Search Results (2,822)

Bird feathers possess functions such as water resistance, thermal insulation, and air permeability, providing inspiration for the design of functional fabrics. Based on the functional differentiation of different feather regions and the structural constraints associated with these functions, this study selected down feathers, feather vanes, hooklets, and fluffy feather filament node structures as biomimetic prototypes. Four biomimetic knitted structures were designed for outdoor environments with significant temperature fluctuations and for the thermo-moisture comfort needs of older adults. Through macro- and micro-structural feature extraction, three-dimensional modeling, and experimental testing, a multi-parameter evaluation system covering water resistance, thermal resistance, thermal insulation rate, air permeability, moisture vapor transmission, and moisture management was established to systematically evaluate the thermo-moisture regulation performance of the fabrics. The results showed that each structure exhibited distinct performance advantages: Structure 1 demonstrated the best thermal insulation performance; Structure 2 showed relatively superior water resistance and outstanding air permeability; Structure 4 exhibited relatively superior moisture vapor transmission and moisture management performance; and Structure 3 achieved the highest gray relational optimality value, indicating a relatively balanced thermo-moisture regulation capability. Among all performance indicators, air permeability showed the highest correlation with the knitted structures. Based on these results, and considering regional differences in heat generation and sweating across different body parts of older adults, this study further explored zonal application strategies for elderly outdoor clothing to improve wearing comfort and functionality under environments with fluctuating thermal conditions. Full article

This paper proposes an experimental, intelligent optimization approach to improve the thermal cooling performance of an overclocked graphics processing unit (GPU). A closed-loop liquid-cooling system was built and tested utilizing deionized water and a silver (Ag) nanofluid coolant (0.015% vol.) across a variety of microchannel heat sink topologies with varying fin spacing. Key thermal performance indicators, including GPU temperature, coolant outlet temperature, and thermal resistance, were measured at different coolant flow rates. Experiments revealed that raising the flow velocity and decreasing the fin gap considerably enhanced cooling performance, while the Ag nanofluid consistently lowered GPU temperature by 1–3 °C compared to water. An Artificial Neural Network (ANN) surrogate model was constructed and trained using experimental data to support predictive analysis and system optimization, achieving excellent predictive accuracy with low RMSE. The trained ANN model was combined with the Non-dominated Sorting Genetic Algorithm II (NSGA-II) to perform multi-objective optimization, aiming to minimize GPU temperature and thermal resistance while improving heat removal. The Pareto-optimal solutions revealed that nanofluid-based cooling offered the best trade-off circumstances, with optimal designs occurring at moderate flow rates and small fin spacing. The ANN-NSGA-II multi-objective optimization results indicated that the best thermal performance of the GPU cooling system was achieved when using Ag nanofluid (0.015 vol.%) as the coolant, with an optimal coolant flow rate in the range of 1.30–1.84 LPM and an optimal fin/channel spacing of 0.57–0.71 mm, producing GPU temperatures of 29.18–29.66 °C, coolant outlet temperatures of 29.06–29.41 °C, and a minimized thermal resistance of 0.0106–0.0152 °C/W; thus, overall, the suggested ANN-NSGA-II framework works well as a practical design tool for improving GPU cooling systems and may be used to other high-heat-flux electronic thermal management applications. Full article

