Search Results (746)

Under the background of the green transformation and energy conservation in the aviation field, hydrogen-fueled aero-engines are the primary direction for achieving sustainable aviation power development. However, the unique thermophysical properties of hydrogen fuel induce extreme thermal load challenges to engine thermal management. Based on the requirements of energy conservation and digital-intelligent technologies, this paper reviewed the recent research progress, important challenges, and future development directions in the thermal management field for hydrogen-fueled aero-engines, and filled the gaps in existing related reviews. (1) As for the liquid hydrogen thermal properties and thermal management requirements, the unique thermal physical properties of liquid hydrogen can easily cause fluctuations in heat load, large temperature differences, and material compatibility issues such as hydrogen embrittlement during storage, transportation, and combustion. The application of thermal barrier coatings, the design of targeted cooling structures, and the regulation of heat loss in the pipeline of the hydrogen supply system require particular attention. (2) As for the technical architecture and optimization of thermal management, the optimization of the high-pressure side manifolds in the cooled cooling air heat exchanger increases the flow uniformity by 18.8% and reduces the weight by 22.5%. The intercooled recuperated engine with the optimum area ratio reduces specific fuel consumption by 5.3% compared to the baseline engine in cruise. However, the system-level optimization research of the above widely recognized solutions is relatively limited in terms of coordinating the energy flow of engines. The baseline engine employed the method of system integration optimization to achieve a 2.99% increase in thrust and a 6.78% reduction in fuel consumption. (3) As for the thermal management modeling and simulation, the intelligent optimization method based on computational fluid dynamics reduces the pressure loss coefficient of the vane-integrated heat exchanger by 36%. Nevertheless, the multiphysics coupling model confronts a contradiction between computational cost and accuracy. (4) As for the comprehensive evaluation method, the advanced configuration of the hydrogen-fueled aero-engine can approximately reduce specific fuel consumption by 68.5% and NOx emission by 12.7% under the same maximum thrust condition. The hydrogen consumption of the proton exchange membrane fuel cells system model compared with the baseline system, optimized by the multi-objective optimization algorithm, has decreased by 15%, while the thermal uniformity has improved by 20–30%. However, the current evaluation system mostly focuses on a single dimension, lacking the analysis of nonlinear coupling among multiple factors and a closed-loop mechanism for evaluation, optimization, and verification. Future research should focus on the matching model of liquid hydrogen’s thermophysical properties and full flight conditions, global multi-energy flows optimization methods, multidimensional collaborative numerical simulation, multiphysics coupling models, and multidimensional comprehensive evaluation systems, to provide closed-loop theoretical support for the efficient, intelligent, and reliable thermal management system for hydrogen-fueled aero-engines. Full article

Reference evapotranspiration (ET₀) represents the atmospheric demand for water from a well-watered vegetated surface and is a key component of the hydrological cycle and agricultural water management. This study evaluated the performance of seven machine learning (ML) models: linear regression (LR), Random Forest (RF), Support Vector Machines (SVM), K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), Decision Trees (DT), and Cubist, for predicting monthly FAO-56 Penman–Monteith ET₀ in Benin. The target variable was calculated from data collected at six synoptic stations over the 2017–2021 period. Ten remote-sensing and topographic predictors were used: MODIS Land Surface Temperature (LST), six Sentinel-2 optical vegetation indices (NDVI, EVI, NDMI, NDWI, MSI, NDRE), elevation, and cyclic month encoding. Models were trained on the 2017–2019 period and evaluated on an independent temporal test set (2020–2021). All models showed positive predictive performance, with the BMA ensemble achieving the highest accuracy (RMSE = 7.0% of mean ET₀, R² = 0.802), followed by Cubist (RMSE = 7.3%, R² = 0.787) and DT (RMSE = 7.5%, R² = 0.776). The seven models were combined via Bayesian Model Averaging (BMA) with posterior weights estimated by the EM algorithm to produce 1 km monthly ET₀ maps for Benin for 2025. BMA-derived inter-model standard deviation provided spatially explicit uncertainty estimates, revealing that prediction uncertainty is greatest in the northern Sudanian zone during the dry season. The ET₀ target variable was constructed as a hybrid product combining station temperature observations with solar radiation, wind speed, and vapor pressure deficit extracted from the TerraClimate gridded reanalysis dataset; this methodological choice is discussed as a study limitation. Full article

