Search Results (1,962)

In battery systems, external mechanical compression is commonly applied to pouch/prismatic cells to improve their electrical performance and mechanical integrity. However, cell clamping can hinder system heat rejection by introducing an additional thermal insulation layer. A novel battery clamping scheme was designed with reduced contact area to explore the system thermal behaviour under different cooling regimes. Experimental data obtained from battery characterisation and performance tests is analysed with a thermal-coupled equivalent circuit model to quantify changes in cell impedance and system thermal properties. By reducing the clamping area by 70%, the temperature rise of the cell was decreased by 0.5 °C in comparison to the reference condition of a cell with no clamping during a 1C discharge under natural convection. Under immersion cooling using BOT2100 dielectric liquid, the thermal benefit was amplified, resulting in temperature reductions of 0.9 °C at 1C and 4 °C at 3C. The principal conclusion of this work is that reshaping the clamping plate has the potential to reduce ohmic heating by lowering battery internal resistance, which outweighs the additional thermal resistance introduced by partial surface coverage. This novel experimental approach demonstrates the potential to improve battery thermal management through geometry-optimised cell clamping, particularly for high-power applications, and further directs the community towards cell clamping solution designed to optimise both thermal and mechanical cell performance. Full article

Anaerobic digesters operating under neotropical conditions face significant technological constraints. High humidity, intense solar radiation, and pronounced diurnal temperature variations increase conductive, convective, and radiative heat losses. These factors reduce internal thermal stability and directly affect methane production rates and overall energy efficiency. As a result, thermal instability becomes a recurrent operational bottleneck in biogas plants without active temperature control. This review examines the thermal and dynamic behavior of anaerobic reactors from a process-engineering perspective. It integrates energy balances, heat-transfer mechanisms, and computational fluid dynamics (CFD) modeling. The combined effects of temperature gradients, hydrodynamic mixing patterns, and structural material properties are analyzed to determine their influence on thermal homogeneity, microbial stability, and methane yield consistency under mesophilic conditions. Technological strategies to mitigate thermal losses are evaluated. These include passive insulation using low-conductivity materials, geometry optimization supported by numerical modeling, and thermal recirculation schemes, as these factors govern temperature distribution and process resilience. Current limitations are also discussed, particularly the frequent decoupling between ADM1-based kinetic models and transient heat-transfer analysis. This separation restricts predictive capability under real-scale diurnal temperature oscillations. The development and validation of coupled hydrodynamic–thermal–biokinetic models under fluctuating neotropical boundary conditions are proposed as critical steps. Such integrated approaches can enhance operational stability, ensure consistent methane production, and improve energy self-sufficiency in organic waste valorization systems. Full article

Located in the north of Yunnan Province, China, the Wuding geothermal area is a typical medium- and low-temperature geothermal system with strong hydrothermal activity and development potential as a clean and renewable energy resource. This study systematically investigates the main controlling factors of the Wuding geothermal field through field investigation, hydrochemical analysis, and stable isotope analysis, and puts forward a genetic model of the geothermal field. The results show that the Wuding geothermal field is a medium- to low-temperature, conduction-dominated geothermal system, and its geothermal water is predominantly of the Ca–HCO₃ (calcium bicarbonate) type. The recharge area lies at an altitude above 2250 m, which is speculated to be within the mountainous area in the southwest of the study area. The underground hot water in the area is immature water. The source water circulates to the deep heat storage zone along faults, rises to the surface through heat convection, and is exposed as hot springs. Upon discharge, the geothermal water mixes with shallow cold water, with cold-water dilution accounting for up to 85% of the total volume. Using the silica thermometer, cation thermometer, and silicon enthalpy model, the maximum temperature of heat storage is estimated to be 91 °C, with the depth of geothermal water circulation reaching 2200 m. The thermal reservoir is composed of dolomites of the Upper Cambrian Erdaoshui Formation (∈3e) and Sinian Dengying Formation (Zbd). Its heat source is heat flow from the upper mantle and the decay of radioactive elements. Continuous heat flow to the thermal reservoir is maintained through the fold fracture zone and faults in the core of the Hongshanwan anticline. The proposed genetic model of the Wuding geothermal field provides a scientific basis for the sustainable redevelopment and utilization of this geothermal resource and is of significance for regional low-carbon energy use and socio-economic sustainable development. Full article

