Search Results (3,699)

Aerial forest firefighting is a critical technology for wildfire suppression. Recent studies have examined suppression agent drop dynamics, deposition patterns, and optimization strategies. This review synthesizes advances from three perspectives: (i) in-flight suppression agent jet dynamics, (ii) ground deposition patterns, and (iii) suppression effectiveness, while outlining future research directions. Flight altitude, velocity, and momentum ratio govern jet behavior—affecting penetration, expansion, and breakup. Momentum ratio, shaped by drop velocity and aircraft speed, is pivotal in penetration depth and fragmentation. Deposition patterns vary with delivery systems and flight parameters: low-altitude/low-speed drops yield higher coverage density over smaller areas, whereas high-altitude/high-speed drops cover larger areas but less densely. Suppression efficacy depends on fire intensity–vegetation interactions, droplet size–coverage requirements, and operational parameters such as response time, aircraft capacity, and real-time intelligence. Large droplets excel in cooling high-intensity flames, while fine droplets provide efficient area coverage. Adequate resources and integrated data enhance outcomes. Future work should couple multi-physics models of terrain, meteorology, and fire plume dynamics, and develop integrated deposition models including wind, thermodynamics, terrain, and fire behavior to optimize aerial dispersion in diverse wildfire scenarios. Full article

The accurate and rapid prediction of hazard gas dispersion fields in urban environments is essential for guiding emergency sensor deployment and enabling real-time risk assessment. However, the computational cost associated with Computational Fluid Dynamics (CFD) simulations hinders their use as real-time forward models, while simplified Gaussian plume models lack the fidelity to resolve building obstruction effects. This study proposes a morphology-guided conditional Generative Adversarial Network (cGAN) framework designed to achieve real-time gas dispersion field modeling in urban environments with complex building configurations. The urban area is discretized into 50 × 50 m grid cells, each characterized by six morphological parameters describing building geometry. K-means clustering categorizes these cells into distinct morphological types. High-fidelity dispersion datasets are then generated for each type using Lattice Boltzmann Method (LBM) simulations. Each sample encodes building geometry, release location, wind speed, and time as multi-channel input images, with the corresponding gas dispersion concentration field is recorded as the output. Two cGAN architectures, Image-to-Image Translation (Pix2Pix) and its high-resolution variant (Pix2PixHD), are employed to learn the mapping from input features to dispersion fields. Model performance is evaluated using four complementary metrics: Fraction within a Factor of Two (FAC2) for prediction accuracy, Normalized Root Mean Square Error (NRMSE) for precision, Fractional Bias (FB) for systematic error, and Structural Similarity Index (SSIM) for spatial pattern fidelity. A case study is conducted across a 1176 km² urban district in China. The results demonstrate that under varying wind speeds (0.5–1.5 m/s) and temporal scales (5–60 s), and across five morphological categories, the Pix2PixHD-based model achieves 92.5% prediction accuracy and reproduces 97.6% of the spatial patterns. The proposed framework accelerates computation by approximately 18,000 times compared to traditional CFD, reducing inference time to under 0.1 s per scenario. This sub-second capability enables real-time concentration field estimation for emergency management, and provides a physically informed, computationally feasible forward model that can potentially support sensor-based gas source localization and detection network planning in complex urban environments. Full article

Understanding how climate change alters the thermal environment experienced by dairy cattle is critical for guiding adaptation in rapidly warming regions. Using meteorological data from 1961 to 2020, this study quantified long-term trends in temperature, precipitation, relative humidity, and wind speed across Jiangsu Province, China, and assessed their impacts on thermal stress using a temperature–humidity index (THI). The results reveal pronounced spatial heterogeneity in climatic change, with accelerated warming in southern and coastal prefectures, and continued winter cold stress in the northern plain. Over the past six decades, the annual number of heat-stress days (THI > 72) increased substantially and expanded northward, while cold-stress days (THI ≤ 38) declined but remained non-negligible in northern Jiangsu. Although the total number of thermally comfortable days changed little at the provincial scale, their seasonal distribution became increasingly compressed between longer summer heat-stress periods and shorter winter cold-stress windows, indicating a narrowing of the effective comfort range for dairy cattle. To link historical analysis with operational applications, a forecasting platform was developed to generate short-term predictions of THI and associated meteorological conditions, enabling spatially explicit visualization and early identification of periods with elevated thermal risk. Overall, these findings demonstrate an intensification and redistribution of thermal stress in Jiangsu, while also illustrating a transferable climate-risk mechanism relevant to other warming, humid dairy regions worldwide. Full article