This study investigated indoor environmental air quality (IEAQ) across university workspaces at a higher education institution in Sharjah, United Arab Emirates (UAE), assessing environmental conditions that may influence occupant health, the surrounding environment, and sustainability. Physical parameters (temperature, relative humidity, noise, and illuminance), chemical parameters (indoor gases and particulate matter), and biological contaminants (airborne bacteria and fungi) were measured in semi-occupied indoor environments with a total of 68 random samples collected and analyzed. Perceived heat discomfort and environmental variability were assessed using the Thom Discomfort Index (TDI), Humidex Index, ANOVA, Kruskal–Wallis, Mann–Whitney U, and one-sample t-tests. Average measurements of relative humidity, temperature, noise, and illuminance were 60.7%, 21.6 °C, 57.5 dB, and 440 lux, respectively. Average concentrations of PM_2.5, PM₁₀, CO, and CO₂ were 1223 ppm, 104 ppm, 1 ppm, and 623 ppm, respectively. Microbial contamination was generally insignificant across most investigated workspaces. While most measured parameters remained within recommended threshold limit values (TLVs), elevated levels of noise, illuminance, and particulate matter were observed in selected workspaces. These findings demonstrate that university indoor environments generally maintain acceptable air quality conditions; however, targeted interventions, including improved HVAC maintenance and indoor pollutant management, are required to enhance sustainable university indoor environments and optimize occupant comfort. Full article

Urban soils act as sinks for polycyclic aromatic hydrocarbons (PAHs) indicating the intensity of the anthropogenic load, while potential environmental and human health concerns may arise. In the present study, the concentrations, spatial distribution, source apportionment and potential health risks of 16 priority PAHs were investigated in urban soils from the city of Thessaloniki, Northern Greece. Surface soil samples were collected from 19 locations characterized by different land uses and traffic conditions. The total levels of the 16 PAHs exhibited substantial variability, with a range of 14.09–1565.4 μg kg⁻¹, reflecting heterogeneous contamination patterns across the city. PAH profiles were dominated by high-molecular-weight compounds (4–6 rings) accounting for over 80% of the total PAHs. Diagnostic molecular ratios highlighted pyrogenic sources, verifying that high-temperature combustion processes dominated the PAH inputs in the urban soils from Thessaloniki city. The factor score plot made prominent the presence of localized contamination hotspots in areas characterized by intense and continuous traffic activity, spotlighting vehicular traffic emissions and transport-related activities as primary sources of PAHs in the study area. Carcinogenic risk assessment based on the BaP-EQ approach indicated acceptable risk levels for most of the sampled soils, although limited localized hotspots with elevated carcinogenic risk were identified. This study provides important baseline information for understanding PAH contamination in urban environments and supports the development of targeted pollution mitigation and environmental management strategies. Full article

Wildfire regimes in mountain forest landscapes are shaped by complex interactions among topography, climate, vegetation, and human activity. However, predicting and interpreting fire occurrence in topographically heterogeneous regions remains challenging because fire–environment relationships vary strongly across elevation gradients and temporal scales. This study developed a hybrid machine-learning framework integrating an Information Value Model (IVM), Random Forest (RF), and Convolutional Neural Network (CNN) to decode elevation-mediated wildfire regimes in western Sichuan, China, a mountainous forest region characterized by strong vertical environmental gradients and high ecological conservation value. Multi-source datasets, including Moderate Resolution Imaging Spectroradiometer (MODIS) burned-area records, topographic variables, monthly meteorological data, vegetation indices, land-cover information, and human-accessibility proxies, were integrated at a 500 m spatial resolution. Environmentally comparable non-fire samples were generated from unburned vegetated pixels, and model training, RF-based feature selection, hyperparameter tuning using Particle Swarm Optimization (PSO), and performance evaluation were conducted within a nested spatial block cross-validation framework. The model produced continuous wildfire occurrence probabilities and showed strong discriminatory performance under the adopted validation protocol, with AUC values exceeding 0.95 across temporal datasets and low probability-error metrics. RF importance and correlation analyses identified mean temperature, elevation, and precipitation as the dominant predictors of wildfire probability. Spatial analyses revealed pronounced elevation-mediated differentiation in wildfire regimes: low-elevation valleys showed higher fire probability and stronger associations with human-accessibility proxies, whereas high-elevation plateau areas exhibited lower and more scattered fire patterns associated with climatic constraints. Seasonal and monthly analyses further showed that winter and spring fires dominated the regional fire regime, with risk intensifying during the pre-monsoon dry period. By combining probabilistic fire-risk mapping, spatial-context learning, and elevation-gradient interpretation, this study provides a transferable framework for understanding wildfire regimes in complex mountain forest landscapes. The findings support adaptive forest fire management, targeted monitoring, and risk zoning in mountainous regions where forest ecosystems, human activities, and conservation values intersect. Full article

