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Found 5157 publications
Investigation of Convective and Radiative Heat Transfer of 21700 Lithium-Ion Battery Cells
Publication Name: Batteries
Publication Date: 2025-07-01
Volume: 11
Issue: 7
Page Range: Unknown
Description:
Due to their high energy density and power potential, 21700 lithium-ion battery cells are a widely used technology in hybrid and electric vehicles. Efficient thermal management is essential for maximizing the performance and capacity of Li-ion cells in both low- and high-temperature operating conditions. Optimizing thermal management systems remains critical, particularly for long-range and weight-sensitive applications. In these contexts, passive heat dissipation emerges as an ideal solution, offering effective thermal regulation with minimal additional system weight. This study aims to deepen the understanding of passive heat dissipation in 21700 battery cells and optimize their performance. Special emphasis is placed on analyzing heat transfer and the relative contributions of convective and radiative mechanisms under varying temperature and discharge conditions. Laboratory experiments were conducted under controlled environmental conditions at various discharge rates, ranging from 0.5×C to 5×C. A 3D-printed polymer casing was applied to the cell to enhance thermal dissipation, designed specifically to increase radiative heat transfer while minimizing system weight and reliance on active cooling solutions. Additionally, a numerical model was developed and optimized using experimental data. This model simulates convective and radiative heat transfer mechanisms with minimal computational demand. The optimized numerical model is intended to facilitate further investigation of the cell envelope strategy at the module and battery pack levels in future studies.
Open Access: Yes
Cost Efficiency Evaluation of Ceramic Fiber, Glass Fiber, and Basalt Fiber-Reinforced Asphalt Mixtures
Publication Name: Applied Sciences Switzerland
Publication Date: 2025-07-01
Volume: 15
Issue: 14
Page Range: Unknown
Description:
The performance of SBS (Styrene Butadiene Styrene) modified asphalt mixtures can be enhanced through the addition of fibers including basalt, ceramic, and glass. This study investigates whether a reduced SBS content of 3%, combined with 0.3% fiber reinforcement can match or exceed the performance of a traditional 7% SBS mixture. A comparative analysis was carried out by examining both performance efficiency and life cycle costs across ceramic, basalt, and glass fiber-reinforced mixtures. Maintenance requirements for each scenario were factored into the life cycle analysis. To assess structural integrity, 3D finite element simulations were conducted using the Burger’s logit model while focusing on fatigue and rutting damage. Findings indicate that basalt and ceramic fiber mixtures deliver better asphalt mixtures, thereby outperforming the 7% SBS mix by requiring fewer maintenance interventions. However, due to the higher cost of ceramic fiber mixtures at 831 Eur/m3, basalt fiber emerges as the more cost-effective option, achieving a performance efficiency gain of 20% with reduced costs at 532 Eur/m3. Among the fiber-reinforced variants, glass fiber showed the least improvement in performance, with a difference in 11% and 13% when compared to ceramic fiber and basal fiber, respectively.
Open Access: Yes
DOI: 10.3390/app15147919
Effect of Fermented Feed on Growth Performance and Gut Health of Broilers: A Review
Publication Name: Animals
Publication Date: 2025-07-01
Volume: 15
Issue: 13
Page Range: Unknown
Description:
The fermented feed used in broiler production has gained significant attention for its potential to improve growth performance, enhance gut health, and modulate gut microbiota. This review synthesized findings on the effects of both solid and liquid fermented feed in broilers. Fermentation processes enhance nutrient bioavailability; reduce anti-nutritional factors; and generate beneficial metabolites, such as short-chain fatty acids, which contribute to gut health. Incorporating fermented feed in broiler diets has been shown to improve weight gain, the feed conversion ratio, and nutrient absorption by promoting favorable gut morphology changes, including an increased villus height and villus height-to-crypt depth ratios. Additionally, fermented feed fosters a beneficial microbial environment by increasing lactic acid bacteria populations while reducing pathogenic microbes. Fermentation also modulates gut immunity by regulating cytokine production and stimulating immune cell activity. However, challenges such as inconsistent effects on feed intake and growth during the early production stages underscore the need for optimizing fermentation protocols tailored to broiler production systems. Although the implementation of liquid fermented feed presents logistical challenges, research suggests it can significantly improve feed digestibility. Advances in precision fermentation techniques and multi-strain inoculant use hold promise for further improving fermented feed efficacy. Future research should focus on assessing the long-term impacts, economic viability, and environmental sustainability of fermented feed in commercial poultry systems. Overall, fermented feed offers a promising strategy to enhance productivity and sustainability in broiler farming while reducing the reliance on conventional feed additives. This review reflects the body of knowledge at the time of writing.
