹), with the consistency coefficient of seed distribution in each row being the main evaluation variable. The results showed that the deviation in the consistency coefficient of seed distribution between the simulation and experimental measurements ranged from 1.24% to 3.94%. This indicates that the calibrated discrete element model for mixed seeds and the EDEM–Fluent coupled simulation can effectively reproduce the air-assisted seed delivery process under the conditions of Vicia villosa and Avena sativa mixed sowing, providing reliable parameters and methodological support for the structural design of seeders and DEM-CFD coupled simulations in legume–grass mixed sowing systems. Full article

Urbanisation and the increasing concentration of populations in cities present significant challenges for achieving sustainable mobility and advancing the energy transition. Private vehicles, particularly those powered by internal combustion engines, remain the primary contributors to urban air pollution and greenhouse gas emissions. This situation has prompted the European Union to accelerate transport decarbonisation through comprehensive policy frameworks, notably the “Fit for 55” package, which aims to reduce net greenhouse gas emissions by 55% by 2030. These measures underscore the urgency of shifting towards low-emission transport modes. In this context, electric vehicles (EVs) play a key role in supporting Sustainable Development Goal 7 by promoting cleaner and more efficient transport solutions, and Sustainable Development Goal 11, aimed at creating more sustainable and liveable cities. Despite growing policy attention, the adoption of EVs remains constrained by users’ concerns regarding purchase costs, driving range, and the availability of charging infrastructure, as shown by the findings of this study. In this context, this study explores the determinants of EV adoption in Italy by employing a combined methodological approach that integrates a stated preference (SP) survey with discrete choice modelling. The analysis aims to quantify the influence of economic, technical, and infrastructural factors on users’ willingness to switch to EVs, providing insights for policymakers and industry stakeholders to design effective strategies for accelerating the transition toward the sustainable mobility. Full article

Efficient scheduling of automated rail transportation in hilly orchards is critical for maintaining fruit freshness and ensuring timely market delivery. This study develops a dynamic scheduling method for multi-transporter orchard rail systems through mathematical modeling, reinforcement learning algorithms, and field validation. We formulated a comprehensive scheduling model and designed four distinct frameworks to address randomly arriving tasks. In the optimal framework (Framework 3, which was chosen due to its hybrid strategy combining periodic global planning and local task point adjustment), we compared six rule-based heuristic algorithms against three reinforcement learning approaches: centralized SAC, decentralized MARL-DQN, and conventional DQN. Additionally, two emergency response strategies were developed and evaluated. Simulation experiments demonstrated that Framework 3 maintained high load factors while reducing task completion times. The centralized SAC algorithm outperformed other methods, achieving 1533.71 ± 50.09 reward points compared to 863.67 ± 30.54 for rule-based heuristics, a 77.6% improvement. For emergency tasks, Strategy 2 achieved faster response times with minimal disruption to routine operations. Field trials on a 153 m physical track with four autonomous transporters validated the DQN algorithm, confirming good sim-to-real consistency. This research provides a practical solution for dynamic scheduling challenges in hilly orchards, offering measurable efficiency improvements over traditional methods. Full article

Bridges serve as vital connectors in the transportation network and infrastructure. Given their significance, it is crucial to continuously monitor bridge conditions to ensure the efficient operation of transportation systems. With advancements in sensing technologies, transportation infrastructure assessment has evolved through the integration of structural health monitoring (SHM) methodologies. Traditionally, bridge monitoring has relied on direct sensor instrumentation; however, this method encounters practical obstacles, including traffic disruptions and limited sensor availability. In contrast, indirect bridge health monitoring (iBHM) utilizes data from moving traffic on the bridge itself. This innovative approach eliminates the need for embedded instrumentation, as sensors on vehicles traverse the bridge, capturing the dynamic characteristics of the bridge. In this paper, system identification methods are explored to analyze the acceleration data gathered using a bicycle-mounted sensor traversing the bridge. To explore the feasibility of this micromobility-based approach, bridge responses are measured under varying traversing conditions combined with dynamic rider–bicycle–bridge interaction for comprehensive evaluation. The proposed method involves a hybrid approach combining Wavelet Packet Transform (WPT) with Synchro-extracting Transform (SET), which are employed to analyze the time–frequency characteristics of the acceleration signals of bike-based iBHM. The results indicate that the combination of WPT-SET demonstrates superior robustness and accuracy in isolating dominant nonstationary frequencies. The performance of the proposed method is compared with another prominent signal processing algorithm known as Time-Varying Filtering Empirical Mode Decomposition (TVF-EMD). Ultimately, this study underscores the potential of bicycles as low-cost, mobile sensing platforms for iBHM that are otherwise inaccessible to motorized vehicles. Full article