Accurate wind power forecasting is essential for efficient wind farm operation and reliable grid dispatch. This study proposes a site-adaptive forecasting framework that integrates machine learning, Tree-structured Parzen Estimator (TPE)-based Bayesian hyperparameter optimization, and SHapley Additive exPlanations (SHAP) for interpretability. Using real-world meteorological and power generation data from two wind farms, we first perform joint-distribution feature analysis to characterize statistical relationships between key inputs and power output, supporting model development and interpretation. TPE optimization is then applied to six benchmark models (CatBoost, Extra Trees, GBM, LightGBM, TabNet, and XGBoost). The optimized Extra Trees model achieves the best performance at Site 1 (R² = 0.965, RMSE = 3.872 kW, MAE = 2.333 kW), whereas the optimized XGBoost model performs best at Site 2 (R² = 0.921, RMSE = 3.049 kW, MAE = 1.382 kW), demonstrating the effectiveness of TPE tuning and the strong predictive capability of tree-ensemble learners. SHAP analysis further reveals heterogeneous drivers across sites: Site 1 benefits from synergistic wind-speed contributions across multiple heights, while Site 2 is primarily governed by hub-height wind speed. Overall, the proposed framework achieves both high accuracy and robust interpretability for multi-site wind power forecasting. Full article

Long-term cold exposure reduces livestock welfare and productivity in Inner Mongolia. This study assessed cold stress effects on 60 two-month-old female Dorper × Mongolia lambs allocated to four sheltering conditions (n = 15): indoor pens with enclosed housing (IP), outdoor pens (OP), house with playground pens (OPP), and polytunnel pens (PP). Compared with IP, OP exhibited significantly lower temperature, humidity, CO₂ concentration, NH₃ concentration, and WCI, and significantly higher wind speed and solar radiant heat (p < 0.001). Humidity, CO₂ concentration, and NH₃ concentration in PP was lower than in IP, but higher than in OP (p < 0.001); temperature, wind speed, and WCI did not differ significantly between PP and IP. ADG was significantly lower in OP and OPP than in IP (p < 0.001), whereas PP did not differ from IP. F:G was higher in OP than in IP and PP (p = 0.040). Feeding duration had significant effects on ACTH, leptin, T₃, T₄, TP, urea, TG, NEFA, LDL, and HDL concentrations. Rearing environment significantly affected GLU, ALB, LDH, and TG. Feeding duration × sheltering conditions interaction significantly influenced ACTH, TP, ALB, urea, LDH, TG, LDL, and HDL. OP induced cold stress and dysfunction, while IP and PP produced milder responses. PP raised indoor temperatures substantially, and is thus optimal for winter lamb production. Full article