Accurate precipitation nowcasting plays an important role in disaster prevention and hydrometeorological applications, yet it remains highly challenging due to the complex spatiotemporal variability and multi-scale structural characteristics of precipitation systems. Existing deep learning methods are largely data-driven and often struggle to effectively exploit multi-source observations or learn physically meaningful representations. To address these limitations, this study proposes a Multi-Scale Frequency–Temporal Network (MS-FTNet) for precipitation nowcasting. The framework leverages Fourier transform-based frequency-domain modeling to achieve an interpretable multi-scale decomposition of precipitation dynamics. Specifically, low-frequency components capture large-scale stratiform patterns and their temporal evolution, while high-frequency components represent localized convective structures and abrupt variations. Building on this, a Global Feature Collaboration (GFC) module integrates global frequency-domain representations with multi-scale convolutional features, and an Adaptive Temporal Fusion (ATF) module enhances temporal dependency modeling. Experiments on the SEVIR dataset demonstrate that MS-FTNet consistently outperforms representative baseline models in terms of MSE, CSI, and LPIPS, particularly for heavy precipitation events and longer forecast lead times. Full article

The conversion of surplus electrical energy into thermal energy represents an effective pathway for increasing the flexibility of renewable-energy systems. This study presents an experimental and numerical assessment of a compact vapor-assisted sensible heat storage unit designed to transform electrical input into stored thermal energy using a controlled evaporation–condensation process inside a vertical steel cylinder. An 800 W immersion heater was employed to generate vapor, while nine temperature sensors monitored the thermal response of the evaporator, enclosure air, and storage medium. Two operating configurations, insulated and non-insulated, were investigated to characterize charging and discharging dynamics. In parallel, CFD simulations performed in ANSYS Fluent were used to analyze coupled heat transfer and phase-change mechanisms. The results demonstrate efficient electrical-to-thermal energy conversion, with rapid temperature rise during charging driven by vapor-assisted convection following the onset of boiling. Experimental data and numerical predictions consistently reveal a transition from conduction-dominated heating to a phase-change-enhanced regime, which accelerates heat distribution and thermal homogenization within the storage unit. Comparative tests further indicate that reduced external losses improve heat retention during discharge. Overall, the combined experimental–numerical approach confirms the capability of the proposed compact system to store electrically generated heat in a stable and repeatable manner, highlighting its potential for daily photovoltaic energy buffering and small-scale renewable-energy applications. Full article

Accurate short-term lightning forecasting requires reliable representations of both lightning occurrence and intensity, as well as the underlying convective processes. While ensemble prediction systems (EPSs) provide valuable probabilistic information, their ability to resolve mesoscale and convective-scale variability remains limited. In this study, we assess the added value of mesoscale information for probabilistic lightning forecasting over eastern China. A mesoscale ensemble is constructed from deterministic forecasts of the China Meteorological Administration (CMA) Mesoscale Model (MESO) using spatiotemporal neighborhood and time-lagged techniques and is combined with predictors from the CMA Regional Ensemble Prediction System (REPS). Lightning occurrence and counts are modeled within a Bayesian additive model for location, scale, and shape (BAMLSS) framework, using a hurdle-based count regression to account for excess zeros and overdispersion. Influential nonlinear predictors are selected via stability selection combined with gradient boosting. Forecast performance with and without MESO-derived predictors is systematically evaluated. The results indicate that incorporating mesoscale information generally improves forecast skill for both lightning occurrence and intensity across multiple verification metrics. These improvements are associated with MESO-derived predictors related to convective available potential energy and convective precipitation, suggesting the importance of mesoscale processes for probabilistic lightning forecasting. Full article

Carbon dioxide (CO₂) hydrate slurries have emerged as promising candidates for cold thermal energy storage (CTES) and refrigeration systems due to their high latent heat, controllable flow behavior, and environmentally friendly nature. These slurries are formed by dispersing solid CO₂ hydrate particles in a liquid phase, forming a multiphase system with tunable thermophysical and rheological properties. The performance of these slurries is dependent on nucleation kinetics, particle sizes and their distribution, solid content, and thermal transport characteristics under flow conditions. This review paper gives an assessment of CO₂ hydrate slurries from a thermofluid’ perspective by focusing on key aspects such as hydrate nucleation mechanisms, viscosity behavior, shear response, thermal conductivity, convective heat transfer, and slurry stability. Particular attention is given to the role of surfactants and nanoparticle additives that enhance hydrate formation and improve slurry performance. The addition of nanofluids is discussed both in terms of their effect on thermal properties as well as in flow stability. Full article