The blowout preventer (BOP) is the most important and the last line of safety defense in drilling engineering. Once a blowout occurs and the BOP fails, engineers will lose control of the entire wellbore pressure, and combustible fluids in the formation will continuously sprayed out, which can easily cause huge losses of life and property. At present, reliable and highly recognized emergency measures for BOP failure are lacking. Therefore, we propose a plugging method after the failure of the BOP that can maintain good control within the secondary well control. Numerical and experimental results indicate that using a small-to-medium displacement (1–2 m³/min) during the early stage of plugging and applying multiple plugging and killing cycles significantly improves plugging stability and killing efficiency. PEEK (polyether ether ketone) was selected as the bridging material for field plugging tests on full-scale blowout preventers, verifying its sealing effectiveness at pressures up to 80 MPa. Subsequently, the CFD–DEM was used to simulate the well killing process after plugging. This study mainly focused on the transportation of particles in a pipeline and the analysis of the process of well killing after plugging. The research results indicate that PEEK demonstrates sufficient pressure-bearing capacity under real blowout conditions. Also reveal that PEEK’s exceptional wear resistance and impact strength help maintain sealing stability during repeated particle–wall collisions, effectively reducing secondary erosion and prolonging the operational lifespan of temporary plugging structures. After undergoing six high-pressure tests of 70 MPa and two high-pressure tests of 80 MPa within 25 min, it remained intact. Both cylindrical and spherical particles can smoothly pass through the storage tank and double-bend pipeline at different displacements. Considering the retention effect of the plugging material, it is recommended to use 1–2 m³/min of pumping the plugging material at medium and small displacements in the early stage of plugging. During the process of plugging and killing, it is recommended to use alternating plugging and killing across multiple operations to prevent further blowouts to achieve the best plugging and killing effect. Full article

Rapid progress in sustainable and intelligent transportation has intensified interest in smart airport initiatives, driven by the need to support environmentally responsible and technology-enabled aviation development. As complex sociotechnical subsystems of smart aviation, smart airports integrate advanced digital, operational, and organizational technologies to enhance efficiency, resilience, and passenger experience. With increasing emphasis on such transformations, multiple strategic development plans have emerged, each with distinct priorities and implementation pathways, which necessitates a rigorous and transparent evaluation mechanism to support informed decision-making under uncertainty. This study proposes an integrated spherical fuzzy multi-criteria decision-making (MCDM) framework for assessing and ranking smart airport development plans. Subjective expert judgments are modeled using spherical fuzzy sets, allowing for the simultaneous consideration of positive, neutral, and negative membership degrees to better capture linguistic and ambiguous information. Expert importance is determined through a hybrid weighting scheme that combines a social trust network model with an entropy-based objective measure, thereby reflecting both relational credibility and informational contribution. Criterion weights are computed through an integrated approach that merges criteria importance through the inter-criteria correlation (CRITIC) method with the stepwise weight assessment ratio analysis (SWARA) method, balancing data-driven structure and expert strategic preferences. The weighted evaluations are aggregated using a spherical fuzzy extension of the combined compromise solution (CoCoSo) method to obtain the final rankings. A case study involving smart airport development planning in China is conducted to illustrate the applicability of the proposed approach. Sensitivity, ablation, and comparative analyses demonstrate that the framework yields stable, discriminative, and interpretable rankings. The results confirm that the proposed method provides a reliable and practical decision support tool for smart airport development and can be adapted to other smart transportation planning contexts. Full article

Grafting is a strategy to mitigate biotic and abiotic stresses in coffee systems. However, initial compatibility indicators between Coffea arabica scions and C. canephora rootstocks under controlled conditions remain insufficiently documented. We evaluated the physiological and morphological compatibility of four C. arabica cultivars (Bourbon, Geisha, Catuai, and Villa Sarchí) grafted onto C. canephora (Robusta) rootstock in a tropical highland nursery in the Peruvian Amazon. Seven physiological and six morphological variables were measured. Statistical analyses included one-way ANOVA and Kruskal–Wallis tests with Bonferroni post hoc comparisons. Two physiological parameters were significantly higher in Villa Sarchí grafts than in Robusta: PSII quantum yield (+0.044 units; p < 0.05) and electron transport rate (+14.702 µmol e⁻ m⁻² s⁻¹; p < 0.05); by contrast, net photosynthesis, stomatal conductance, intercellular CO₂ concentration, and transpiration did not differ, and maximum PSII efficiency was similar among treatments (p = 0.509). Conversely, no morphological trait showed significant differences, and graft-take was high across all combinations. The results support the use of Coffea robusta as a rootstock for these four cultivated varieties, thereby offering the possibility of improving their resilience in tropical highland regions. Full article