Prescribed burning is important for reducing wildfire risk and regulating fuel loads, but its implementation in mountainous forests is strongly influenced by the coupled effects of the wind field and topography, making it difficult to control. This study focuses on Yunnan pine (Pinus yunnanensis) forests in southwestern China. A three-dimensional Fire Dynamics Simulator (FDS) combined with measured fuel characteristics was used to simulate 21 slope (0–35°) and wind speed (0–2 m s⁻¹) combinations to quantitatively analyze the fire spread, flame structure, and gaseous emission characteristics during downslope prescribed burning. The local fire spread rate (ROS), evaluated along three lateral lines (Y = 2.5, 5.0, and 7.5 m), exhibits a non-monotonic dependence on slope over the tested range, with a minimum near 30° and a modest rebound at 35°. A downslope wind of 1 m s⁻¹ promotes near-surface heating and accelerates spread, whereas a stronger wind of 2 m s⁻¹ lifts flames away from the fuel bed and suppresses combustion. Thermal field analysis reveals that peak temperature decreases with increasing slope and that a late-stage secondary heating episode occurs at 35°. CO₂ emissions are significantly positively correlated with fuel consumption, reaching a peak of 717.5 kg under a 35° slope and no-wind conditions. CO emissions, as an indicator of combustion efficiency, reach their highest value of 2.23 kg at a 35° slope and a wind speed of 1 m s⁻¹, indicating that their trend is not entirely consistent with the ROS and temperature and that there is a certain degree of decoupling. The interaction between slope and wind speed transforms fire behavior from a cooperative to a competitive mechanism, and the topography–wind field coupling provides differentiated control over the combustion intensity and completeness. This study provides a scientific basis for the safe implementation of mountain burning programs and for regional carbon emission assessments. Full article

Wind energy stands as one of the most technologically mature renewable sources, playing a pivotal role in the mitigation of greenhouse gas emissions. However, wind farms and associated infrastructures increase collision risk for flying organisms. Implementing higher cut-in speeds is a proven mitigation strategy to significantly decrease wildlife mortality rates, particularly for bat species, by preventing turbine operation during low-wind periods of high activity. The suggested, non-standard, increased cut-in speed for wind turbines is generally 5.0 m/s. To test the effectiveness of cut-in speed increase, bat activity was monitored at three wind farms in northern Portugal (Gevancas, Azinheira, and Lagoa de Dom João e Feirão), to characterize spatial and temporal activity patterns and assess the potential associated risk. Ultrasonic acoustic detection was carried out at fixed stations, at heights of 55 m above ground level from March to October. Wind speed data were recorded concurrently using anemometers mounted on meteorological towers. Contradicting recommendations, the results show that significant bat activity might occur at wind speeds above the current curtailment values. Since turbine operation coincides with peak bat activity, it is imperative to implement site-specific mitigation strategies, such as optimized cut-in speeds, to minimize mortality risk. Full article

Micro-meteorological monitoring systems have been widely deployed in power grids, providing essential data to support the prevention and mitigation of ice- and wind-related disasters. However, understanding of the associated error mechanisms and quantitative evaluations under freezing rain and snow remains limited, particularly in complex field environments. This study presents a field-based quantitative assessment of two key variables, air temperature and wind speed, based on comparative observations collected over multiple winter icing cycles. We analyze the coupled effects of low temperature, ice accretion, and solar radiation on temperature measurements through multi-configuration sensor comparison, and characterize the dynamic response of cup anemometers under icing conditions using cross-correlation lag analysis. Results show that temperature error is dominated by sensor installation configuration and solar radiation. Under weak solar radiation, unshielded sensors tend to record lower temperatures than a standard Stevenson screen, but once radiation exceeds 200 W/m², they warm rapidly and exhibit maximum positive biases of ~8–10 °C. Ice accretion further induces a cold bias of ~1 °C and a response lag of 5–18 min, while suppressing the rapid warming driven by shortwave radiation. For wind measurements, cup anemometers show clear underestimation during ice accretion, with the error increasing nonlinearly with ice thickness to ~20% before freezing-induced failure occurs. These findings provide a basis for improved sensor deployment and interpretation of field monitoring data in cold, humid, and icing-prone environments, although the quantitative results are site-dependent. Full article

