Search Results (976)

Driven by demanding global emission regulations and the urgent requirements for sustainable mobility, Electric Vehicles (EVs) have emerged as the primary alternative to Internal Combustion Engine (ICE) vehicles. Central to this transition is the electric propulsion system (EPS), a multidisciplinary integration of power electronics, advanced motor drives, and electrochemical energy storage. This paper provides a comprehensive overview of the current landscape of power electronic drives, focusing on the evolution of high-efficiency traction motors and next-generation energy storage systems (ESSs), and advancements in ultra-fast chargers. The analysis explores the vital impact of power converters, evaluating recent breakthroughs in wide-bandgap (WBG) semiconductors and advanced control topologies that enhance energy density and thermal management. Furthermore, the study identifies critical challenges in the design, modulation, and operational reliability of converters under dynamic automotive environments. By synthesizing current research trends and technical bottlenecks, this paper offers insights into the future trajectory of power electronics in achieving high-performance, cost-effective, and carbon-neutral transportation. 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

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

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

The safe operation of power battery systems relies on the dynamic symmetric equilibrium of electrochemical distribution and thermal management states, whereas fault occurrence is often accompanied by symmetry breaking. To achieve accurate fault diagnosis and symmetry restoration, this study proposes a symmetrical closed-loop framework (DBP-KG-FBN) that integrates digital battery passport (DBP) text mining, knowledge graph (KG), and fuzzy Bayesian network (FBN). Power battery fault diagnosis is critical to new energy vehicle (NEV) safety; however, conventional methods face two key limitations: (1) they inadequately exploit multi-source heterogeneous textual data in DBPs; and (2) they fail to handle uncertainty in fault propagation. The methodology proceeds as follows. First, a BERT-BiLSTM-CRF model extracts fault-related entities and relations from unstructured DBP text, which are structured into a Neo4j-based knowledge graph. Second, via rule-based topological mapping, the KG topology is transformed into a Bayesian network through structurally symmetric transformation between the semantic and probabilistic layers, with cyclic dependencies resolved by introducing latent variables. Third, network parameters are determined by integrating fuzzy set theory with game theory-based weighting to quantify uncertainty and subjectivity in expert evaluations, thereby achieving symmetric utilization of subjective and objective information. This enables bidirectional symmetric reasoning for forward fault prediction and backward fault traceability. Experimental results demonstrate that while maintaining symmetric stability of the diagnostic knowledge topology, the proposed DBP-KG-FBN method achieves a diagnostic accuracy of 0.92 (Top-3). This symmetrical closed-loop framework significantly outperforms fault tree analysis (FTA) and event tree analysis (ETA) in diagnostic accuracy and reasoning efficiency. It transforms unstructured DBP data into computable knowledge for intelligent battery diagnosis. Future work will expand the corpus via transfer learning and optimize adaptive weighting algorithms for expert evaluations. Full article

Cairo’s Islamic architectural heritage represents one of the world’s most significant concentrations of pre-industrial environmental ingenuity. For over a millennium, an integrated suite of passive climate-control systems—the Mašrabiya latticework screen, the open courtyard (Ṣaḥn), the wind-scoop (Malqaf), and stalactite vaulting (Muqarnas)—has moderated temperature, humidity, and airflow with remarkable effectiveness. Today, these inherited solutions are under unprecedented stress from urban densification, chronic particulate pollution, climate-driven temperature rise, and growing visitor footfall. This study investigates indoor environmental quality (IEQ) in six Fatimid- and Mamlūk-era buildings in Historic Cairo through the integrated IQAD-IAH framework, combining IoT field monitoring (January–December 2023) of temperature, relative humidity, CO₂, and PM2.5 with CNN-based deterioration image analysis and Random Forest predictive modeling. Results document critical summer thermal buffering failures reaching 28% of occupied hours above the ASHRAE 55 adaptive comfort limit; hygrothermal stress cycles exceeding the EN 15757 ±10% RH safe threshold for up to 38% of annual hours; and PM2.5 courtyard concentrations of 40–61 µg/m³ under normal conditions, surging to 180–320 µg/m³ during Ḫamāsῑn-seasonal wind events. Machine-learning projections indicate all three principal passive elements will cross the critical deterioration threshold of 70/100 under RCP 8.5 before 2050. A precautionary intervention window is identified between 2025 and 2032. Evidence-based management recommendations compatible with UNESCO World Heritage obligations are presented. Full article

Herringbone gear pairs are critical in high-speed aerospace transmissions, where windage power loss significantly impacts efficiency and thermal management. This study proposes a prediction method that decomposes the total windage loss into five components based on structural features: the tooth, end, circumferential, and relief groove surface losses for both gears, and the meshing extrusion loss. Theoretical models for each component are established to form a complete prediction method using fluid–structure interaction principles. CFD simulations analyze the velocity, pressure, and energy fields around the gear pair, with windage loss integrated via fluid torque on gear surfaces. Results indicate that windage loss escalates rapidly and becomes non-negligible when the driving gear speed exceeds 7000 rpm. The prediction model demonstrates strong agreement with CFD simulations, with a maximum relative error of 13.6%. Analysis reveals that the driving gear contributes the largest share of the total gear pair loss, with meshing extrusion accounting for 20.1–23.6%. For a single herringbone gear, the tooth surface is the primary source of loss (~83%), followed by the end surface (~8%), while relief groove and circumferential losses remain below 10%. This research provides a validated theoretical foundation for optimizing efficiency and thermal control in high-speed aerospace gear systems. Full article