This study presents a comparative evaluation of four drying methods for carrot, red beet, and pumpkin pomace to produce natural functional food ingredients. The work addresses the valorization of 35–45% vegetable processing waste—a rich source of bioactive compounds—aligning with circular bioeconomy principles and Kazakhstan’s goals for deep processing of agricultural raw materials. The compared methods were convective drying (CD), ultrasound pretreatment + convective drying (US + CD), vacuum-microwave drying (VMD), and ultrasound pretreatment + vacuum-microwave drying (US + VMD). Drying kinetics, water activity, physicochemical and functional properties of powders, retention of bioactive compounds, color characteristics, thermal stability, and sensory attributes were assessed. Kinetics were fitted using Midilli et al., Page, and Weibull models. US + VMD provided the highest drying acceleration (6–11 times faster than CD), reaching final moisture of 5.1–5.9%, water activity a_w 0.27–0.31 in 80–170 min, and bioactive compound retention of 90–95% (carotenoids 92–95%, betalains 90–94%). It also delivered superior flowability (Carr’s index 22.5–30.4%), dispersibility (80–88% in 30 s), and thermal stability (75–85% at 200 °C). Acceleration varied by raw material: maximum for beet (up to 11×) due to soluble sugars and nitrates, minimum for pumpkin (5.5–8×) due to dietary fibers and pectins, and intermediate for carrot (6–9×) influenced by carotenoids’ dielectric properties. The results highlight US + VMD’s strong potential for producing functional powders to replace synthetic additives in food systems. Effective method selection and parameter optimization require consideration of raw material type and rheological characteristics. Full article

This study investigated thermal insulation in layered suit systems by systematically varying air-layer thickness and structure (single vs. sandwiched), fabric air permeability, and ambient airflow. A hot plate based apparatus equipped with air-layer spacers and an airflow-generation system was developed, and suit fabrics with different air permeability but similar thickness were fabricated. Heat flux from the heated plate and air-layer temperature were measured in three experimental series. Under no-airflow conditions, insulation was maximized at a 20 mm air layer, whereas a 30 mm air layer increased heat flux, suggesting buoyancy-driven convection. Under airflow conditions, thinner air-layers allowed airflow to influence the hot plate region more directly, while thicker-layers attenuated this effect. The sandwich-structured air layer reduced heat flux compared with a single air layer of the same total thickness, and its effect depended on the thickness distribution between the upper and lower air-layers. Fabric air permeability increased heat flux mainly under airflow, indicating that permeability effects should be evaluated under combined conditions of ambient airflow and controlled air-layer configurations. Full article

We evaluated the indoor environmental quality of the administrative office at University Medical Center Ho Chi Minh City branch 2 and implemented a multi-stage engineering control strategy to optimize occupational health conditions. A cross-sectional assessment monitored important air quality parameters, including carbon dioxide (CO₂), fine particulate matter (PM2.5 and PM10), humidity, and illumination. Following baseline measurements, an integrated system was deployed to address pollutant mass balance, consisting of High-Efficiency Particulate Air (HEPA) filtration units for mechanical particle scrubbing, ceiling-mounted axial fans to induce forced convection, and ultraviolet-C germicidal lamps for photochemical disinfection. Post-intervention results demonstrated significant gains in system removal efficiency. CO₂ concentrations decreased by over 60% due to enhanced volumetric air exchange, while PM2.5 levels decreased by more than 40% through interception and diffusion mechanisms within the HEPA media. Furthermore, UVC irradiation achieved a 90% reduction in viable airborne microbial colonies. The results of this study show that low-cost, scalable environmental engineering controls and fluid dynamic optimizations effectively mitigate indoor air pollution and enhance workplace stability in healthcare administrative settings. Full article

The operational safety and endurance of unmanned aerial vehicles (UAVs) are strongly affected by lithium-ion battery degradation under extreme thermal environments. However, conventional physics-based models often rely on simplified assumptions, whereas purely data-driven methods usually lack physical interpretability and robust generalization. To address these limitations, this study proposes a Physics-Informed Deep Neural Network (PIDNN) for predicting UAV battery degradation under complex environmental conditions. The proposed framework integrates thermodynamic and fluid dynamic principles with deep neural networks by incorporating physical constraints derived from heat generation, heat conduction, and convective heat transfer into the loss function. This design enables the model to capture nonlinear degradation patterns while maintaining consistency with fundamental physical laws. Comprehensive simulation-based experiments were conducted under high-temperature (45 °C), low-temperature (−20 °C), and room-temperature (25 °C) conditions, together with varying discharge rates, humidity levels, wind speeds, and multi-factor coupled scenarios. The results show that the proposed PIDNN consistently outperforms conventional physics-based models and several representative data-driven methods, including SVM, LSTM, and GAN-based approaches. It achieves lower prediction errors across all evaluated conditions, as reflected by reduced mean absolute error and root mean square error. By providing physically consistent predictions of capacity fade, internal resistance growth, and remaining useful life, the proposed framework supports degradation-aware monitoring and early warning for intelligent battery management systems. These findings provide a robust methodological basis for improving the reliability, safety, and service life of UAV power systems operating in complex climatic environments. Full article

