Search Results (3,780)

In this study, the cooling performance of fuel cell electric vehicles (FCEVs) with regard to thermal derating is investigated. Particularly in hot climate conditions, low operating temperature of the fuel cell stack and hence low temperature difference to the environment can result in thermal derating of the fuel cell stack. Experimental investigations on a production vehicle with a fuel cell drive (Hyundai Nexo) are conducted to analyze the influence of climatic boundary conditions and a dynamic driving scenario on the thermal management system of the vehicle. Therefore, a new method based on energy balances is introduced to indirectly measure the average cooling air velocity at the cooling module. The results indicate that the two high-power radiator fans effectively maintain a high cooling airflow between a vehicle speed of approximately 30 and 100 $\mathrm{k}\mathrm{m}/\mathrm{h}$, leading to efficient heat rejection at the cooling module largely independent of vehicle speed. Furthermore, this study reveals that the efficiency of the fuel cell system is notably affected by ambient air temperature, attributed to the load on the electric air compressor (EAC) as well as on cooling system components like cooling pump and radiator fans. However, at the stack level, balance of plant (BoP) components demonstrate the ability to ensure ambient temperature-independent performance, likely due to reliable humidification control up to 45 ${}^{\circ }$C. Additionally, a new method for determining thermal derating of FCEVs on roller dynamometer tests is presented. A real-world uphill drive under ambient temperatures exceeding 40 ${}^{\circ }$C demonstrates derating occurring in 6.3 of the time, although a worst case with an aged stack and high payload is not investigated in this study. Finally, a time constant of 50 $\mathrm{s}$ is found to be suitable to correlate the average fuel cell stack power with a coolant temperature at the stack inlet, which gives information on the thermal inertia of the system observed and can be used for future simulation studies. Full article

Phytoplankton size classes (PSC), which categorize phytoplankton into pico- (<2 µm), nano- (2–20 µm), and microphytoplankton (>20 µm), have been widely used to describe functional group responses to environmental variability. Distribution of PSCs heavily influences marine ecosystems and biogeochemical processes. Despite the importance of PSC distributions, especially in the face of climate change, long-term studies on PSC variability and its driving factors are lacking. This study aimed to identify the key environmental drivers affecting summer PSC variability in the northern East China Sea (NECS) by analyzing 27 years (1998–2024) of satellite-derived data. Statistical analyses using random forest and multiple linear regression models revealed that euphotic depth (Z_eu) and suspended particulate matter (SPM) were the primary factors influencing PSC variation; deeper Z_eu values favored smaller picophytoplankton, whereas higher SPM concentrations supported larger PSCs. Long-term trend analysis showed a clear shift toward increasing picophytoplankton contributions (+2.4% per year), with corresponding declines in nano- and microphytoplankton levels (2.2% and 0.4% annually, respectively). These long-term changes are hypothesized to result from a persistent decline in SPM concentrations, which modulate light attenuation and nutrient dynamics in the euphotic zone. Marine heat waves intensify these shifts by promoting picophytoplankton dominance through enhanced stratification and reduced nutrient availability. These findings underscore the need for continuous monitoring to inform ecosystem management and predict the impacts of climate change in the NECS. Full article