Open Access: Yes
DOI: 10.3390/ani15131957
The Impact of Pitch Error on the Dynamics and Transmission Error of Gear Drives
Publication Name: Applied Sciences Switzerland
Publication Date: 2025-07-01
Volume: 15
Issue: 14
Page Range: Unknown
Description:
Gear whine noise is governed not only by intentional microgeometry modifications but also by unavoidable pitch (indexing) deviation. This study presents a workflow that couples a tooth-resolved surface scan with a calibrated pitch-deviation table, both imported into a multibody dynamics (MBD) model built in MSC Adams View. Three operating scenarios were evaluated—ideal geometry, measured microgeometry without pitch error, and measured microgeometry with pitch error—at a nominal speed of 1000 r min−1. Time domain analysis shows that integrating the pitch table increases the mean transmission error (TE) by almost an order of magnitude and introduces a distinct 16.66 Hz shaft order tone. When the measured tooth topologies are added, peak-to-peak TE nearly doubles, revealing a non-linear interaction between spacing deviation and local flank shape. Frequency domain results reproduce the expected mesh-frequency side bands, validating the mapping of the pitch table into the solver. The combined method therefore provides a more faithful digital twin for predicting tonal noise and demonstrates why indexing tolerances must be considered alongside profile relief during gear design optimization.
Open Access: Yes
DOI: 10.3390/app15147851
Exergy-Based Sustainability Assessment of Gold Mining in Colombia: A Comparative Analysis of Open-Pit and Alluvial Mining
Publication Name: Energies
Publication Date: 2025-07-01
Volume: 18
Issue: 13
Page Range: Unknown
Description:
Highlights: Exergy analysis quantifies the sustainability of a process based on the environmental burden generated by using energy resources. Open-pit mining relies on fossil fuels (53%), while alluvial mining is mostly water-dependent (94%) Strategies include improving efficiency, minimizing exergy losses, using renewables, and adopting circular economy principles. Exergy efficiency is improved by reduction in exergy inputs and exergy emissions/waste, i.e., reduction in the loss of useful energy. Findings highlight inefficiencies, guiding resource optimization, and reduced environmental impact. Thermodynamic methods such as exergy analysis enable the evaluation of environmental load (environmental impacts) by quantifying entropy generation and exergy destruction associated with using renewable and non-renewable resources throughout a production system. Based on the principle that environmental impacts occur when exergy is dissipated into the environment, this study applies exergy analysis as a tool for assessing the sustainability of gold mining in Colombia. Two extraction technologies—open-pit and alluvial mining—are evaluated by calculating exergy efficiencies, cumulative exergy demand (CExD), and associated environmental impacts. The results reveal significant differences between the two methods: open-pit mining is heavily dependent on fossil fuels (53% of input exergy), with 99.62% of total exergy destroyed, resulting in an exergy efficiency of just 0.37% and a sustainability index (SI) of 1.00. In contrast, alluvial mining relies predominantly on water (94%), with 69% of input exergy destroyed, an exergy efficiency of 31%, and an SI of 1.46. Four strategies are proposed to reduce environmental burdens: improving efficiency, minimizing exergy losses, integrating renewable energy, and adopting circular economy principles. This study presents the first application of exergy analysis to comprehensively assess the exergy cost of gold production, from extraction through refining, casting, and molding, highlighting critical exergy hotspots and offering a thermodynamic foundation for optimizing resource use in mineral processing.
Open Access: Yes
DOI: 10.3390/en18133247
Performance of Low-Cost Air Temperature Sensors and Applied Calibration Techniques—A Systematic Review
Publication Name: Atmosphere
Publication Date: 2025-07-01
Volume: 16
Issue: 7
Page Range: Unknown
Description:
Low-cost air temperature sensors are an emerging theme in environmental monitoring. These sensors offer the advantage of making microclimate monitoring feasible due to their affordability. However, they are limited by the quality of the data they provide; in many cases, they have been reported to have presented errors in the sensor readings. These errors have been shown to improve after calibration was applied. The lack of a comprehensive understanding of the available calibration techniques, models, and sensor types has led to studies presenting heterogeneity in models and techniques alongside different performance metrics. To address this gap, this study conducted a systematic review following the PRISMA guidelines, reviewing studies from 2015 to 2024 across the databases Web of Science and Scopus, alongside the search engine Google Scholar. The aim was to identify the calibration techniques and models, the commercially available low-cost air temperature sensors used, the performance metrics utilised, and the calibration settings. The findings presented three main categories of calibration models utilised in the collected studies: linear, polynomial, and machine learning. Twenty-two commercially available low-cost sensors were identified, with the DHT22 sensor being the most utilised. Indoor settings were identified as the most preferred for conducting calibrations. Key challenges included limitations in reported results for calibration by the studies, the use of different performance metrics across studies, insufficient studies conducting calibration, and the diversity in sensor types utilised.