Net primary productivity (NPP) is a key indicator of the carbon sequestration capacity of terrestrial ecosystems, and its dynamics are jointly influenced by climate change and human activities. However, quantitatively disentangling their respective contributions and clarifying their non-linear interactions remains challenging. In this study, remote sensing, meteorological, and anthropogenic data were integrated to investigate the spatiotemporal dynamics of vegetation NPP in the Yellow River Basin (YRB) from 2000 to 2024. Six scenarios were constructed to quantify the relative contributions of climate change and human activities. Furthermore, an XGBoost-SHAP framework was employed to elucidate the underlying non-linear driving mechanisms. The results indicate that vegetation NPP exhibited a significant increasing trend over the study period, with a rapid recovery phase after 2012 and a peak in 2024 (351.75 gC·m⁻²·a⁻¹), representing a 71.43% increase compared with the baseline period. Spatially, the upper reaches were primarily climate-driven (58.74%), the middle reaches showed a strong synergistic effect between climate and human factors (97.41%), while the lower reaches were dominated by human activities (73.02%). The XGBoost-SHAP analysis identifies land surface temperature (LST) as the primary moderator of carbon sequestration across river basins (mean SHAP > 12.0). The driving mechanisms exhibit a clear longitudinal shift, transitioning from a heat-dominated regime in the upper reaches to a complex interplay of precipitation and intense urbanization in the middle and lower reaches. These non-linear interactions reveal critical feedback loops between natural hydrological constraints and urban expansion pressures. These findings clarify the drivers of regional carbon sequestration, providing a scientific basis for targeted ecological management and carbon neutrality strategies in the YRB. Full article

Total ammonia nitrogen (TAN) is a ubiquitous and critical pollutant in global surface waters. In China, regulatory oversight largely relies on static standard limits, often overlooking the influence of environmental factors on ammonia toxicity. Based on large-scale monitoring data from seven major river basins across China from 2021 to 2024, this study employed pH- and temperature-dependent Local Water Quality Criteria (LWQC) to identify the spatiotemporal decoupling between TAN concentrations and Risk Quotients (RQs). The results reveal a “double-peak” seasonal pattern in TAN concentrations nationwide, namely a primary peak in winter (December to February) and a secondary peak in summer (June to August), driven by low flow during the dry season and rainfall-induced non-point source runoff, respectively. Crucially, the study confirms a significant “concentration-risk paradox”: while TAN concentrations are highest in winter, ecological risk remains at an annual low due to the protective effect of low temperatures on toxicity. Conversely, despite lower total concentrations in summer, high temperatures and elevated pH trigger a sharp decline in LWQC and a surge in the proportion of highly toxic un-ionized ammonia (NH₃), marking summer as the peak period for ecological risk. Comparative analysis indicates that approximately 61.43% of river sections meeting the current Grade III water quality standards remain in a high-risk state. This underscores the inadequacy of static standards in providing sufficient protection during sensitive seasons. We suggest that water environmental management should shift from “concentration-based compliance” to “risk-based management,” implementing differentiated TAN control strategies specifically targeting the sensitive summer window. Full article