Background\Objectives: The aim of this study was to investigate the effects of periodontal blood flow on the periapical region during various endodontic disinfection procedures. The hypothesis that periodontal blood flow reduces the increase in root surface temperature during disinfection procedures was tested. Methods: One hundred and twenty extracted human teeth were shortened to 11 mm and the root canal was prepared using the F4 ProTaper Gold system. The specimens were covered with wax and then sealed in a thermoforming sheet, leaving a gap of 0.2 mm. Cannulas were attached to simulate stable fluid circulation. Thermographic evaluation was carried out using an infrared camera. The following methods were chosen for disinfection: I, λ445 nm diode laser (0.6 W, cw); II, λ445 nm diode laser, 3 W, pulsed, duty cycle 50%, 10 Hz; III, λ445 nm diode laser, 3 W, pulsed, duty cycle 75%, 10 Hz; IV, λ970 nm diode laser, 2 W, pulsed, duty cycle 50%, 10 Hz; V, λ970 nm diode laser, 2 W, pulsed, duty cycle 75%, 10 Hz; VI, experimental plasma device (2.5 W, 3.7 V); VII, heat plugger (200.0 °C); VIII, NaOCl 3% (60 °C). The results were analyzed statistically using the Kruskal–Wallis test. When there were significant differences between the groups (p < 0.05), the pairwise Mann–Whitney test with sequential Bonferroni correction was applied. Results: The smallest temperature changes, with a median value of 0.82 °C (max. 2.02 °C, min. 0.15 °C, IQR 0.87 °C), were observed using the laser at a setting of λ445 nm, 0.6 W cw, and a circulation rate of 6 mL/min. The highest temperature changes were measured at a fluid circulation rate of 0 mL/min with a laser setting of λ445 nm, 3 W, pulsed, duty cycle 75% with a median value of 21.7 °C (max. 25.02 °C, min. 20.29 °C, IQR 2.04 °C). Conclusions: Disinfection procedures with laser, NaOCl, and an experimental plasma device can lead to an increase in root surface temperature. With the exception of the heat plugger, no significant temperature changes were observed. This study was conducted in vitro, which may limit the direct applicability of the results to clinical scenarios. Nevertheless, the simulation of blood flow showed a thermally protective effect, suggesting that clinical protocols should consider this variable when selecting thermal disinfection methods. These results support the hypothesis that periodontal blood flow may have a potentially positive influence on temperature changes during disinfection procedures. Full article

Temperature is a critical factor affecting the development and population dynamics of many organisms. An organism’s ability to withstand extreme temperature events, such as heat waves, will become increasingly important as the severity, duration, and frequency of these events continue to rise worldwide due to global warming. Knowledge on the effects of heat stress on both pests and their natural enemies will thus be crucial for keeping biological control and pest control programs effective in future. This research aimed to study the effect of short-term heat stress on the predatory mite Phytoseiulus persimilis, which is one of the important natural enemies utilized as a biocontrol agent against spider mites such as Tetranychus urticae. The experiments assessed the immature developmental time of P. persimilis after a four-hour incubation of eggs at high temperatures, namely 36, 38, 40, and 42 °C, as well as 85 ± 5% RH and a 16:8 h photoperiod (L:D). After adult females emerged, they were exposed to the same conditions again and the population parameters were monitored. The results demonstrated that the immature development time decreased as temperature increased, with the shortest development duration of 5.30 days seen in eggs exposed to 40 °C, while the eggs exposed to 42 °C did not hatch. Female and male adult longevity decreased significantly as the temperature increased. Fecundity, the adult pre-ovipositional period, and the total pre-ovipositional period were lowest following the 40 °C treatment. The population parameters of P. persimilis, including r and λ, reached their highest values in mites treated at 36 °C, and were significantly higher than in the control group. Addressing these challenges through targeted research and adaptive management is essential to sustaining the efficiency of P. persimilis in biocontrol programs, particularly in the context of global climate change. Full article

The decommissioning of the Zion Nuclear Power Plant (NPP) provided a unique opportunity to harvest and study service-aged reactor pressure vessel (RPV) beltline materials. This work, conducted through the U.S. Department of Energy’s Light Water Reactor Sustainability (LWRS) Program, aims to improve the understanding of radiation-induced embrittlement to support extended nuclear plant operations. Material segments containing the Linde 80 flux, wire heat 72105 (WF-70) beltline weld and the A533B Heat B7835-1 base metal, obtained from the intermediate shell region with a peak fluence of 0.7 × 10¹⁹ n/cm² (E > 1.0 MeV), were extracted, cut into blocks, and machined into test specimens for mechanical and microstructural characterization. The segmentation process involved oxy-propane torch-cutting, followed by precision machining using wire saws and electrical discharge machining (EDM). A chemical composition analysis confirmed the expected variations in alloying elements, with copper levels being notably higher in the weld metal. The harvested specimens enable a detailed evaluation of through-wall embrittlement gradients, a comparison with the existing surveillance data, and the validation of predictive embrittlement models. This study provides critical data for assessing long-term reactor vessel integrity, informing aging-management strategies, and supporting regulatory decisions to extend the life of nuclear plants. This article is a revised and expanded version of a paper entitled, “Current Status of the Characterization of RPV Materials Harvested from the Decommissioned Zion Unit 1 Nuclear Power Plant”, PVP2017-65090, which was accepted and presented at the ASME 2017 Pressure Vessels and Piping Conference, Waikoloa, HI, USA, 16–20 July 2017. Full article

