Search Results (372)

Large-format pouch cells enable higher pack-level energy density and simplified system architecture, yet they pose significant thermal challenges due to long internal conduction paths, pronounced spatial gradients, and limited access to core temperature. This work develops a high-fidelity electro-thermal model for large-format cells based on an equivalent circuit network that mirrors the physical assembly of tabs, welds, and electrode stacks. The model couples three-dimensional ohmic conduction in tabs, welds, and current collectors with node-level equivalent circuit models in the stack, and uses measurement-anchored parameters. The model is used to study thermally critical design factors for a 44 Ah pouch cell, including thermal management configurations, tab width, tab thickness, and tab welding. Simulation results indicate that among four active cooling options, two-sided stack surface cooling achieves the lowest temperatures and the best uniformity, lowering the average temperature by about 11 °C relative to natural convection and reducing the temperature standard deviation to 1.43 °C. It also decreases the core maximum temperature by more than 9 °C, whereas other configurations provide only 4 to 5 °C core reductions. Changes to tab geometry and welding have minor effects except under one-sided tab cooling. Full article

Peach consumers demand good quality fruit, but premature harvests result in fruit that does not ripen properly and does not reach the required organoleptic quality, so consumers stop buying this product that does not meet their expectations. In our region, peaches are exported long distances, and it is required that when they reach the destination market their quality is adequate. Therefore, the objective of this study was to determine the storage capacity of commercial and delayed harvest in three peach cultivars. ‘Rich Lady’, ‘Summer Lady’, and ‘Merryl O’Henry’ were harvested at commercial maturity (H1) and, a few days later (H2), packed in passive modified atmosphere (PMA), and stored under refrigeration for up to 40 days to simulate marketing to distant markets. During storage and after three days of shelf-life, the physico-chemical characteristics, damage, and sensory quality of the fruit were analyzed. In general, after cold storage, peaches improve their sensory characteristics after three days at room temperature. PMA with refrigeration was suitable for exporting ‘Rich Lady’ peaches overseas for H1. The late harvest, H2, is recommended for ‘Summer Lady’, as it improves sensory quality without losing storability. ‘Summer Lady’ was the best-rated cultivar by the tasters, and ‘Merryl O’Henry’ the worst, due to its lack of ripening and high incidence of chilling injury. Full article

Electric vehicles (EVs) rely on a battery pack as their primary energy source, making it a critical component for their operation. To guarantee safe and correct functioning, a Battery Management System (BMS) is employed, which uses variables such as State of Charge (SOC) to set charge/discharge limits and to monitor pack health. In this article, we propose a Multilayer Perceptron (MLP) network to estimate the SOC of a 14.8 V battery pack installed in a robotic vacuum cleaner. Both offline and online (real-time) tests were conducted under continuous load and with rest intervals. The MLP’s output is compared against two commonly used approaches: NARX (Nonlinear Autoregressive Exogenous) and CNN (Convolutional Neural Network). Performance is evaluated via statistical metrics, Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE), and we also assess computational cost using Operational Intensity. Finally, we map these results onto a Roofline Model to predict how the MLP would perform on an automotive-grade microcontroller unit (MCU). A generalization analysis is performed using Transfer Learning and optimization using MLP–Kalman. The best performers are the MLP–Kalman network, which achieved an RMSE of approximately 13% relative to the true SOC, and NARX, which achieved approximately 12%. The computational cost of both is very close, making it particularly suitable for use in BMS. Full article

The dual-rotor in-wheel motor (DRIWM) drive electric vehicle has multiple braking modes. Determining how to select the most suitable braking mode for the current driving conditions and dynamically allocate the regenerative braking torque of the inner and outer motors is the key to achieving maximum energy recovery. On the basis of regenerative braking characteristic analyses of the DRIWM, the switching rules of the vehicle braking modes were designed based on the optimal system efficiency, and the specific working ranges of various braking modes were determined. According to the efficiency characteristics of the inner and outer motors, a regenerative braking torque allocation strategy based on the principle of maximizing the system energy recovery was proposed in the dual-motor coupled regenerative braking mode. The simulation results show that, during the entire CLTC-P cycle condition, the three regenerative braking modes of the DRIWM can effectively recover braking energy within their designed working ranges. Moreover, both the inner motor and outer motor can operate at the best efficiency when they undertake the optimal braking torque to achieve the maximum braking energy recovery. The experimental results show that a variable voltage charging scheme for the DRIWM is adopted, which can further ensure that both the inner and outer motors can simultaneously store energy with the maximum efficiency to the power battery pack. Full article