Tritium breeding blanket is a key component of future fusion power plants, and its performance depends on the selection, fabrication, and qualification of lithium-based ceramic material. Among the proposed lithium ceramics materials, the main candidates for ceramic breeders are lithium orthosilicate (Li₄SiO₄) and lithium metatitanate (Li₂TiO₃). These advanced ceramics and their biphasic composites are the leading candidates due to their high lithium density, favorable tritium breeding ratio (TBR ≈ 1.15–1.25 with Be₁₂Ti multiplier and 90% ⁶Li enrichment), and robust thermo-mechanical behavior within the 200–900 °C operational window of helium-cooled pebble bed (HCPB) blankets. This review provides an engineering-oriented assessment covering fabrication routes (solid-state, hydrothermal, melt-based, drip casting, powder injection molding, microwave sintering, and digital light processing additive manufacturing); microstructure–property relationships and performance under neutron irradiation; and tritium generation, retention, and release as functions of chemical composition, defect structure, and operating temperature. Induced radioactivity of Li-based ceramics and key impurity elements is quantified using activation formalisms applied to WWR-K reactor conditions, providing guidance for raw-material selection and waste-management assessment. Authors’ original contributions include (i) an empirical model of pebble crush load vs. biphasic composition (R² > 0.99); (ii) two universal semi-empirical kinetic models (exponential growth and non-linear strength degradation, R² = 0.97–0.99) for nine structural and mechanical parameters of Li₂TiO₃ under He²⁺ and H⁺ irradiation; (iii) a consolidated table of Arrhenius tritium diffusion parameters from reactor experiments and DFT; and (iv) an induced radioactivity calculation for the biphasic system with two-exponential post-irradiation decay analysis. The review identifies biphasic Li₄SiO₄–Li₂TiO₃ composites with ~30 ± 5 mol.% Li₂TiO₃ as particularly promising and formulates specific data gaps and modeling needs for the reliable deployment of ceramic breeder pebbles in helium-cooled fusion blanket systems. It should be specifically noted that Li₄SiO₄ pebbles fabricated via the melt method, as an example, typically exhibit exceptionally high densities, generally exceeding 90% of the theoretical density (TD). Building on the calculation of induced radioactivity, it is crucial to consider the microstructural distribution of highly radioactive nuclides (e.g., Co, Mn) within the ceramic matrix. If these impurities segregate at grain boundaries rather than being homogeneously distributed, there is a potential pathway to develop targeted wet-chemical methods, such as selective acid leaching, to remove these impurities post-irradiation, thereby lowering the waste disposal classification. Full article

Decarbonizing heavy-duty logistics requires powertrains that integrate novel topology design, degradation-aware optimization, and robust dynamic performance under real-world operational loads. While solid oxide fuel cells offer high efficiency, their application in transportation is hindered by thermal fatigue. This study proposes a novel hybrid powertrain topology integrating a metal-supported solid oxide fuel cell (SOFC), a micro gas turbine (MGT), and an aluminum–silicon phase change material (PCM) thermal buffer. A high-fidelity dynamic model is developed and coupled with a multi-objective optimization framework to size the PCM buffer and battery pack, balancing capital expenditure and system lifetime. Furthermore, a degradation-aware energy management strategy based on a thermal state-of-charge metric is introduced. Simulations over a 10 h dynamic drive cycle indicate that the optimal configuration (120 kg PCM, 80 kWh battery) extends the SOFC’s simulated remaining useful life to 38,400 h, a 2.5-fold improvement over unbuffered systems. Concurrently, the proposed energy management strategy reduces the MGT mechanical wear index by 98% compared to conventional load-following strategies. The system demonstrates robust performance across ambient temperatures from −20 °C to +45 °C and achieves a 22% reduction in projected capital expenditure compared to standard proton exchange membrane fuel cell powertrains. This topology offers a highly durable and economically viable pathway for next-generation zero-emission heavy-duty vehicles. This work addresses a critical gap in the literature: the lack of integrated thermal buffering and degradation-aware control strategies for high-temperature fuel cell systems in dynamic vehicular applications. By coupling a physical latent heat buffer with a novel Thermal-SOC-proportional Energy Management Strategy, the proposed architecture directly targets the primary degradation mechanisms that have historically impeded SOFC commercialization in heavy-duty transport. Full article