Efficient and accurate grey-box building models, including water-based heating and cooling systems, are crucial for simulating and optimizing the energy demand of building, neighborhood, and network scenarios. However, the numerical effort and the amount of input data required for existing models are still high, and the parameterization of these systems is very labor-intensive. This paper presents a grey-box model that addresses these limitations by requiring minimal input data and offering a highly efficient parameterization method. Using physical principles, the model was validated against a detailed physical building model and measurement data. Our results show that the grey-box model accurately predicts return temperatures (σ = 0.37 K, µ = 0.05 K) and room air temperatures (σ = 0.62 K, µ = 0.28 K). Compared to 8229 s for the detailed physical model, the model requires only 18 s for a one-year simulation. The model also shows robust behavior with alternative weather data and control strategies. The key contribution of this work is the development of a grey-box model that combines high accuracy and numerical efficiency with significantly reduced data and parameterization requirements, with possible applications in large-scale building simulations, demand-side management, short-term energy storage strategies, and model predictive control. Full article

With the rapid growth of the global population, increasing per capita energy demands, and waste generation, the need for innovative strategies to mitigate greenhouse gas emissions and effective waste management has become paramount. Pyrolysis, a thermochemical conversion process, facilitates the transformation of diverse biomass feedstocks, including agricultural biomass, forestry waste, and other carbonaceous wastes, into valuable biofuels such as bio-oil, biochar, and producer gas. The article reviews the benefits of pyrolysis as an effective and scalable technique for biofuel production from waste biomass. The review describes the different types of pyrolysis processes, such as slow, intermediate, fast, and catalytic, focusing on the effects of process parameters like temperature, heating rate, and residence time on biofuel yields and properties. The review also highlights the configurations and operating principles of different reactors used for pyrolysis, such as fixed bed, fluidized bed, entrained flow, plasma system, and microwaves. The review examines the factors affecting reactor performance, including energy consumption and feedstock attributes while highlighting the necessity of optimizing these systems to improve sustainability and economic feasibility in pyrolysis processes. The diverse value-added applications of biochar, bio-oil, and producer gas obtained from biomass pyrolysis are also discussed. Full article

This study introduced and evaluated a new Carbon Nanotube (CNT) sheet-based method for battery temperature management, aimed at enhancing the performance of Li-ion batteries in subzero environments. This method addressed critical challenges such as startup failures, capacity loss, and the poor performance of the Li-ion battery in extreme cold conditions, particularly for industrial applications like forklifts operating at temperatures as low as −30 °C. Without CNT heating, the battery performance dropped significantly in low-temperature environments. At −20 °C, the battery delivered only 63.4% of its capacity, with minimal self-heating. At −30 °C, it failed almost entirely, shutting down after just 45 s. In contrast, CNT heating greatly enhanced performance. The CNT sheet quickly warmed the battery to 0 °C—within 97 s at −20 °C and 141 s at −30 °C—allowing it to recover up to 90% of its capacity. These improvements resulted in enhanced capacity and energy output compared to batteries without CNT heating, which suffered from severe performance losses, including a negligible capacity and energy output under −30 °C. It can be concluded that the CNT sheet-based approach provides superior thermal conductivity, rapid heating, and exceptional energy conversion efficiency, enabling extended battery life and enhanced operational reliability in subzero environments. Its scalability and affordability position it as a transformative innovation for industrial applications reliant on efficient battery performance in extreme cold environments. Full article

Integrating building information modeling (BIM) with Internet of things (IoT) technologies significantly enhances facility management (FM) by enabling advanced real-time monitoring of indoor environmental quality (IEQ). However, technical complexity, proprietary limitations, high software costs, and unclear long-term benefits hinder practical adoption. This study suggests a way to combine BIM and IoT using open standards like IFC and JSON, simple programming tools like Node-RED, and secure cloud services. A case study of a six-story office building showed that real-time IEQ sensor data can be combined with organized BIM information, helping to make better decisions about maintaining, replacing, or upgrading heating, ventilation, and air conditioning (HVAC) systems. This integration offers essential data needed for using advanced analysis techniques, specifically tackling issues with compatibility, ease of use, and organizational challenges, which is especially advantageous for small-to-medium-sized office buildings. Nevertheless, this study faced limitations due to restricted real-time data access from existing building management systems and preliminary predictive analytic capabilities, highlighting a need for improved direct data integration and robust analytical methods in future implementations. Full article