In this study, we investigate the impact of processing strategies on the nanoscale morphology and photophysical behavior of donor–acceptor thin films composed of the polymeric donor PBDTTTPD and the n-type acceptor PNDI(2HD)2T. The blend morphology and interfacial characteristics were systematically tuned using three distinct fabrication techniques: spin-coating, convective self-assembly, and space-confined solvent vapor annealing. Atomic force microscopy and photoluminescence spectroscopy were employed to elucidate structure–property correlations relevant to all-polymer optoelectronic systems. Films processed via convective self-assembly exhibited nanoscale features with extensive donor–acceptor intermixing, leading to the most efficient photoluminescence quenching of nearly 85%, indicative of enhanced exciton dissociation and charge transfer. In contrast, as-cast films displayed moderately mixed morphologies with approximately 81% quenching, serving as a reference state. The solvent vapor annealing method induced pronounced phase segregation and the formation of larger domains, resulting in reduced photoluminescence quenching efficiency of about 52%. These findings demonstrate that the nanoscale morphology, and consequently the photophysical response, of PBDTTTPD:PNDI(2HD)2T blends can be precisely tailored through processing, providing valuable design guidelines for all-polymer optoelectronic applications such as organic photovoltaics and field-effect transistors. Full article

Enhancing convective heat transfer in solar air heaters (SAHs) without disproportionate hydraulic penalty remains critical for decentralized low-carbon heating. This study experimentally investigates a serpentine-channel SAH equipped with distributed three-dimensional vortex generators under outdoor winter conditions. The configuration combines curvature-induced secondary motion with distributed vortex generation to intensify absorber–air heat transfer. Experiments were conducted over a mass flow range of 0.012–0.061 kg s⁻¹, corresponding to a Reynolds number range of 2.1 × 10³–1.07 × 10⁴, using a smooth duct as the reference configuration. The enhanced configuration achieved peak thermal efficiencies of 81.6–85.4%, compared with 65.8–67.7% for the smooth collector, while daily averaged efficiency increased from 56–59% to 71–75%. Although pressure drop increased, thermo-hydraulic performance remained superior across the investigated Reynolds number range. Exergy efficiency was consistently higher for the enhanced system and remained within optical limit constraints. Environmental assessment based on grid emission factor displacement indicates approximately 33% greater annual CO₂ mitigation potential, corresponding to about 6.6 tonnes over a 20-year service life. The levelized cost of heating was estimated at 3.1–4.4 ₹ kWh⁻¹. These results indicate that compound curvature–vortex transport intensification can improve thermal efficiency and increase carbon mitigation potential under realistic operating conditions. Full article

The accurate and timely nowcasting of severe weather events such as short-term torrential rainfall is essential for disaster preparedness and early warning systems. Our prior studies have demonstrated a high correlation (0.92) and ~10 min time lag between in-cloud (IC) lightning and ground rainfall. In this study, based on the approach introduced by Shimizu and Uyeda, an automatic method for identifying and tracking convective storm cells, we integrate total lightning data and heavy precipitation data for further improving the prediction accuracy of torrential rainfall. High-resolution 2D weather radar composite precipitation data are collected from XRAIN, operated by MLIT, Japan, and total lightning data (TL, i.e., IC and CG) are collected from the Japanese Total Lightning Network (JTLN). The adapted algorithm is used to track lightning-frequent areas (≥5 and ≥2 pulses per 5 min) as well as heavy (≥50 mm/h) and torrential (≥80 mm/h) precipitation cells. To evaluate the predictive capability of TL, cross-correlation analyses are performed across multiple intensity thresholds and time lags. The results of correlation matrix analysis for identifying the movement of the storm and utilization towards spatiotemporal nowcasting of extreme rainfall is discussed. Full article

This paper starts by analysing the equivalent circuit model of a Thermoelectric Module (TEM) with PLECS simulation by using the PLECS thermal block-set. The approach enables the evaluation of power-module losses when mounted on a sandwich assembly of a TEM, heatsink, and cooling fan. An experimental setup was first built using power resistors for controlled heat generation to be absorbed by the cooling system and validated with the simulation model. Experimental investigations were then carried out on a DC/DC converter under four cooling conditions: natural convection and forced convection without a TEM and then natural convection and forced convection with a TEM. The experimental results are validated using PLECS Software (version 4.8). This result demonstrates a reduction in the power-module junction temperature of the DC/DC converter when employing forced convection with a TEM compared to forced convection without a TEM. Furthermore, the results indicate about 32% potential weight and size reduction of the converter magnetic components, along with improved power density, through the integration of TEM-based cooling. Full article