This research seeks to model a packed bed with cocoa waste on an industrial scale using computer software and parametric evaluation to remove Pb(II) in solution. To achieve this, they developed multiple simulations of a packed bed using Aspen Adsorption software using different configurations of inlet flow rate and bed height through a parametric sensitivity study to evaluate the system performance using Langmuir as an isothermal model and the Linear Driving Force (LDF) model as a kinetic model. It was found that the efficiency of the adsorption process reached 99.7% for Pb(II) removal. On the other hand, the best simulation conditions considering efficiency, breakthrough time and saturation were a flow rate of 200 m³/day, a head of 5 m and an initial concentration of 1000 mg/L. This research exhibits a novel engineering perspective to anticipate the potential performance of packed bed with agro-industrial biomasses in the multiscale removal of Pb(II). Full article

Current state-of-the-art (SoTA) instance segmentation models often struggle to accurately segment small and densely distributed vessels. In this study, we introduce MAKSEA, a new satellite imagery dataset collected from the Makkoran Coast that contains small and overlapping vessels. We also propose an efficient and robust segmentation architecture, namely MVSegNet, to segment small and overlapping ships. MVSegNet leverages three modules on the baseline UNet++ architecture: a Multi-Scale Context Aggregation block based on Atrous Spatial Pyramid Pooling (ASPP) to detect vessels with different scales, Attention-Guided Skip Connections to focus more on ship relevant features, and a Multi-Head Self-Attention Block before the final prediction layer to model long-range spatial dependencies and refine densely packed regions. We evaluated our final model with SoTA instance segmentation architectures on two benchmark datasets including LEVIR_SHIP and DIOR_SHIP as well as our challenging MAKSEA datasets using several evaluation metrics. MVSegNet achieves the best performance in terms of F1-Score on LEVIR_SHIP (0.9028) and DIOR_SHIP (0.9607) datasets. On MAKSEA, it achieves an IoU of 0.826, improving the baseline by about 7.0%. The extensive quantitative and qualitative ablation experiments confirm that the proposed approach is effective for real-world maritime traffic monitoring applications, particularly in scenarios with dense vessel distributions. Full article

Efficient packing of irregular mechanical parts in limited container space is essential for reducing transportation and storage costs in automated manufacturing. This study focuses on eccentric-shaped parts characterized by geometric asymmetry, multiple orientations, and local irregularities, and proposes a two-stage three-dimensional packing strategy. In the first stage, an optimal single-layer layout is generated using a heuristic algorithm that combines grid scanning with a gravity-drop principle and tabu search to optimize part positions and orientations. In the second stage, the optimized layer template is vertically replicated with buffer layers to enhance stacking stability, ensuring feasible and non-overlapping arrangements. Comparative experiments with Best Fit, BLF, LHL, and Random methods show that the proposed approach increases average space utilization by 8.3%, 8.8%, 8.1%, and 15.5%, respectively, while maintaining high stability and reasonable computation time. The results demonstrate that this method achieves dense and stable packing, offering an effective solution for intelligent packing and automated production of irregular parts. Full article

Komagataeibacter species are the best producers of bacterial nanocellulose membranes (BNC)—amazing biomaterial with unique properties and applications in the medical and food industries. The molecular mechanisms of BNC synthesis control remain poorly understood and the need for BNC production and structure improvement is growing. Looking for the genes significant for biosynthesis, we studied the unexplored effect of ClpP proteolytic subunit inactivation on Komagataeibacter xylinus E₂₅ cell morphology and production of BNC. A mutant with a disrupted clpP gene and a complemented strain were obtained. The colonies of the mutant cells, in contrast to the wild-type and complemented ones, were smaller, irregular, and were surrounded by a polymeric noncellulosic envelope. Additionally, the mutant cells were longer and organized in chains, showing different growth and production dynamics of BNC when grown under standard conditions. We also observed worse growth and production of BNC at 5 °C above optimal temperature and in the presence of increased levels of ethanol. E₂₅ mutant cells were characterized by lower viability under stress conditions. The 3D microstructure of BNC displayed thicker fibers and denser packing and contained more hard-to-extract exopolysaccharides (HE-EPSs). Based on the outcomes, we conclude that the effect of ClpP on K. xylinus decreased resistance to stress and lowered the BNC production level. Full article