Heat exchangers are critical components in various industrial applications, requiring efficient thermal management to enhance thermal performance and energy efficiency. Longitudinal vortex generators (LVGs) have emerged as a potent mechanism to enhance heat transfer within these devices. A precise knowledge of the thermal performance enhancement of HE through LVGs is missing in the literature. Therefore, this study aims to provide a critical review of both numerical simulations and experimental studies focusing on the enhancement of heat transfer through LVGs to further enhance the knowledge of the field. It begins with elucidating the fundamental principles behind LVGs and delineating their role in manipulating flow patterns to augment heat transfer. This is followed by an exploration of the various numerical methods employed in the field, including computational fluid dynamics techniques such as Reynolds-Averaged Navier–Stokes (RANS) models, Large Eddy Simulation (LES), and Direct Numerical Simulation (DNS). Various experimental methods are then summarised, including differential pressure measuring instruments, temperature measurements, velocity measurements, heat transfer coefficient measurements, and flow visualisation techniques. The effectiveness of these methods in capturing the complex fluid dynamics and thermal characteristics induced by LVGs is critically assessed. The review covers a wide range of LVG configurations, including their geometry, placements, and orientations, and their effects on the thermal performance of heat exchangers. Different from previous reviews that mainly focus on classical configurations and historical studies, this review also emphasizes recent developments in computational fluid dynamics and progress in interdisciplinary fields such as innovative materials, additive manufacturing, surface finishing, and machine learning. By bridging the gap between fluid dynamics, thermal enhancement, and emerging manufacturing technologies, this paper provides a forward-looking, comprehensive analysis that is valuable for both academic and industrial innovations. Full article

An urban heat island (UHI) refers to urban areas that experience higher temperatures due to heat absorption and retention by impervious surfaces compared to the surrounding rural areas. Urban wetlands are crucial in mitigating the UHI effect and improving climate resilience via their cooling effect. This study examines Colombo, Sri Lanka, the RAMSAR-accredited wetland city in South Asia, to assess the cooling effect of urban wetlands based on 2023 dry season data for effective sustainable management. We used Landsat 8 and 9 data to create Land Use/Cover (LUC), Land Surface Temperature (LST), and surface-reflectance-based maps using the Google Earth Engine (GEE). The Enhanced Vegetation Index (EVI), Modified Normalized Difference Water Index (mNDWI), topographic wetness, elevation, slope, and impervious surface percentage were identified as the influencing variables. The results show that urban wetlands in Colombo face tremendous pressure due to rapid urban expansion. The cooling intensity positively correlates with wetland size. The threshold value of efficiency (TVoE) of urban wetlands in Colombo was 1.42 ha. Larger and more connected wetlands showed higher cooling effects. Vegetation- and water-based wetlands play an important role in <10 km urban areas, while more complex shape configuration wetlands provide better cooling effects in urban and peri-urban areas due to edge effects. Urban planners should prioritize protecting wetland areas and ensuring hydrological connectivity and interconnected wetland clusters to maximize the cooling effect and sustain ecosystem services in rapidly urbanizing coastal cities. Full article

Effective health management during the transition period depends on early disease detection, which can be achieved through continuous monitoring using precision livestock farming tools. This study assessed reticulorumen temperature, rumination time, and activity in dairy cows during the periparturient period under summer heat stress. We hypothesized differences in these parameters between healthy (HE) cows and those developing postpartum disorders (DI). Forty clinically healthy, multiparous cows were monitored from 5 days prepartum to 14 days after calving (days in milk; DIM). A cow was considered healthy and allocated to the HE group (n = 26) if she was not affected by any postpartum health disorders until the end of the study period. A cow was considered diseased and allocated to the DI group (n = 14) if she had been diagnosed with mastitis, metritis, lameness, or ketosis. Weather loggers recorded barn microclimate data, while rumination, activity, and rumen temperature were tracked using a microphone-based sensor in the neck collar (Ruminact HR) and rumen bolus (Smaxtec). THI values remained above 68 throughout the study, peaking at 80, indicating sustained heat stress. Rumen temperature ranged between 39 and 41 °C and moderately correlated with THI (correlation coefficient was 0.27; 95% CI: 0.20; 0.33; p < 0.0001). Both groups exhibited a nadir in rumen temperature at calving, with no differences. Rumination time declined prepartum, reaching its lowest at 2 DIM in DI cows. It was significantly affected by days around calving, postpartum disorders, and THI. Activity increased prepartum and normalized by 4 DIM in HE cows, while DI cows showed higher activity at 4 DIM, stabilizing by 5–7 DIM. These findings underscore the value of precision monitoring tools for early disease detection and intervention. Full article