The increasing demand for lithium-ion batteries (LIBs) raises concerns about the security of critical raw material supply and the management of hazardous waste. Efficient recycling can alleviate these issues by transforming spent batteries into high-value secondary materials for the circular economy. Industrial recycling has traditionally focused on the recovery of nickel (Ni) and cobalt (Co), whereas lithium (Li) recovery has often been sidelined due to technical complexities and fluctuating economic incentives. To meet the European Union (EU) Batteries Regulation target of 80% lithium recovery by the end of 2031, technically effective and economically viable lithium recovery strategies are required. This study investigates the use of food-grade sucrose as an organic reductant for the targeted recovery of lithium from NMC622 and NCA battery materials. The process combines sucrose-assisted reductive roasting with selective water leaching. The effects of roasting temperature, holding time, sucrose dosage, and heating rate were systematically evaluated and optimised. Under the best conditions of 600 °C, 15 min, 15 wt% sucrose, and a heating rate of 20 °C/min, lithium leaching efficiencies of 93.2% and 87.6% were achieved for separated NMC622 cathode material and NMC622-derived black mass, respectively. The method was also applicable to NCA-based black mass, reaching 83.7% lithium recovery under the same conditions. Mechanistic analysis revealed that lithium release was strongly controlled by the extent of transition metal reduction. Cobalt was fully reduced to its metallic state under all tested conditions. However, maximum lithium recovery required nickel to be reduced to metallic Ni and manganese-containing phases to be converted to MnO. The sucrose-assisted roasting process was rapid and holding times longer than 15 min decreased lithium recovery. This decrease was caused by the formation of poorly soluble lithium-containing phases, such as LiF and Li₃PO₄. F composition analysis showed the black mass (1.06 wt%) and anode fractions (2.26 wt%) to contain significantly more F than the cathode fraction (0.46 wt%), hence leading to the 5% Li leaching efficiency difference between cathode and black mass fractions under most conditions tested. Overall, these results demonstrate that sucrose-assisted reductive roasting, followed by selective water leaching, provides a rapid and effective route for high-efficiency lithium recovery from NMC- and NCA-based battery materials. Full article

Heat stress is a major constraint on poultry productivity in tropical environments, where persistent high temperature and humidity intensify its negative effects on production traits. In this study, we quantified the relationship between thermal load and monthly egg production in black-boned and Thai native chickens and developed a refined temperature–humidity index intended to improve the assessment of heat stress under tropical conditions. A large dataset comprising 136,816 monthly egg production records from 11,530 birds was analyzed using regression models and seven THI equations. The results confirmed that heat stress significantly reduces monthly egg production, while conventional indices showed only moderate explanatory power. In contrast, the refined index consistently improved model performance, providing modest improvements in model fit compared with the original formulation. Notably, genotype-specific responses were identified, with Thai native chickens exhibiting greater tolerance to elevated thermal conditions. Distinct heat stress thresholds were also established, with values of 72 for black-boned and 74 for Thai native chickens. These findings highlight the environmentally sensitive nature of monthly egg production traits and demonstrate that targeted refinement of thermal indices enhances the detection of heat stress effects. This study provides a practical framework for integrating environmental indicators into management and breeding strategies aimed at improving thermal resilience in poultry systems. Full article

Accurate prediction of the potential habitat distribution of Scomber japonicus, an important target species in China’s distant-water fisheries, is essential for fishing ground forecasting. Using catch data for S. japonicus collected from Chinese large-scale purse-seine and trawl fisheries in the Northwest Pacific Ocean from May to November during 2015–2024, this study applied the maximum entropy model (MaxEnt) and the genetic algorithm for rule-set production (GARP) model to predict the potential habitat distribution of S. japonicus in the Northwest Pacific Ocean. The area under the receiver operating characteristic curve (AUC) and the true skill statistic (TSS) were used to evaluate model performance. The MaxEnt model predicted a relatively concentrated highly suitable habitat, whereas the GARP model identified a broader highly suitable area. To reduce the bias and uncertainty associated with single-model predictions, the outputs of the MaxEnt and GARP models were integrated using a weighted ensemble approach, with the optimal weights for MaxEnt and GARP determined as 0.7:0.3. The ensemble model achieved higher predictive performance, with an AUC of 0.983 and a TSS of 0.840. The highly suitable habitat of S. japonicus was mainly concentrated within 147° E–156° E and 40° N–44° N. Chlorophyll concentration, sea surface temperature (SST), and temperatures at depths of 150 m and 200 m were the main environmental variables affecting the potential habitat distribution of S. japonicus in the MaxEnt model. These findings provide useful information for resource utilization, fishing ground forecasting, and sustainable management of S. japonicus in the high seas of the Northwest Pacific Ocean. Full article

