Search Results (37)

The electrification of public transport with battery electric buses (BEBs) poses technical, regulatory, and environmental challenges. This paper analyzes the impact of BEB charging on a Brazilian urban medium-voltage (MV) feeder using a novel methodology to convert utility GIS data into OpenDSS simulation models. The study utilizes Geographic Database of the Distribution Company (BDGD) data from the Brazilian Electricity Regulatory Agency (ANEEL) and OpenDSS simulations. Motivated by Cuiabá’s proposal to electrify its public bus fleet, four realistic scenarios were simulated, incorporating distributed photovoltaic (PV) generation and vehicle-to-grid (V2G) operation. Results show that up to 118 BEBs can be charged simultaneously without voltage violations. However, thermal overload occurs beyond 56 units, requiring conductor upgrades or load redistribution. PV systems can supply up to 64% of the daily energy demand but introduce reverse power flows and overvoltages, indicating the need for dynamic control. V2G operation enables peak shaving but also leads to overvoltages when more than 33 buses inject power concurrently. The findings suggest that while the current infrastructure partially supports fleet electrification, future scalability depends on integrating smart grid features and reinforcing the system. Although focused on Cuiabá, the methodology offers a replicable approach for low-carbon urban mobility planning in similar developing regions. Full article

The penetration rate of battery electric buses (BEBs) continues to rise, and the design of BEB networks has become the foundation for establishing efficient and sustainable public transportation systems. Improving the equity of bus network and reducing the total cost of the bus system are taken as the targets, a multi-objective programming model for TNDP is proposed in this study. Among them, the Gini coefficient of bus travel times during peak hours and the direct travel proportion of the elderly during non-peak hours are used to describe the equity of the bus network. When calculating the comprehensive cost, factors such as the fleet size of battery electric buses, charging facilities requirements, and charging costs are taken into account. To enhance the reliability of the obtained results, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is adopted to generate the Pareto-optimal solution set. The Mandl’s benchmark network is used for comparative validation, and a case study based on the road network of Zhengzhou is undertaken. Calculation results indicate that the proposed model not only minimizes the total travel costs but also significantly reduces the Gini coefficient of the transportation mode distribution. Under the constraint of overall expenses, it effectively improves the equity and the direct travel proportion of the elderly served by the bus system. The results can provide quantitative support to formulate livelihood transportation policies for local government and optimize the allocation of public transportation resources. Full article

We present calculations of the ionization cross sections for collisions of electrons and positrons with the acene molecules naphthalene, anthracene, tetracene, pentacene, and hexacene. The computations are performed using the binary-encounter Bethe (BEB) model and its modifications for positrons. The results show that all acenes exhibit maxima in their ionization cross sections at the same incident energy, regardless of molecular size. Furthermore, we find that the magnitude of the cross sections scales linearly with the number of rings in the acene molecules. Full article

Limited molecular data exist on zoonotic parasites Cryptosporidium spp., Giardia duodenalis, and Enterocytozoon bieneusi in Angus calves from Guizhou, China. This study constitutes the first molecular epidemiological survey of these pathogens in this region. 817 fecal samples from Angus calves across 7 intensive beef farms (Bijie City). Nested PCR methods targeting SSU rRNA (Cryptosporidium spp.), gp60 (Cryptosporidium bovis subtyping), bg/gdh/tpi (G. duodenalis), and ITS (E. bieneusi) coupled with DNA sequencing were employed. DNA sequences were analyzed against the NCBI. database. Statistical differences were assessed via a generalized linear mixed-effects model. Cryptosporidium spp. prevalence 23.5% (192/817; 95% CI 28.1–34.6%), with C. bovis predominating 89.6% (172/192; 95% CI 84.4–93.5%) and six subtypes (XXVIa-XXVIf). Highest infection in 4–8-week-olds 29.9% (143/479; 95% CI 25.8–34.1%) (p < 0.01). G. duodenalis: 31.3% (256/817; 95% CI 28.1–34.6%) positive, overwhelmingly assemblage E 97.6% (6/256; 95% CI 0.9–5.0%), zoonotic assemblage A was marginal 0.7% (6/817; 95% CI 0.3–1.6%). Farm-level variation exceeded 10-fold (e.g., Gantang: 55.0% (55/100; 95% CI 44.7–65.0%) vs. Tieshi: 4.9% (5/102; 95% CI 1.6–11.1%). E. bieneusi: prevalence 19.7% (161/817; 95% CI 17.0–22.6%), exclusively zoonotic genotypes BEB4: 49.7% (80/161; 95% CI 41.7–57.7%); I: 40.4% (65/161; 95% CI 32.7–48.4%). Strong diarrhea association (p < 0.01) and site-specific patterns (e.g., Guanyindong: 39.2%). While Giardia exhibited the highest prevalence (31.3%) with minimal zoonotic risk, Enterocytozoon—despite lower prevalence (19.7%)—posed the greatest public health threat due to exclusive circulation of human-pathogenic genotypes (BEB4/I) and significant diarrhea association, highlighting divergent control priorities for these enteric parasites in Guizhou calves. Management/Public health impact: Dominant zoonotic E. bieneusi genotypes (BEB4/I) necessitate: 1. Targeted treatment of 4–8-week-old Angus calves. 2. Manure biofermentation (≥55 °C, 3 days), and 3. UV-disinfection (≥1 mJ/cm²) for karst water to disrupt transmission in this high-humidity region. Full article