The resolution and accuracy of airborne/spaceborne SAR are continuously improving, making it an effective means for observing ocean dynamic processes and detecting marine targets. In contrast, utilizing its unique orbital angular momentum (OAM) mode, vortex radar does not require temporal accumulation to achieve azimuthal resolution, making it particularly suitable for observing moving sea surfaces. This capability enables stable and continuous monitoring of dynamic ocean scenes. This paper proposes a vortex radar imaging method based on three-dimensional sea surface scattering characteristics: first, a three-dimensional wind-driven sea surface geometric model is established based on the Elfouhaily sea spectrum, and its scattering characteristics under different incident angles, wind speeds, and wind directions are analyzed using the semi-deterministic facet-based two-scale method; then, two-dimensional range-azimuth imaging is achieved through coordinate transformation, echo modeling, pulse compression, and fast Fourier transform (FFT) in OAM mode domain, with the correctness of the imaging algorithm verified through multiple point target imaging results. Finally, simulation results of two-dimensional sea surface vortex imaging under different incident angles are presented, and the influence of wind speed and direction on sea surface vortex imaging is analyzed. The study shows that the vortex imaging system can effectively reflect wave fluctuations and wind direction characteristics, demonstrating the feasibility and potential of vortex radar imaging in oceanographic applications. Full article

The prediction of dynamic responses of offshore wind turbine foundations under wind-wave-current multi-field coupled loads is the cornerstone of safety in offshore wind power engineering. The currently widely adopted equivalent load application method, while computationally efficient, simplifies loads into concentrated forces applied at the pile top and tower top, neglecting fluid-structure dynamic interaction mechanisms, which leads to deviations in response predictions. To overcome this limitation, this paper proposes a high-precision bidirectional fluid-structure interaction numerical framework. The fluid domain employs computational fluid dynamics (CFD) to construct an air-seawater two-phase flow model, utilizing the standard k-ε turbulence model and nonlinear wave theory to accurately simulate complex marine environments. The solid domain establishes a wind turbine-stratified seabed system via the finite element method (FEM), describing soil-rock mechanical properties based on the Mohr-Coulomb constitutive model. Comparative studies indicate that the equivalent static method significantly underestimates the displacement response of pile foundations, particularly under the extreme shutdown conditions examined in this study. This value should be interpreted as a case-specific observation rather than a universal deviation, and the discrepancy may vary with sea state, wind speed, current velocity, and wind–wave misalignment, thereby leading to non-conservative estimates of stress distribution. In contrast, the fluid-structure interaction method can reveal key physical processes such as local flow acceleration and wake–interference effects around the tower and the parked rotor under shutdown conditions, and the nonlinear interaction and resistance-increasing mechanisms between waves and currents. This model provides a reliable tool for safety assessment and damage evolution analysis of wind turbine foundations under extreme marine conditions, promoting the transformation of offshore wind power structure design from empirical formulas to mechanism-driven approaches. Full article

High-speed operation is a key pathway to higher power density in modern EV traction systems, and multi-parameter optimization is essential for enhancing its high-speed performance. This study investigates a 20,000 r/min interior double-V permanent-magnet flat-wire motor via finite-element simulations to systematically examine the effects of multiple interacting parameters—including flat-wire layer number, stator slot geometry, magnet grade, and rotor magnetic barrier angle—on the electromagnetic performance under high-speed operating conditions. The results indicate that increasing winding layers significantly reduces high-speed torque; an eight-layer design decreases torque by about 50% compared to a four-layer one, while a six-layer arrangement offers a favorable torque-loss trade-off. Wider slots lower the average torque but reduce torque ripple by approximately 27%, whereas deeper slots increase tooth flux density and reduce efficiency. Higher-grade magnets enhance air-gap flux and torque at elevated cost. Rotor magnet angle optimization reveals a trade-off between peak torque and ripple, with a symmetric 100°/100° design achieving balanced performance. These findings clarify structural–control interactions and support the multi-objective design of high-speed flat-wire permanent-magnet motors. Full article