In transport applications, metal hydride tanks represent a promising solution for safe and effective hydrogen storage. In this paper, we examine the effects of operational conditions on hydrogen supply continuity from MNTZV-159 tanks into the fuel cell of a hydrogen-powered vehicle. Numerical and analytical calculations are based on thermal field measurements, pressure and the hydrogen flow rate during absorption and desorption. Heat transport and tank thermal field homogeneity were identified in an ANSYS CFX environment, and the results were validated using an analytical model created based on thermal balances. The key outcome of this paper is the identification of the tank time constant—483 s—found in the tested conditions, something which is important in designing control strategies for technical transport systems. The results indicate that an appropriate combination of experimental measurements, numerical simulations and analytical calculations facilitates identifying a tank’s dynamic characteristics, as well as operation optimisation. These findings help in achieving the more reliable and efficient use of MNTZV-159 metal hydride tanks in hydrogen-powered vehicles and facilitating their integration into systems that strive for sustainable mobility and renewable energy use. Full article

This paper presents a detailed experimental evaluation of a newly developed diesel fuel additive, specifically formulated to enhance the energy efficiency and emission characteristics of internal combustion engine (ICE) vehicles, with particular emphasis on its applicability to aging vehicle fleets. Diesel engines are known for producing significant amounts of harmful emissions, necessitating the development of effective mitigation strategies. One such approach involves the use of fuel additives. The additive under investigation is a proprietary formulation containing 1-(N,N-bis(2-ethylhexyl)aminomethyl)-1,2,4-triazole and other compounds. To the best of our knowledge, this specific additive composition has not yet been tested or reported in the existing scientific literature. To evaluate the real-world contribution of such additives, a comprehensive set of controlled measurements was conducted in a certified chassis dynamometer laboratory, including an exhaust gas analyser and supplementary diagnostic equipment. The testing protocol comprised repeated measurement cycles under identical driving conditions, both without and with the additive. Exhaust gas concentrations of CO₂, CO, and NOx were continuously monitored. Simultaneously, fuel consumption and engine performance were tracked over a cumulative driving distance of 2000 km. The results indicate measurable improvements across all monitored domains. CO₂ emissions decreased by 4.57%, CO by 14.29%, and NOx by 3.12%. Fuel consumption was reduced by 4.79%, while engine responsiveness and power delivery showed moderate but consistent enhancements. These improvements are attributed to more complete combustion and an increased cetane number enabled by the additive’s chemical structure. The findings support the adoption of advanced additive technologies as part of transitional strategies towards low-emission transportation systems. Full article

Suspended sediment transport in large rivers is characterized by complex cross-sectional patterns. This study investigates the cross-sectional distribution of the suspended sediment concentration (SSC), based on 15 measurement campaigns at six stations along a 67 km reach of the middle Rhine in Germany. Utilizing a multi-method approach, we conducted turbidity and acoustic backscatter measurements, in situ particle size data, recorded water quality parameters such as electrical conductivity, and took 495 pump-based water samples over a period of 2.5 years. Statistical analysis of this comprehensive dataset shows that lateral differences have greater importance for the cross-sectional SSC distribution than vertical differences, suggesting that incomplete river mixing is of greater importance than vertical stratification for uncertainties in load calculations. We demonstrate that surface measurements are consistently representative for the whole water column and that applying the traditional Rouse equation for vertical extrapolation from surface measurements leads to large errors. We conclude that efficient monitoring programs should prioritize covering the lateral SSC distribution for more accurate load calculations and offer practical recommendations for improved SSC monitoring in similar conditions. Full article