This review investigates how cell form factors (cylindrical, prismatic, and pouch) and electrode architecture (jelly-roll, stacked, and blade) influence the performance, safety, and manufacturability of lithium-ion batteries (LIBs) across the main commercial chemistries LiFePO₄ (LFP), Li (NiMnCo)O₂ (NMC), LiNiCoAlO₂ (NCA), and LiCoO₂ (LCO). Literature, OEM datasheets, and teardown analyses published between 2015 and 2025 were examined to map the interdependence among geometry, electrode design, and electrochemical behavior. The comparison shows trade-offs among gravimetric and volumetric energy density, thermal runaway tolerance, cycle lifespan, and cell-to-pack integration efficiency. LFP, despite its lower nominal voltage, offers superior thermal stability and a longer cycle life, making it suitable for both prismatic and blade configurations in EVs and stationary storage applications. NMC and NCA chemistries achieve higher specific energy and power by using jelly-roll architectures that are best suited for tabless or multi-tab current collection, enhancing uniform current distribution and manufacturability. Pouch cells provide high energy-to-weight ratios and flexible packaging for compact modules, though they require precise mechanical compression. LCO remains confined to small electronics owing to safety and cost limitations. Although LFP’s safety and affordability make it dominant in cost-sensitive applications, its low voltage and energy density limit broader adoption. LiMnFePO₄ (LMFP) cathodes offer a pathway to enhance voltage and energy while retaining cycle life and cost efficiency; however, their optimization across various form factors and electrode architecture remains underexplored. This study establishes an application-driven framework linking form factors and electrode design to guide the design and optimization of next-generation lithium-ion battery systems. Full article

Metal–Organic Frameworks (MOFs) have diverse applications due to their tunable porosity, large surface area, and diverse chemical functionalities. Among them, one of the most researched MOFs is MIL-101(Cr), which, in addition, is very stable in water. We have used a commercially available substance with approximately 300 nm large crystals for the preparation of a sensing nano-thin layer for the emerging water contaminant PFOS, due to its high selectivity towards this compound. Here, we have synthesized 20 nm sized crystals of MIL-101(Cr), which are among the smallest reported, and compared them to the same material with 300 nm sized crystals. The material was characterized by TEM and XPS. It was possible to prepare insoluble monolayers at the air–water interface (Langmuir films), which were characterized with film compression isotherms, Brewster angle microscopy, and surface potential measurements. The Langmuir–Blodgett (LB) method was used to deposit monolayers on Si wafers and 434 MHz Surface Acoustic Wave resonator simultaneously. The LB layers were very stable over time. The smaller-sized MIL-101 (Cr) crystals exhibit denser, more homogeneous water coverage and packing upon compression, with no observable 10–100 µm aggregates. LB monolayers from the 20 nm particles have approximately six times lower surface roughness. The LB monolayer is far from being smooth, but this will allow excellent access to the MOF pores by the tested analyte in a chemical sensing application. The lack of research on depositing presynthesized MOFs using probably the best method for nanoarchitectonics—the LB method—is addressed. The 20 nm sized MOF crystals are the smallest deposited by this method so far. Full article

Loquat fruit is valued for its pleasant taste and favorable ripening period. However, its delicate texture and high perishability make it highly vulnerable to damage during packaging, so the fruit is usually packed by hand. Developing a fruit-sizing machine could increase commercial market opportunities. Automated mass detection reduces manual sorting errors and labor requirements. Overall, it enhances grading accuracy, speed, and uniformity in loquat processing. It also helps distinguish between ripe, underripe, and overripe fruits through subtle mass differences. Mass modeling has proven to be an effective baseline approach for the development and optimization of grading machines, and its efficiency has been demonstrated across different fruit types. Here, we present a comparative analysis of various models for mass modeling of six international and Italian loquat varieties (“Algerie,” “Peluche,” “Golden Nugget,” “Virticchiara,” “Nespolone di Trabia,” and “Claudia”) cultivated in southern Italy. On fifty fruits per variety, singular mass and spatial diameters [longitudinal (DL), maximum transverse (DT1), and minimum transverse (DT2) were measured. Linear and non-linear regression analyses, including quadratic, polynomial, and cubic models, were applied to both the complete dataset and individual varieties. A set of predictors was used, including DL (length), DT1 (width), and DT2 (thickness), ellipsoid and oblate spheroid volume. Model performance was evaluated based on higher R² values, and lower RMSE and MBE values. The best general model was obtained using an ellipsoidal volume (R² = 0.97, RMSE = 2.76). Both linear and cubic models demonstrated high suitability across all varieties, with ellipsoidal volume emerging as the most effective predictor. Conversely, (DL) based models were the least suitable, yielding the lowest (R² = 0.41) values in “Virticchiara.” The developed general and specific-variety models and equations provide a solid foundation for establishing high-performance systems for mass and size estimation, which can be effectively integrated into a fruit sizer machine. Full article