The electron-impact ionization and partial ionization cross sections are reported for few silicon-chlorine molecules using semi-empirical methods. The partial ionization cross sections are determined using a modified version of the binary-encounter-Bethe model. In this approach, the binary-encounter-Bethe model is modified through a two-step process, namely, transforming the binding energies of the occupied orbitals and introducing a scaling factor. The scaling can be done using either the mass spectrometry data or experimental values of cross sections. It correctly adjusts the scaling term of the BEB model so that the order of magnitude of resulting partial ionization cross sections is the same as that of experimental values. Further, the use of the experimental value of ionization and appearance energy values ensures that the cross sections have a correct threshold. This further mitigates the dependence of cross sections on energy at low values. The role of the scaling factor and the behavior of branching ratios is also examined at different energies. The species whose partial ionization cross sections are reported are highly relevant in plasma processing. However, the proposed model can be extended to any multi-centerd molecular structures comprising a large number of atoms or electrons, except in cases where resonance effects or additional ionization channels become significant. The mass spectrometry data is of utmost importance in computing partial ionization cross sections in order to obtain reliable results. Full article

(1) Background: Ionizing radiation in the Earth’s atmosphere drives key chemical transformations affecting atmospheric composition. Despite their environmental relevance, experimental data on proton collisions with hydrofluorocarbons remain limited, and theoretical models for total cross-sections and stopping power are still underdeveloped. (2) Methods: This study applies Rudd’s semiempirical model to calculate proton impact ionization cross-sections for the CF₃CH₂F molecule, considering contributions from both outer and inner electron shells. The model enables the estimation of differential cross-sections and the average energy of secondary electrons. In addition, we calculate the photoionization cross-sections using a discretized representation of the continuum—the so-called pseudo-spectrum—obtained through TDDFT with PBE0 as an exchange–correlation functional and compare it with the cross-section obtained for proton impact in the high-energy limit. (3) Results: The Rudd model proves highly adaptable and suitable for numerical applications. However, its validation is hindered by the scarcity of experimental data. Existing models, such as SRIM and Bethe–Bloch, show significant discrepancies due to their limited applicability at intermediate energies and lack of molecular structure consideration. (4) Conclusions: A comparison between the Rudd and BEB models reveals strong agreement in the analyzed energy range. This consistency stems from both models accounting for the molecular structure of the target, as well as from the fact that protons and electrons possess charges of the same magnitude, supporting a coherent description of ionization processes at these energies. Full article

This article presents the maiden investigation of the electronic structural properties of the Sr⁺ ion confined inside fullerene. The Dirac equations are solved to calculate the energy levels, probability distributions, etc. for various confinement depths of the Gaussian Annular Square Well (GASW) potential using the Multi-Configuration Dirac Hartree–Fock (MCDHF) formalism. The wavelengths, transition probabilities, and oscillator strengths are reported for the $5S_{1/2}⟷5P_{1/2}$ ($D_1$ line) and $5S_{1/2}⟷5P_{3/2}$ ($D_2$ line) transitions of the encapsulated ion. We also estimate variations in the line intensity ratio, electron density, Coulomb coupling parameter, etc. A suggested direction for the calculation of electron impact ionization cross-section using the binary-encounter Bethe (BEB) model with the present data is also given. Full article

Battery electric buses (BEBs) are a sustainable and environmentally friendly solution for modern transit systems, offering zero tailpipe emissions and reduced noise pollution. However, due to the relatively short driving range and limited charging resources, it is crucial to jointly optimize the BEB fleet, charging schedules, and charging infrastructure to improve operational efficiency. This study proposes a BEB charging scheduling method with multiple types of vehicles and chargers. In particular, a partial charging strategy, charging continuity, and the compatibility of vehicles with chargers are incorporated. We first formulate a mixed-integer programming model to minimize the total costs of the BEB transit system, including the purchase costs of chargers, fleet composition costs, and electricity costs. Then, a column generation (CG) algorithm is designed to solve the model, and a case study based on a real transit network in Nanjing, China, was conducted. The results verify the effectiveness of the proposed model and algorithm. The findings in this study provide practical guidance on BEB charging scheduling and promote the sustainable development of bus transit systems. Full article