Anaerobic digestion (AD) offers a sustainable solution by treating biodegradable waste while recovering bioenergy, enhancing the share of renewable energy. Thus, this study aims to investigate the AD for managing and valorizing residues from the potato chip industry: potato peel (PP), potato offcuts (OC), waste cooking oil (WCO), wastewater (WW), and sewage sludge (SS). In particular, the biochemical methane potential (BMP) of each residue, anaerobic co-digestion (AcoD), and greenhouse gas (GHG) emissions of an AD plant are assessed. WW, OC, and SS present a BMP of around 232–280 NmL_CH4/kg of volatile solids (VS). PP and WCO reach a BMP slightly lower than the former substrates (174–202 NmL_CH4/g_VS). AcoD results in methane yields between 150 and 250 NmL_CH4/g_VS. An up-scaled anaerobic digester is designed to manage 1.60 Mg/d of PP. A residence time of 12 days and a digester with 165 m³ is estimated, yielding 14 Nm³_CH4/Mg_VS/d. A simulated AD plant integrated with a combined heat and power unit results in a carbon footprint of 542 kg of CO₂-eq/Mg_db PP, primarily from biogenic GHG emissions. These findings highlight the potential of AD to generate renewable energy from potato industry residues while reducing fossil fuel-related GHG emissions and promoting resource circularity. Full article

In this research, we present the development and validation of a compact, resource-efficient (low-cost, low-energy), distributed, real-time traffic and air quality monitoring system. Deployed since November 2023 in a small town that relies on burning various fuels and waste for winter heating, the system comprises three IoT units that integrate image processing and environmental sensing for sustainable urban and environmental management. Each unit uses an embedded camera and sensors to process live data locally, which are then transmitted to a central database. The image processing algorithm counts vehicles by type with over 95% daylight accuracy, while air quality sensors measure pollutants including particulate matter (PM), equivalent carbon dioxide (eCO₂), and total volatile organic compounds (TVOCs). Data analysis revealed fluctuations in pollutant concentrations across monitored areas, correlating with traffic variations and enabling the identification of pollution sources and their relative impacts. Recorded PM10 daily average levels even reached eight times above the safe 24 h limits in winter, when traffic values were low, indicating a strong link to household heating. This work provides a scalable, cost-effective approach to traffic and air quality monitoring, offering actionable insights for urban planning and sustainable development. Full article

This paper investigates the coupled relationship between solid-phase temperature fields and droplet evaporation, focusing on the effects of substrate thermal conduction properties on droplet evaporation behavior. A mathematical model is developed to analyze the impacts of substrate thermal conductivity, thickness, and lower-surface temperature on evaporation rate, surface temperature, and evaporation flux. A dimensionless relative evaporation rate (HCs) is introduced to characterize the influence of substrate thermal conduction. Results show that increasing substrate thermal conductivity enhances droplet surface temperature and evaporation flux, thereby monotonically increasing evaporation rate until it approaches the rate of the evaporative cooling model. Conversely, increasing substrate thickness lengthens the heat transfer path, reducing heat conducted to the solid–liquid interface and decreasing evaporation rate. Changes in substrate lower-surface temperature significantly affect evaporation rate, but HCs remains nearly unaffected. The concept of equivalent substrates is proposed and verified through dimensionless analysis and simulations. It is found that different combinations of substrate thickness and thermal conductivity exhibit consistent effects on droplet evaporation, with minimal relative errors in evaporation rate and total heat transfer at the solid–liquid interface. This confirms the existence of the equivalent substrate phenomenon. Additionally, the effects of droplet properties, such as contact angle and evaporative cooling coefficient (Ec), on the equivalent substrate phenomenon are explored, revealing negligible impacts. These findings provide theoretical guidance for optimizing droplet evaporation processes in practical applications, such as micro/nanoscale thermal management systems. Full article