The transition to electric aircraft for zero-emission transport requires integrating thermal management systems for high-performance batteries without incurring significant weight, balance, or aerodynamic penalties. This study focuses on the aerodynamic penalties associated with air-cooling systems that can compound the presently unavoidable reduction in endurance imposed by current battery energy density limitations. Building on previous research into battery installation layouts and internal cooling flows, this study is the first to investigate the lift-to-drag (L/D) optimisation for the multiple wing-mounted inlets and outlets necessary for air-cooling batteries in the wing of an electrified aircraft. Wing leading-edge inlets and NACA (National Advisory Committee for Aeronautics) ducts were analysed by systematically varying their layout, number, and dimensions. The analysis evaluated their effects on the wing’s lift, drag, and moment to maximise the L/D. Multiple highly efficient simulation test designs were developed to screen for the main factors to identify the best inlet and outlet configuration, resulting in 66 different Computational Fluid Dynamics (CFD) simulations in Ansys Fluent. Following this, three CFD verification cases of the best configuration were conducted to verify the cooling effect by combining both internal and external flow simulations with heat generation. Compared to the baseline wing of the carbon combustion aircraft, the best configuration caused a 1.75% reduction in L/D, range, and endurance. While the aerodynamic penalty is now minimised, the internal battery pack layout requires further optimisation to re-establish uniform cooling across the battery pack. Designers may still be able to separate the CFD analysis of the internal and external flow regimes with idealised inlets and outlets; however, more whole-field CFD iterations are needed to guide such subdivision to a viable and safe design for wing-mounted batteries. Further, the margins are such that wing-mounted electrification warrants careful instrumented validation in an aircraft. These findings provide crucial design guidance for sustainable aviation, particularly to enable after-market electrification projects. Full article

This work explores the thermal management of cylindrical lithium-ion batteries used in electric vehicles by introducing a combined cooling approach that couples phase-change materials (PCM) with a liquid-based cooling loop. Fluent-based numerical simulations are conducted to first examine the effects of battery spacing and ambient temperature on PCM cooling performance, from which the optimal spacing is identified. Building on this foundation, a coupled PCM–liquid cooling model is developed to evaluate the impacts of liquid-channel inlet configuration, coolant flow velocity, and inlet temperature. Results show that varying the inlet position has little impact when the outlet is fixed. Increasing coolant velocity lowers the peak cell temperature and the extent of PCM melting but enlarges the temperature difference, reaching 5.03 °C at 0.0075 m/s, which exceeds the recommended safety threshold. Lowering the coolant inlet temperature further decreases the peak temperature but also deteriorates temperature uniformity. To simultaneously suppress both the maximum temperature (T_maxi) and temperature gradient, two structural optimization schemes are proposed. Among them, distributing liquid cooling plates evenly above and below the battery pack achieves the best overall performance. The findings demonstrate the strong cooling potential of the PCM–liquid hybrid system and offer theoretical support for the design and optimization of advanced battery thermal management systems. Full article

The growing accumulation of glass waste and the limited availability of natural aggregates present major challenges for sustainable road construction. This study aimed to evaluate the influence of the glass cullet content (GC) in the range of 0–30% on the mechanical and compaction properties of cement-bound granular mixtures (CBGM 31.5 mm, R_c class C_5/6) intended for the road base and subbase layers. Laboratory tests were carried out to analyze the effect of GC on the optimum moisture content (OMC), the maximum dry density (ρ_d,max), and the compressive strength after 7 and 28 days (R₇, R₂₈). The results showed a systematic decrease in OMC and ρ_d,max with increasing GC content, by approximately 18% and 2.8%, respectively, for the mixture containing 30% glass. All CBGM mixtures met the strength requirements for class C_5/6 (R_c = 6–10 MPa), with the highest value of R28 obtained for the mixture containing 20% GC (9.4 MPa), representing a 24% increase compared to the reference mix. The relationship between GC content and compressive strength was best described by a second-degree polynomial function (R² = 0.60–0.65), indicating an optimum within the 10–20% range. Strength enhancement was attributed to synergistic effects of physical mechanisms (filler effect and improved particle packing) and chemical activity (pozzolanic reactivity of fine glass fractions). The 30% GC mixture provided the minimum required strength while achieving the highest level of waste utilization and environmental benefit. Therefore, the optimal GC content should be determined as a balance between mechanical performance and sustainable use of secondary materials in the temperate climatic conditions of Central Europe. Full article

The problem of packing multidimensional spheres in a container defined by a hyperbolic surface is introduced. The objective is to minimize the height of the hyperbolic container under non-overlapping and containment conditions for the spheres, considering minimal allowable distances between them. To the best of our knowledge, no mathematical models addressing optimized packing spheres in hyperbolic containers have been proposed before. Our approach is based on a space dimensionality reduction transformation. This transformation relies on projecting a multidimensional hyperboloid into a lower-dimensional space sequentially up to two-dimensional case. Employing the phi-function technique, packing spheres in the hyperbolic container is formulated as a nonlinear programming problem. The latter is solved using a model-based heuristic combined with a decomposition approach. Numerical results are presented for a wide range of parameters, i.e., space dimension, number of spheres, and metric characteristics of the hyperbolic container. The results demonstrate efficiency of the proposed modeling and solution approach highlighting new opportunities for packing problems within non-traditional geometries. Full article