The total cross-sections for the single electron-impact ionization of pyrimidine (C₄H₄N₂), 2-chloropyrimidine (2-C₄H₃ClN₂), 5-chloropyrimidine (5-C₄H₃ClN₂), 2-bromopyrimidine (2-C₄H₃BrN₂) and 5-bromopyrimidine (5-C₄H₃BrN₂) molecules have been calculated with the binary-encounter-Bethe model from the ionization threshold up to 5 keV. The input data for the BEB calculations concerning electronic structure of the studied targets have been obtained with quantum chemical methods including the Hartree–Fock (H-F) and the outer valence Green function (OVGF) methods. The calculated cross-section for the ionization of the pyrimidine molecules due to electron impact is compared with available experimental and theoretical data. The question of the magnitude the pyrimidine ionization cross-section is also discussed, as is the efficiency of the ionization process of studied halogenated derivatives of pyrimidine. Full article

Due to the increasing share of battery electric buses (BEBs) in cities, depots need to be adapted to the increasing load demand. The integration of renewable energy sources (RESs) into a depot can increase the self-consumption, but optimal sizing is required for a cost-efficient and reliable operation. Accordingly, this paper introduces a co-design optimization framework for a depot microgrid, equipped with photovoltaics (PVs) and an energy storage system (ESS). Three European cities are considered to evaluate the effect of different environmental conditions and electricity prices on the optimal microgrid design. Accurate models of the different subsystems are created to estimate the load demand and the power generation. Different energy management strategies (EMSs), developed to properly control the power flow within the microgrid, are compared in terms of operational costs reduction, one of which was also experimentally validated using a hardware-in-the-loop (HiL) test setup. In addition, the total cost of ownership (TCO) of the depot microgrid is analyzed, showing that an optimally designed depot microgrid can reduce the charging-related expenses for the public transport operator (PTO) by 30% compared to a scenario in which only the distribution grid supplies the BEB depot. Full article

With an increasing adoption of battery-electric bus (BEB) fleets, developing a reliable charging schedule is vital to a successful migration from their fossil fuel counterparts. In this paper, a simulated annealing (SA) implementation is developed for a charge scheduling framework for a fixed-schedule fleet of BEBs that utilizes a proportional battery dynamics model, accounts for multiple charger types, allows partial charging, and further considers the total energy consumed by the schedule as well as peak power use. Two generation mechanisms are implemented for the SA algorithm, denoted as the “quick” and “heuristic” implementations, respectively. The model validity is demonstrated by utilizing a set of routes sampled from the Utah Transit Authority (UTA) and comparing the results against two other models: the BPAP and the Qin-Modified. The results presented show that both SA techniques offer a means of generating operationally feasible schedules quickly while minimizing the cost of operation and considering battery health. Full article

This study evaluates the projected impact of climate change on wheat production in Northwest Tunisia, specifically at Medjez El Beb (36.67 m, 9.74°) and Slougia (36.66 m, 9.6°), for the period 2041–2070. Using the CNRM-CM5.1 and GFDL-ESM2M climate models under RCP4.5 and RCP8.5 scenarios, coupled with the AquaCrop and SIMPLE crop growth models, we compared model outputs with observed data from 2016 to 2020 to assess model performance. The objective was to determine how different climate models and scenarios affect wheat yields, biomass, and growth duration. Under RCP4.5, projected average yields are 7.709 q/ha with AquaCrop and 7.703 q/ha with GFDL-ESM2M. Under RCP8.5, yields are 7.765 tons/ha with AquaCrop and 7.198 q/ha with SIMPLE Crop, indicating that reduced emissions could improve wheat growth conditions. Biomass predictions showed significant variation: in Medjez El Beb, average biomass is 17.99 tons/ha with AquaCrop and 18.73 tons/ha with SIMPLE Crop under RCP8.5. In Slougia, average biomass is 18.90 tons/ha with AquaCrop and 19.04 tons/ha with SIMPLE Crop under the same scenario. Growth duration varied, with AquaCrop predicting 175 days in Medjez El Beb and 178 days in Slougia, while SIMPLE Crop predicted 180 days in Medjez El Beb and 182 days in Slougia, with a standard deviation of ±12 days for both models. SIMPLE Crop demonstrated higher accuracy in predicting growth cycle duration and yield, particularly in Slougia, with mean bias errors of −3.6 days and 2.26 q/ha. Conversely, AquaCrop excelled in biomass prediction with an agreement index of 0.97 at Slougia. Statistical analysis revealed significant yield differences based on climate models and emission scenarios, with GFDL-ESM2M under RCP4.5 showing more favorable conditions. These findings emphasize the importance of model selection and calibration for accurately projecting the agricultural impacts of climate change, and they provide insights for enhancing prediction accuracy and informing adaptation strategies for sustainable wheat production in Northwest Tunisia. Full article