Dust pollution induced by blasting during tunnel construction via the drill-and-blast method poses a severe threat to workers’ health and construction safety. To address this issue, a wet chord grid dust removal and purification device adaptable to deep-buried long tunnels was developed in this study. The device integrates dust control and removal functions, featuring mobility, high purification efficiency, and water recycling capability. Through experimental tests, the optimal operating parameters of the system were determined: the dust removal efficiency reached a peak of 94.3% (laboratory optimal value from the basic parameter optimization test) when the frequency of the extraction axial flow fan was set to 30 Hz and the cross-sectional wind speed of the chord grid reached 3.34 m/s. The circulating water tank achieved the optimal water treatment performance under the conditions of a relative buried depth of 0.42 for the water inlet, a volume ratio of 1:2 for the sedimentation area to the clear water area, and a relative baffle height of 0.65. Numerical simulations based on CFD software (2021) revealed that the on-site dust removal efficiency of the device reached 79.86% and 87.9% under the working conditions where the tunnel face was 10 m and 100 m away from the connecting passage, respectively, which are in good agreement with the field measurement results. In the practical application at the Shierpo Tunnel of the Guangxi Tianba Expressway, the device achieved an average total dust removal efficiency of 78.4%, with 81.2% removal efficiency for PM₁₀ and 76.5% for PM_2.5, demonstrating excellent engineering applicability and dust removal performance for respirable dust. This study provides effective technical support and a theoretical basis for improving the construction environment of drill-and-blast tunnels. Full article

Unbalance diagnosis for non-constant speed systems is challenging because the 1X fundamental rotational harmonic magnitude, commonly used as an unbalance indicator, depends on shaft rotational speed. This dependency makes it difficult to separate speed effects from unbalance effects. It has been shown that 1X magnitudes become speed-invariant if they are normalized with respect to the rotational speed in power four for variable-speed wind turbines. However, the applicability of this diagnostic technology to dual-speed machines remains unclear. This study experimentally investigates unbalance diagnosis technologies for dual-speed wind turbines, for which speed-dependent interference is present. Vibration data are collected from the main bearings of two dual-speed wind turbines. Novel residual-based, speed-invariant unbalance diagnostic technology is proposed. The experimental results show consistent statistical distributions of the new diagnosis indicator across low and high-speed operating regimes. These findings confirm the suitability of the proposed technology for unbalance diagnosis for dual-speed rotating machinery. Full article

Airborne microbial contamination in dairy cattle housing is strongly influenced by housing conditions and management practices. This study evaluated the influence of environmental and housing parameters on total bacterial, coliform, and mold levels across four dairy farms. Microclimatic variables, including temperature, relative humidity, wind speed, bedding moisture, air volume per cow, particulate matter (PM₁, PM_2.5, PM₁₀), and total volatile organic compounds (TVOCs), were measured. Comparative analyses showed that air volume per cow and bedding moisture were consistently associated with variability in total microbial and mold counts, while particulate matter and wind speed were linked to differences in airborne coliforms. Generalized linear mixed models indicated that most environmental variables did not have statistically significant effects, with the exception of farm type for coliforms and temperature for molds. The predominance of non-significant environmental effects, together with more consistent differences observed between farms, suggests that variability in airborne microbial levels is more strongly associated with farm-specific management and housing characteristics than with individual environmental parameters. Overall, the findings highlight the combined influence of housing design, management practices, and environmental conditions, emphasizing the importance of optimized ventilation and bedding management to improve air quality in dairy cattle housing. Full article

The offshore wind energy sector requires efficient logistics to retrieve generated electricity using maritime mobile energy storage systems. This study addresses the maritime mobile energy storage scheduling problem to maximise the total net energy delivered to the onshore grid. The proposed approach utilises a mixed-integer linear programming framework. The mathematical formulation integrates a replicated port node mechanism to plan multi-trip operations over a continuous planning horizon. Additionally, the model accounts for energy transfer loss coefficients and incorporates a speed discretisation strategy to balance propulsion consumption against retrieved electricity. Numerical experiments based on simulated operational scenarios demonstrate the effectiveness of this method. The results indicate that expanding vessel storage capacity from 500 to 600 megawatt-hours eliminates the necessity for multi-stop trips, thereby reducing propulsion energy consumption from 270.79 to 73.65 megawatt-hours. Furthermore, increasing the fleet size from five to six vessels enables the full retrieval of available offshore electricity while decreasing fleet propulsion consumption to 91.08 megawatt-hours. The solver consistently achieves optimal solutions within an average of 0.88 s. Consequently, this framework provides operators with precise decision support for determining fleet capacity and configuring offshore energy retrieval networks. Full article