Recently, a strain of Streptococcus agalactiae serotype Ia sequence type 7 clonal complex 1 (SaIa ST7 CC1) has emerged in Latin American tilapia aquaculture as an international threat. This study evaluated outbreaks of acute streptococcosis occurring between 2021 and 2025 on commercial Nile tilapia (Oreochromis niloticus) farms in six Latin American countries, aiming to integrate molecular, clinical, pathological, and environmental data. In total, 360 moribund or recently dead fish at various production stages (larvae/fry, pre-grow-out, and grow-out) were examined, and 25 S. agalactiae isolates were serotyped and subjected to real-time PCR analysis, multilocus sequence typing (MLST), virulence and antimicrobial resistance gene profiling, and antimicrobial susceptibility testing. All isolates belonged to SaIa and shared the same ST7 CC1 MLST profile, forming a highly homogeneous cluster with reference SaIa ST7 CC1 strains previously isolated from tilapia farms in Asia. These results are consistent with the regional spread of a single clonal line. At the larval and fry stages, SaIa ST7 CC1 was associated with hyperacute septicemia, gastrointestinal hemorrhage, and frequent intestinal intussusception, whereas in pre-grow-out and grow-out fish, neurological signs were more prominent, followed by ocular signs, systemic hemorrhages, and coelomic lesions. Histopathological examination showed profuse colonization of the brain, spleen, liver, and intestine by Gram-positive cocci, accompanied by marked acute circulatory and inflammatory lesions and few chronic granulomatous responses, consistent with a rapidly progressing, highly aggressive infectious process. All outbreaks occurred during extended periods of warm water (>32 °C), with large day–night thermal gradients and reduced dissolved oxygen, suggesting that thermal stress may exacerbate disease expression in affected systems. All SaIa ST7 CC1 strains exhibited phenotypic susceptibility to florfenicol and amoxicillin, whereas 84% (21/25) and 100% (25/25) exhibited intermediate susceptibility to oxytetracycline and enrofloxacin, respectively. In total, 5 of the 21 isolates (23.8%) with intermediate susceptibility to oxytetracycline carried tetracycline resistance genes (tetM, tetO). These findings identify SaIa ST7 CC1 as a clinically significant emerging threat associated with thermally facilitated and geographically expanding streptococcosis in tilapia production in Latin America. Immediate priorities include screening imported broodstock using MLST or whole-genome sequencing (WGS), harmonized regional molecular surveillance, climate-adaptive farm management practices, prudent antimicrobial use, and serotype-matched vaccination and breeding strategies that improve both disease and heat resilience. Full article

Urban water scarcity and climate change pose significant challenges for sustainable development, particularly in rapidly expanding metropolitan areas. In cities like Casablanca, these pressures also threaten the preservation of cultural heritage sites such as traditional public bathhouses (Hammams). This study investigates how Hammams can integrate sustainable water management solutions in alignment with Sustainable Development Goal 11 (SDG 11), focusing on the treatment and reuse of graywater. This study compares three graywater treatment systems, a Membrane Bioreactor (MBR), a Sequencing Batch Reactor (SBR), and a Moving Bed Biofilm Reactor (MBBR), evaluated through literature review and dimensioning calculations, and also integrates an existing treatment plant in Berlin that functions as a real-scale laboratory. The comparison is based on a set of technical, economic, and environmental criteria used for comparative engineering design assessment and evaluation for the selected Hammam water reuse applications. All systems are technically feasible but show distinct trade-offs. The SBR has the lowest energy demand and highest cost savings, the MBBR offers a compact and simple design, and the MBR provides the highest effluent quality at a higher energy cost. Heat recovery provides a significant thermal energy recovery potential but is reported separately from the electrical energy demand of the treatment systems. Full article

The use of entomopathogenic fungi as biological control agents has gained increasing relevance as a sustainable alternative to chemical insecticides in tropical agroecosystems. In this study, a naturally occurring isolate of Metarhizium brunneum infecting adults of Metamasius hemipterus was recovered from banana plantations in the Amazonas region, Peru, and evaluated for its potential as a biological control agent. Multilocus phylogenetic analysis based on tef1α, β-tubulin, rpb1, and rpb2 sequences confirmed its taxonomic identity within the M. brunneum clade. Physiological characterization revealed variability in growth and thermal response among isolates, while conidial production differed significantly depending on the substrate. Notably, isolate PM9 exhibited the highest conidial yield on rice substrate. Pathogenicity assays demonstrated high virulence against adult weevils, with an LC₅₀ of 2.91 × 10⁵ conidia·mL⁻¹ and mortality exceeding 90% at the highest concentration tested. These findings indicate that isolate PM9 combines desirable physiological and pathogenic traits for biological control. The natural occurrence of this entomopathogen in banana systems suggests ecological adaptation to local conditions and supports its potential incorporation into integrated pest management strategies, although further field-based evaluation is required. Full article