Battery Energy Storage Systems (BESSs) are increasingly deployed in grid-scale applications, electric mobility, and renewable integration, where safety, reliability, and longevity are critical. Thermal runaway remains one of the most severe failure modes in lithium-ion batteries, often triggered by complex interactions between electrochemical, thermal, and mechanical phenomena. This paper presents an extended hybrid Physics-Informed Neural Network (PINN) framework for thermal anomaly prediction and early detection of runaway precursors in BESS. The proposed architecture integrates governing physical laws, specifically the Bernardi heat generation equation and Fick’s diffusion law, within a deep learning pipeline composed of a physics module, a temporal Bi-LSTM, and an attention mechanism for explainability, which may represent an obstacle in the application of deep learning algorithms. Beyond the initial formulation, the extended version presented here provides a deeper theoretical background, an expanded methodological justification, a more comprehensive comparison with state-of-the-art approaches, and a detailed discussion on scalability, uncertainty, and deployment challenges. The results for synthetic yet physically consistent datasets represent a proof of concept of the PINN approach, which can achieve superior generalization, robustness to noise, and interpretability compared to purely data-driven baselines, achieving an accuracy above 90% and an AUC of 0.95. The framework contributes to proactive safety management in cyber-physical energy systems and establishes a foundation for real-time, physics-aware anomaly detection in safety-critical BESS applications, e.g., marine transportation contexts and port environments. Full article

Forest fires are an increasing environmental challenge in Southern Europe, requiring reliable tools for assessing both fire-induced disturbances and subsequent ecosystem recovery. This study presents an integrated satellite-based system for automated monitoring of post-fire forest dynamics. The system combines multispectral data from Sentinel-2 and Landsat (TM, ETM+, OLI, OLI-2) with thermal anomaly information from MODIS and VIIRS within a unified processing framework. It is structured into two modules: Post-Fire Disturbance (PFDMO) and Post-Fire Recovery (PFRMO). The methodology builds on a validated algorithm integrating the Disturbance Index (DI), Vector of Instantaneous Condition (VIC), and Direction Angle (DA), enabling automated multi-temporal analysis from fire detection to recovery assessment. The system was applied to three wildfire-affected areas in Bulgaria under different environmental conditions. Results reveal substantial spatial variability in disturbance and recovery, with PFDMO values ranging from −5.17 to +10.16 and PFRMO values from −2.25 to +7.40. The results demonstrate the applicability of the proposed system for monitoring post-fire forest dynamics and illustrate its potential to support informed decision-making in forest management, biodiversity conservation, and sustainable resource use. The main contribution of the system lies in the integration of disturbance and recovery assessment within a single automated and scalable workflow based on freely available satellite data. Full article

Accurate estimation of the internal spatial-temporal temperature distribution is crucial for the safety and performance management of lithium-ion batteries. However, traditional lumped parameter models overlook spatial gradients, while numerical methods for partial differential equations (PDEs) incur high computational costs. This paper proposes a hard constraint physics-informed neural network (HCPINN) framework for the real-time reconstruction of the axial temperature field in 18,650 cylindrical batteries. By restructuring the neural network’s solution space through distance functions, the Robin boundary conditions are strictly embedded as hard constraints, ensuring exact satisfaction of the prescribed Robin boundary conditions within the mathematical model and eliminating boundary loss terms. An electro-thermal coupled model considering the Arrhenius effect and state-of-charge (SOC) dependent internal resistance is integrated into the loss function to capture the nonlinear heat generation dynamics. Experimental validation across discharge rates from 1C to 4C demonstrates that the HCPINN achieves high estimation accuracy with a mean absolute error (MAE) below 0.34 °C. Furthermore, by leveraging the continuous differentiability of the model, this study quantifies the evolution of spatial temperature gradients and reveals the ideal heat transfer coefficients required for thermal equilibrium are inverted, providing a quantitative basis for the design of advanced battery thermal management systems (BTMS). Full article