In Thailand, diesel buses are notorious for their poor energy efficiency and contribution to air pollution. To combat these issues, battery electric buses (BEBs) have emerged as a promising alternative. However, their high initial costs have posed challenges for fleet management, especially for agencies such as the Bangkok Mass Transit Authority (BMTA). This study aims to revolutionize BEB fleet management by developing an energy model tailored to the BMTA’s needs. The methodology consists of two crucial steps: analyzing BMTA bus routes and designing fleet management and charging systems. Through this process, the study seeks to determine the maximum number of BEBs that can be operated on each route with the fewest chargers possible. The results reveal exciting possibilities. Within the city bus landscape, two out of five BMTA bus routes show potential for transitioning to BEBs, provided they meet a maximum energy requirement of 200 kWh every two rounds. This analysis identifies routes ripe for BEB adoption while considering the limitations of battery size. In the next step, the study unveils a game-changing strategy: a maximum of 13 BEBs can operate on two routes with just four chargers requiring 150 kW each. This means fewer chargers and more efficient operations. Plus, the charging profile peaks at 600 kW from 4:00 to 8:00 p.m., showing when and where the fleet needs power the most. However, the real eye-opener? Significant energy savings of THB 10.44 million per year compared to diesel buses, with an initial investment cost savings of over 37%. These findings underscore the potential for BEB fleet management to revolutionize public transportation and save money in the long run. However, there is more work to be done. The study highlights the need for real-time passenger considerations, the development of post-service charging strategies, and a deeper dive into total lifetime costs. These areas of improvement promise even greater strides in the future of sustainable urban transportation. Full article

As the adoption of battery electric buses (BEBs) in public transportation systems grows, the need for precise energy consumption forecasting becomes increasingly important. Accurate predictions are essential for optimizing routes, charging schedules, and ensuring adequate operational range. This paper introduces an innovative forecasting methodology that combines a propulsion and auxiliary energy model with a novel concept, the environment generator. This approach addresses the primary challenge in electric bus energy forecasting: estimating future environmental conditions, such as weather, passenger load, and traffic patterns, which significantly impact energy demand. The environment generator plays a crucial role by providing the energy models with realistic input data. This study validates various models with different levels of model complexity against real-world operational data from a case study of over one year with 16 electric buses in Göttingen, Germany. Our analysis thoroughly examines influencing factors on energy consumption, like altitude, temperature, passenger load, and driving patterns. In order to comprehensively understand energy demands under varying operational conditions, the methodology integrates data-driven models and physical simulations into a modular and highly accurate energy predictor. The results demonstrate the effectiveness of our approach in providing more accurate energy consumption forecasts, which is essential for efficient electric bus fleet management. This research contributes to the growing body of knowledge in electric vehicle energy prediction and offers practical insights for transit authorities and operators in optimizing electric bus operations. Full article

Recent attention for reduced carbon emissions has pushed transit authorities to adopt battery electric buses (BEBs). One challenge experienced by BEB users is extended charge times, which create logistical challenges and may force BEBs to charge when energy is more expensive. Furthermore, BEB charging leads to high power demands, which can significantly increase monthly power costs and may push the electrical infrastructure beyond its present capacity, requiring expensive upgrades. This work presents a novel method for minimizing the monthly cost of BEB charging while meeting bus route constraints. This method extends previous work by incorporating a more novel cost model, effects from uncontrolled loads, differences between daytime and overnight charging, and variable rate charging. A graph-based network-flow framework, represented by a mixed-integer linear program, encodes the charging action space, physical bus constraints, and battery state of the charge dynamics. The results for three scenarios are considered: uncontested charging, which uses equal numbers of buses and chargers; contested charging, which has more buses than chargers; and variable charge rates. Among other findings, we show that BEBs can be added to the fleet without raising the peak power demand for only the cost of the energy, suggesting that conversion to electrified transit is possible without upgrading power delivery infrastructure. Full article