Open Access: Yes
Gas Barrier Properties of Organoclay-Reinforced Polyamide 6 Nanocomposite Liners for Type IV Hydrogen Storage Vessels
Publication Name: Nanomaterials
Publication Date: 2025-07-01
Volume: 15
Issue: 14
Page Range: Unknown
Description:
This study investigates the hydrogen permeability of injection-molded polyamide 6 (PA6) nanocomposites reinforced with organo-modified montmorillonite (OMMT) at varying concentrations (1, 2.5, 5, and 10 wt. %) for potential use as Type IV composite-overwrapped pressure vessel (COPV) liners. While previous work examined their mechanical properties, this study focuses on their crystallinity, morphology, and gas barrier performance. The precise inorganic content was determined using thermal gravimetry analysis (TGA), while differential scanning calorimetry (DSC), wide-angle X-ray diffraction (WAXD), and scanning electron microscopy (SEM) were used to characterize the structural and morphological changes induced by varying filler content. The results showed that generally higher OMMT concentrations promoted γ-phase formation but also led to increased agglomeration and reduced crystallinity. The PA6/OMMT-1 wt. % sample stood out with higher crystallinity, well-dispersed clay, and low hydrogen permeability. In contrast, the PA6/OMMT-2.5 and -5 wt. % samples showed increased permeability, which corresponded to WAXD and SEM evidence of agglomeration and DSC results indicating a lower degree of crystallinity. PA6/OMMT-10 wt. % showed the most-reduced hydrogen permeability compared to all other samples. This improvement, however, is attributed to a tortuous path effect created by the high filler loading rather than optimal crystallinity or dispersion. SEM images revealed significant OMMT agglomeration, and DSC analysis confirmed reduced crystallinity, indicating that despite the excellent barrier performance, the compromised microstructure may negatively impact mechanical reliability, showing PA6/OMMT-1 wt. % to be the most balanced candidate combining both mechanical integrity and hydrogen impermeability for Type IV COPV liners.
Open Access: Yes
DOI: 10.3390/nano15141101
Crude oil Price forecasting: Leveraging machine learning for global economic stability
Publication Name: Technological Forecasting and Social Change
Publication Date: 2025-07-01
Volume: 216
Issue: Unknown
Page Range: Unknown
Description:
The volatility of the energy market, particularly crude oil, significantly impacts macroeconomic indices, such as inflation, economic growth, currency exchange rates, and trade balances. Accurate crude oil price forecasting is crucial to risk management and global economic stability. This study examines various models, including GARCH (1,1), Vanilla LSTM, GARCH (1,1) LSTM, and GARCH (1,1) GRU, to predict Brent crude oil prices using different time frequencies and sample periods. The LSTM and GARCH (1,1)-GRU hybrid models showed superior performance, with LSTM slightly better in predictive accuracy and GARCH (1,1)-GRU in minimizing squared errors. These findings emphasize the importance of precise crude oil price forecasting for the global energy market and manufacturing sectors that rely on crude oil prices. Accurate forecasting helps ensure economic sustainability and stability and prevents disruptions to production and distribution chains in both developed and emerging economies. Policymakers may choose to implement energy security measures in response to the significant impact of crude oil price volatility on the macroeconomic indicators. These measures could include maintaining strategic reserves, diversifying energy sources, and decreasing the dependence on volatile oil markets. By doing so, a country's ability to handle oil price fluctuations and ensure a stable energy supply can be enhanced.
Open Access: Yes
Driver Clustering Based on Individual Curve Path Selection Preference
Publication Name: Applied Sciences Switzerland
Publication Date: 2025-07-01
Volume: 15
Issue: 14
Page Range: Unknown
Description:
The development of Advanced Driver Assistance Systems (ADASs) has reached a stage where, in addition to the traditional challenges of path planning and control, there is an increasing focus on the behavior of these systems. Assistance functions shall be personalized to deliver a full user experience. Therefore, driver modeling is a key area of research for next-generation ADASs. One of the most common tasks in everyday driving is lane keeping. Drivers are assisted by lane-keeping systems to keep their vehicle in the center of the lane. However, human drivers often deviate from the center line. It has been shown that the driver’s choice to deviate from the center line can be modeled by a linear combination of preview curvature information. This model is called the Linear Driver Model. In this paper, we fit the LDM parameters to real driving data. The drivers are then clustered based on the individual parameters. It is shown that clusters are not only formed by the numerical similarity of the driver parameters, but the drivers in a cluster actually have similar behavior in terms of path selection. Finally, an Extended Kalman Filter (EKF) is proposed to learn the model parameters at run-time. Any new driver can be classified into one of the driver type groups. This information can be used to modify the behavior of the lane-keeping system to mimic human driving, resulting in a more personalized driving experience.
Open Access: Yes
DOI: 10.3390/app15147718