Lithium-ion batteries (LIBs) are widely used in the electric bicycle/vehicle sector, but fire accidents frequently caused by thermal runaway of LIBs have become a severe public concern. From a reverse perspective of safety engineering, investigation of fire accidents based on the historical data recorded by the Battery Management System (BMS) and exploration of the causes of thermal runaway can enhance the safety of LIBs and electric bicycles/vehicles. This study aims to provide support for fire investigation through the analysis of the BMS. By conducting electrical, thermal and mechanical abuse experiments, the variations of the electrothermal parameters involving voltage, current and temperature are examined. The results reveal that these electrothermal parameters exhibit unique time-sequential inter-relationships under each specific abuse mode. A secured relationship can be solidified between the variation features of the electrothermal parameters and the specific cause of thermal runaway, i.e., whether the abuse mode is electrical, thermal or mechanical abuse. Such peculiar time-series variations or inter-relationships can be used for post hoc fire investigation to trace the fire reasons. Based on the findings of this study, a real fire case was analyzed to validate the feasibility of the proposed tracing method by means of BMS analysis. The resultant fire reason confirmed the one given by the authority, thus validating the effectiveness of the fire investigation method. Full article

This study proposes two enhanced configurations for a parallel-channel cold plate in battery thermal management systems to improve thermo-hydraulic performance through the introduction of cylindrical and fin-type baffles. A three-dimensional computational fluid dynamics (CFD) model was developed in ANSYS to simulate fluid flow and heat transfer within the cold plate. A Poly-Hexcore meshing strategy with local refinement and near-wall inflation layers was employed to ensure numerical accuracy while maintaining computational efficiency. A parametric investigation involving 150 cases was conducted to identify the optimal channel configuration. The results indicate that, among the investigated configurations and under the present numerical operating conditions, the fin-type baffle exhibits the most balanced thermo-hydraulic behavior by achieving an effective balance between heat-transfer enhancement and pressure-drop penalty. The present study provides a CFD-based framework for the design and optimization of parallel-channel cold plates for battery thermal management applications. Full article

Cascaded multilevel inverters constitute a promising system concept for battery electric powertrains due to their high efficiency, low harmonic distortion, and advanced battery management capabilities. This study presents a novel electro-thermal simulation framework for the symmetrical Parallel Enhanced Commutation Integrated Nested (PECIN) multilevel inverter. The proposed model employs a control-oriented approach that enables the development and evaluation of advanced inverter and battery control algorithms, which exploit the extensive series-parallel reconfiguration capabilities of the PECIN topology. The framework is based on electrical and thermal equivalent circuit models to capture physical behavior and cross-domain interactions. Electrical network analysis employs algorithms that iterate over each phase-arm network, replacing high-dimensional matrix inversions and thereby enhancing computational efficiency. The overall model is readily adaptable to various system configurations, including different AC and DC charging modes, and scalable with respect to the number of submodules and phases. Simulation results for a 31-level multilevel inverter in a three-phase AC charging configuration demonstrate the model’s operational capabilities. Execution time analysis shows that the current distribution calculation is the key contributor to computational effort as the number of submodules increases, resulting in a quadratic growth of the overall computational time. Full article

Integrating a heat exchanger (HEX) into the cooling duct of a high-power fuel-cell-based aircraft presents a critical trade-off between thermal performance and aerodynamic penalties. The present study addresses this challenge through the design and system-level analysis of a HEX integrated into the cooling duct. Developed as part of the Clean Aviation project FAME, the design features a rectangular inlet, a circular outlet, and a tilted HEX. The evaluation is performed using high-fidelity Large Eddy Simulations (LESs). The HEX is modeled with a porous media approach based on the Darcy–Forchheimer equation, while the simulations are carried out using a self-adapted version of the pisoFoam solver, termed pisoTempFoam, to account for heat transfer. The study reveals that while component-level design choices, such as a straight inlet and tilted HEX configuration, successfully mitigate local flow separation and duct-induced losses, a critical system-level performance issue emerges. The analysis demonstrates that the cooling duct design, when subjected to realistic operational conditions, generates the high pressure head to overcome the resistance of the HEX. The external aerodynamic analysis also indicates that the HEX resistance is a critical factor, and without overcoming it the system fails to capture the required air mass flow rate, compromising thermal management. The findings highlight the necessity to optimize the design, by an adapted duct shape or an auxiliary fan, to overcome the HEX-induced pressure drop. The porous media approach is thereby validated as an effective tool for rapid system-level design analysis, despite its inherent limitation in capturing detailed downstream turbulence. Full article