This study presents a dual surfactant-assisted hydrothermal approach for the synthesis of Co₃V₂O₈ (CoVO) nanostructures and their surfactant-modified derivatives, PVP-assisted Co₃V₂O₈ (P-CoVO) and PVP–SDS co-assisted Co₃V₂O₈ (P/S-CoVO), which were directly grown on nickel foam. The use of PVP and SDS enabled controlled nucleation and growth, yielding a hierarchical nanoflower-like morphology in P/S-CoVO with increased porosity, a higher surface area, and uniform structural features. Comprehensive physicochemical characterization confirmed that surfactant incorporation effectively modulated particle size, dispersion, and active-site availability. Electrochemical measurements demonstrated that P/S-CoVO exhibited superior performance, with the largest CV area, low equivalent series resistance (0.52 Ω), and a maximum areal capacitance of 13.71 F cm⁻² at 8 mA cm⁻², attributable to rapid redox kinetics and efficient ion transport. The electrode also showed excellent cycling stability, retaining approximately 83.7% of its initial capacitance after 12,000 charge–discharge cycles, indicating robust structural integrity and interfacial stability. Additionally, an asymmetric supercapacitor device (P/S-CoVO//AC) delivered a high energy density of 0.082 mWh cm⁻², a power density of 1.25 mW cm⁻², and stable operation within a 1.5 V potential window. These results demonstrate that cooperative surfactant engineering provides an effective and scalable strategy to enhance the morphology, electrochemical kinetics, and durability of Co₃V₂O₈-based electrodes for next-generation high-performance supercapacitors. Full article

The effectiveness of transit-oriented development (TOD) in achieving emission reductions and energy savings is highly influenced by policy frameworks, the accessibility of sustainable transport systems, and the degree of land use integration. This study investigated the implementation of TOD in Dukuh Atas along the Sudirman–Thamrin corridor in Jakarta to assess its role in promoting energy efficiency and lowering emissions. The analysis incorporated carbon emission calculations, annualized traffic volumes, and emissions data, alongside land use metrics such as the floor area ratio (FAR), job-to-housing ratio, and point-of-interest (POI) density. The findings indicate that while TOD implementation in the corridor is still evolving, there were positive outcomes in several key areas. Energy efficiency measures have been partially realized through the operation of electric buses in the bus rapid transit (BRT) system, electrified rail modes, such as commuter lines, mass rapid transit (MRT), and light rail transit (LRT), and improved pedestrian infrastructure, as reflected in a favorable Pedestrian Environmental Quality Index (PEQI). Public transport ridership has significantly increased, contributing to a measurable reduction in emissions from private vehicle use. The land use analysis showed that medium- to high-density housing dominated (78.94% FAR), with a job-to-housing ratio of approximately 1:2. This study also found that the emission estimates were moderately sensitive to changes in both emission factors (EFs) and vehicle kilometers traveled (VKT). Overall, the results suggest that TOD can effectively contribute to energy savings and emission reductions by enhancing public transport usage and reducing dependence on motorcycles. Moreover, the efficacy of modal shifting in the Global South is significantly influenced by population mobility characteristics, which are intricately linked to socio-cultural factors, alongside government initiatives to improve the quality of mass public transportation systems (e.g., integration, availability, service coverage, affordable fares, and inclusive design). Full article

Current research on the performance and emissions of vehicles and internal combustion engines should include analysis of efficiency-enhancing technologies and emission reduction strategies across a variety of vehicle systems. To improve both performance and emission control, it is necessary to examine advanced heavy-duty driveline technologies, considering their real-world impact on fuel economy and emission reduction under various driving conditions. This article will deal with predictive cruise control (PCC) and its influence on the operating characteristics of a truck, specifically a semi-trailer combination. The measurement was carried out using dynamic driving tests of a truck on a selected road. The use of electronic systems for automatically maintaining the vehicle’s motion states (especially speed) based on the specified conditions most often has several benefits for the driver not only from the point of view of vehicle operation but also from the point of view of transport companies (cost reduction). It is generally known that the use of these electronic systems reduces the vehicle’s fuel consumption and therefore also reduces the amount of exhaust gases. Comparing the individual directions of the road tests, the difference in relative maximum power utilization between the driver and the PCC system was 26.42% in the ST-MY direction and 23.81% in the MY-ST direction. The use of PCC also results in fuel savings of up to 17.11%. This study provides new insights into the quantification of the impact of PCC on fuel consumption in real operating conditions and highlights the potential for integrating PCC into driver assistance systems and logistics planning to reduce costs and emissions in freight transport. Further research could focus on applying this system in specific road conditions. Full article