Heatwaves and tropical nights are emerging as significant public health challenges under accelerating climate change, with middle-aged and older adults demonstrating heightened vulnerability. This scoping review maps the existing evidence on how nocturnal heat affects sleep in middle-aged and older adults aged 45 and above, synthesizing findings from experimental and observational studies published in English over the past decade. A comprehensive search of PubMed and Scopus, supplemented by reference screening, identified 31 relevant studies. Data on study design, population characteristics, heat exposure metrics, sleep outcomes, and interventions were charted and synthesized narratively due to methodological heterogeneity. Across studies, elevated nighttime temperatures consistently reduced total sleep time and sleep efficiency, increased wake after sleep onset, and disrupted sleep architecture, particularly REM and N3 stages. Environmental, behavioral, and physiological interventions such as improved ventilation, targeted cooling strategies, and pre-sleep thermal management partially mitigated heat-related sleep disruption. Overall, the findings highlight gaps in standardized exposure metrics and harmonized sleep assessment, providing guidance for future research and public health strategies aimed at protecting sleep health in middle-aged and aging populations amid increasingly frequent extreme heat events. Full article

Background: The lactate-to-albumin ratio (LAR) and C-reactive protein-to-albumin ratio (CAR) are biomarkers for metabolic stress and inflammation. However, their prognostic significance after return of spontaneous circulation (ROSC) in out-of-hospital cardiac arrest (OHCA) remains unclear. Therefore, this study aims to investigate the association between serial LAR/CAR measurements and in-hospital mortality. Methods: This retrospective observational cohort study included adult comatose patients with OHCA treated with targeted temperature management between January 2022 and December 2025. Serum lactate, albumin, and C-reactive protein levels were measured at admission and at 24, 48, and 72 h after ROSC. The primary outcome was in-hospital mortality. Multivariable logistic regression analyses were performed to assess independent associations of LAR and CAR with in-hospital mortality, and discriminatory performance was assessed using the area under the receiver operating characteristic curve (AUC). Results: Of the 284 eligible patients, 253 were included in the final analysis. Of these, 80 patients died in hospital, corresponding to an in-hospital mortality rate of 31.6%. LAR and CAR were significantly higher in non-survivors than in survivors at admission and at 24, 48, and 72 h after ROSC. After adjustment for potential confounders, LAR was associated with in-hospital mortality at all assessed time points. CAR was independently associated with in-hospital mortality at admission and at 48 and 72 h after ROSC, but not at 24 h. The AUCs of LAR for predicting in-hospital mortality ranged from 0.702 to 0.734, whereas those of CAR ranged from 0.640 to 0.690. Conclusions: In this single-center retrospective cohort of post-ROSC OHCA patients, sequential tracking of LAR and CAR profiles during the first 72 h after ROSC provided meaningful insights into in-hospital mortality. LAR showed a more consistent independent association with mortality and fair discriminatory performance, whereas CAR demonstrated limited prognostic value despite its association with mortality. Full article

Meeting the rigorous performance standards of modern electrified transit necessitates the deployment of high-performance outer rotor PMSMs with elevated power-to-volume ratios. However, their unique internal heat source topology inherently restricts heat dissipation. This limitation risks permanent magnet demagnetization and winding insulation failure. To address these thermal bottlenecks, this paper proposes internal bio-inspired cooling channels. These channels feature micro-scale V-shaped ribs. This design targets a 60 kW outer rotor PMSM. The motor uses a fractional-slot concentrated winding. The analytical procedure commences with the formulation of a transient 2D numerical model utilizing the Time-Stepping Finite Element approach (TS-FEM). It is coupled with the Bertotti model to compute electromagnetic losses. This approach accurately determines losses under high-frequency rated conditions. Results reveal that stator iron loss constitutes the dominant heat source. It accounts for 76.4 percent of the total electromagnetic loss. Furthermore, these losses show severe spatial concentration at the stator teeth. Subsequently, a three-dimensional fluid-solid coupled CFD model is developed. This model evaluates the proposed internal cooling channels. The design integrates bio-inspired vein networks and V-shaped ribs. These internal ribs disrupt the near-wall thermal boundary layer. This disruption enhances the local convective heat transfer. Comparative multiphysics analyses indicate improved hydraulic and thermal performance of the bio-inspired design under the same numerical boundary conditions. The bio-inspired channel achieves a more uniform static pressure distribution and reduces severe fluid stagnation zones. In the numerical model, the maximum stator and permanent magnet temperatures are reduced to 48 °C and 42 °C, respectively. This work provides a numerical design reference for thermal management in high-performance electric aviation. Full article