Within the framework of European Union-funded Clean Aviation and TheMa4HERA (Thermal Management for the Hybrid Electric Regional Aircraft) projects, a preliminary performance prediction and design tool for centrifugal compressors has been developed, targeting the turbomachinery components used in environmental control systems (ECS) in short/medium-range types of aircraft. This tool is an integral part of the objective to establish a complete optimization methodology for the performance assessment and sizing of air generation systems for next-generation aircraft. The methodology is based on mean-line analysis for the impeller, vaneless and vaned (including variable-vaned) diffusers, and volute, with a two-zone approach for the flow analysis in the vaned diffuser passage. The results of the model are validated against experimental data related to two different open-source compressor designs with both diffuser types. It is concluded from these cases that, for the purpose of the design tool, the model provides accurate results for the impeller and both diffuser types. Extreme conditions such as stall and choke remain difficult to accurately predict due to the complex three-dimensional nature of these phenomena. Future developments of the tool will include modeling capabilities for radial turbines and heat exchangers. Full article

Utility disruptions may stem from insufficient power generation, inferior infrastructure, or secondary weather perils (e.g., tornadoes, floods, snowstorms) that take energy infrastructure offline. The latter present a unique risk that not all existing power options can mitigate. Regardless of their origin, power disruptions have the potential to cripple food supply chains and undermine food system sustainability. To prepare for managing future disruptions, food and beverage manufacturers may couple electrical microgrid and thermal district heating infrastructure with small modular reactors (SMRs) or smaller microreactor systems to form low-carbon power islands. Although SMR technology is a somewhat new source of energy and has not yet achieved commercial viability, it provides the potential to make food and beverage manufacturing more resilient and sustainable when it becomes broadly available. To assess the potential cost–benefit of activating such technology as a sustainability-oriented resilience investment, we conducted a technoeconomic downtime threshold analysis. The case assumes that the technology is the full-time power source and the SMR yields stronger returns as facility downtime or downtime costs rise. The analysis found the breakeven point to range from 12.3 h down to 613.2 h down annually for a 5 MW system, depending on facility scale and assumed downtime costs. At a representative downtime opportunity cost of $10,000/h, SMR adoption requires approximately 61.3 h (5 MW) of annual outages to break even, highlighting scale effects on feasibility. Incorporating a 20% thermal energy credit reduces required outage thresholds by roughly 20%, lowering the breakeven level to 49.1 h. These results highlight the potential role of SMR-enabled power islanding in supporting sustainable food manufacturing through improved energy resilience, low-carbon power, and thermal energy recovery. Full article

Miniature vapor compression refrigeration systems are gaining increasing relevance in cutting-edge applications such as drone docking station cooling, electric vehicle battery thermal management, portable medical and diagnostic devices, compact beverage dispensers, field-mounted telecom cabinet cooling, as well as the already established fields of electronics and personal cooling. These systems offer a promising pathway to localized and mobile cooling solutions. When coupled with the implementation of alternative low-GWP refrigerants that match or even enhance system performance, the result is a more efficient, environmentally responsible, and potentially sustainable refrigeration technology. Therefore, this study experimentally evaluates the performance of R515B as a low-GWP drop-in replacement for R134a in a miniature vapor compression refrigeration system. Key parameters were analyzed to determine the most suitable operating conditions, resulting in a capillary length of 1.25 m, refrigerant charge of 110 g, compressor speed of 4500 rpm, and high condenser fan speed, under which R515B achieved a COP of 5.16 and a cooling capacity of 252.20 W, representing improvements of 38% and 6.5%, respectively, compared to R134a. These results confirm the viability of R515B as an efficient, environmentally friendly alternative for miniature small-scale vapor compression systems. Full article

Background: Isolated Perfusion Chemotherapy (IPC) with balloon occlusion creates transient ischemic tissue compartments while patients remain exposed to significant perioperative heat loss. Active warming during these phases is commonly avoided due to theoretical concerns regarding impaired heat distribution and potential local heat accumulation in ischemic tissue. This study investigated the thermal safety of forced-air warming during IPC under these conditions. Methods: In this prospective observational study, 31 patients undergoing IPC were monitored during balloon-induced vascular occlusion. Convective warming was applied using a forced-air system set to 43 °C. Core temperature was measured rectally, and local temperatures were continuously recorded at gluteal, lumbar, and interscapular sites. Temperature trajectories and maximum values during occlusion were analysed descriptively. Results: Local temperature increases during ischemia were limited, with a maximum increase of 2.3 °C at the lumbar site. Absolute temperatures remained well below the predefined safety threshold of 39.5 °C at all skin measurement sites (maximum observed 37.7 °C). Core temperature remained stable throughout the occlusion phase. No evidence of local heat accumulation, threshold exceedance, or thermal skin reactions was observed. Conclusions: Under conditions of controlled application, close temperature monitoring, and short ischemic intervals, forced-air warming during IPC did not result in local overheating or clinically relevant thermal exposure. These findings challenge the prevailing precautionary approach of avoiding active warming during vascular isolation and provide prospective clinical evidence supporting a reassessment of temperature management strategies toward actively maintained normothermia in isolated perfusion chemotherapy. Full article

Urban heating systems continue to rely heavily on fossil fuels, driving significant CO₂ emissions and underscoring the need for scalable renewable alternatives. This study evaluates a solar-assisted aquifer thermal energy storage (ATES) system for sustainable urban heating, operating within a relatively deep aquifer. A numerical model of the Mannville aquifer is developed to simulate charge–discharge cycles in a relatively deep open-loop ATES system, examining subsurface temperature evolution, storage efficiency, and long-term thermal stability under Canadian climatic conditions. Modeling results indicate that such aquifers act as an effective thermal buffer for solar energy storage operations, smoothing seasonal temperature fluctuations and stabilizing heat production. Surplus solar thermal energy injected during low-demand periods significantly reduces long-term temperature decline and preserves thermal availability for winter extraction. Balancing contributions from solar and aquifer storage maintains system efficiency during peak demand while improving overall thermal management. The integrated approach enhances renewable energy utilization, reduces reliance on conventional heating systems, and strengthens the resilience of urban energy networks. Our findings demonstrate that coupling solar thermal input with geothermal heat storage in relatively deep aquifers offers a practical pathway for advancing sustainable urban heating in cold-climate regions. The modeling framework provides a foundation for optimizing seasonal storage strategies and guiding the design of hybrid solar–geothermal systems for large-scale urban applications. Full article

The physiological performance of the Pacific oyster Magallana gigas in subtropical lagoon systems is shaped by the interaction between environmental variability, reproductive dynamics, and oxidative stress. This study quantified monthly changes in the growth and proximate composition of oysters cultivated in Estero La Cruz, Sonora, and evaluated their relationship with temperature and chlorophyll-a as proxies for thermal stress and trophic availability. Shell growth was continuous, while somatic biomass increased markedly during winter, indicating high thermal tolerance and metabolic flexibility. Proximate composition showed pronounced seasonal oscillations, with energy reserves accumulating during periods of high primary productivity and declining sharply in December, coinciding with peak gametogenic activity. Antioxidant enzyme activities (SOD, CAT, GPx) increased toward winter, reflecting elevated oxidative stress. Correlation and regression analyses revealed consistent relationships among environmental variables and biological responses, identifying temperature as the main factor associated with growth variability. Overall, these results demonstrate a strong coupling between environmental forcing, energy allocation, and oxidative stress, providing an integrative framework for understanding oyster performance and supporting aquaculture management in subtropical coastal systems. Full article