Search Results (533)

This article analyzes the applications of computational fluid dynamics (CFD) in addressing the issue of flow patterns in a realistic urban landscape, specifically in the Metropolitan Area of Monterrey. CFD enables the simulation of physical phenomena such as turbulence, which is useful for studying the transport behavior of pollutants in urban environments. The computational model was obtained from satellite imaging and covered a surface of about 1.134 km × 1.227 km. It was composed of 173 urban blocks, representing around 3570 houses, including hospitals, schools, recreation centers and other gathering places. The population of the urban landscape was estimated at around 11,400 inhabitants. Three velocity scenarios, low, average, and high (air gusts), were simulated, using data from a local weather station. The Reynolds numbers (Re) ranged from 1.9 × 10⁶ to 21.2 × 10⁶, falling within the fully developed turbulence regime, which was modeled using the renormalization group (RNG) k–ε turbulence model. Results showed that the mean velocity patterns were preserved independent of the Reynolds number (Re) and were characterized by regions of high velocity in the main avenues, as well as other regions of low velocity between urban blocks. This methodology may also be applicable for understanding the flow patterns of similar urban regions composed of irregularly arranged low-rise blocks. Full article

A two-dimensional ultrasonic anemometer was installed at a height of 20 m on a wind measurement tower in Haiyan Town, Jiangmen, to monitor flow conditions in typhoon Mangkhut (1822) before and after landfall. Mean wind speed, wind direction, turbulence intensity, gust factor, turbulence integral scale, and turbulence power spectral density were derived and analyzed before and after landing. The results show that the central wind speed time history before and after landfall exhibits significant differences, and the mean wind direction undergoes a reverse change of about 180°. The mean downwind and crosswind turbulence intensity before landing were 0.25 and 0.22, respectively, and 0.20 and 0.16 after landing. The associated mean downwind and crosswind gust factors were 1.70 and 0.61 before landing, and 1.55 and 0.46 after. These differences before and after landing are considered significant, and both turbulence intensity and gust factor showed a certain decreasing trend with the increase in wind speed. The relationship between turbulence intensity and gust factor, though somewhat scattered, was basically consistent with the commonly used Ishizaki and Choi empirical formulas. Mean streamwise and crosswind turbulence integral scales before landfall were 218 m and 100 m, respectively, and 198 m and 177 m after. They showed a weak increasing trend with increase in mean wind speed. Power spectra before and after landing were basically consistent. Comparisons with standard forms were inconclusive, though the von Karman spectrum appeared to be slightly superior to the others, particularly as the wind speed and turbulence integral scale increased. Full article

To address the scientific gap concerning optimal urban wind turbine morphology, this work presents an experimental performance comparison between two small-scale wind turbine designs: a conventional three-blade horizontal-axis wind turbine (HAWT) and a duct-equipped Ayanz-inspired screw-blade turbine. Both configurations were tested in a controlled wind tunnel under steady and transient wind conditions, including synthetic gusts designed to emulate urban wind patterns. The analysis focuses on power output, aerodynamic efficiency (via the power coefficient $C_P$), dynamic responsiveness, and integration suitability. A key novelty of this study lies in the full-scale experimental comparison between a non-conventional Ayanz screw-blade turbine and a standard three-blade turbine, since experimental data contrasting these two geometries under both steady and gusty urban wind conditions are extremely scarce in the literature. Results show that while the three-blade turbine achieves a higher $C_P$ peak and greater efficiency near its optimal operating point, the Ayanz turbine exhibits a broader performance plateau and better self-starting behavior under low and fluctuating wind conditions. The Ayanz model also demonstrated smoother power build-up and higher energy capture under specific gust scenarios, especially when wind speed offsets were low. Furthermore, a methodological contribution is made by comparing the $C_P$ vs. tip speed ratio λ curves at multiple wind speeds, providing a novel framework (plateau width analysis) for realistically assessing turbine adaptability and robustness to off-design conditions. These findings provide practical insights for selecting turbine types in variable or urban wind environments and contribute to the design of robust small wind energy systems for deployments in cities. Full article

Modern port operations face increasing challenges from rapidly changing weather and environmental conditions, requiring accurate short-term forecasting to support safe and efficient maritime activities. This study presents a sensor fusion-based machine learning framework for real-time multi-target nowcasting of wind gust speed, sustained wind speed, and wind direction using heterogeneous data collected at the Port of Livorno from February to November 2025. Using an IoT architecture compliant with the oneM2M standard and deployed at the Port of Livorno, CNIT integrated heterogeneous data from environmental sensors (meteorological stations, anemometers) and vessel-mounted LiDAR systems through feature-level fusion to enhance situational awareness, with gust speed treated as the primary safety-critical variable due to its substantial impact on berthing and crane operations. In addition, a comparative performance analysis of Random Forest, XGBoost, LSTM, Temporal Convolutional Network, Ensemble Neural Network, Transformer models, and a Kalman filter was performed. The results show that XGBoost consistently achieved the highest accuracy across all targets, with near-perfect performance in both single-split testing (R² ≈ 0.999) and five-fold cross-validation (mean R² = 0.9976). Ensemble models exhibited greater robustness than deep learning approaches. The proposed multi-target fusion framework demonstrates strong potential for real-time deployment in Maritime Autonomous Surface Ship (MASS) systems and port decision-support platforms, enabling safer manoeuvring and operational continuity under rapidly varying environmental conditions. Full article

Because wildfire spread is strongly influenced by instantaneous gusts, models that use only mean wind speed typically underestimate spread. In contrast, incorporating suppression effects often leads to overestimation. To reduce these errors, this paper newly proposes the concepts of an effective wind speed (EWS) and an EWS coefficient that jointly account for short-range forecast mean wind speed and the maximum gust from numerical weather prediction. The EWS is defined as an EWS coefficient-weighted average of the mean wind speed and maximum gust, so that the simulated perimeter matches the observed wildfire perimeter as closely as possible. Here, EWS refers exclusively to near-surface horizontal wind speed; vertical wind components are not considered. The EWS coefficient is modeled as a function of elapsed time since ignition, thereby implicitly reflecting the level of suppression resource deployment. The proposed frameworks are described in detail using time-stamped perimeters from multiple large-scale wildfires that occurred concurrently in South Korea during a specific period. On this basis, an EWS coefficient suitable for operational use in South Korea is derived. Using the derived EWS for spread prediction, the Sørensen index increased by up to 0.4 compared with predictions based on maximum gust alone. Incorporating the proposed EWS and coefficient into Korean wildfire spread simulators can improve the accuracy and robustness of predictions under extreme weather conditions, supporting safer and more efficient wildfire response. Full article

Small wind turbines operating at low heights frequently experience rapidly fluctuating and highly turbulent wind conditions that challenge conventional reactive pitch-control strategies. Under these non-stationary regimes, sudden gusts produce overspeed events that increase mechanical stress, reduce energy capture, and compromise operational safety. Addressing this limitation requires a control scheme capable of anticipating aerodynamic disturbances rather than responding after they occur. This work proposes a hybrid anticipatory pitch-control approach that integrates a conventional PI regulator with a data-driven rotor-speed prediction model. The main novelty is that short-term rotor-speed forecasting is embedded into a standard PI loop to provide anticipatory action without requiring additional sensing infrastructure or changing the baseline control structure. Using six years of real wind and turbine-operation data, an optimized Random Forest model is trained to forecast rotor speed 20 s ahead based on a 60 s historical window, achieving a prediction accuracy of RMSE = 0.34 rpm and R² = 0.73 on unseen test data. The predicted uses a sliding-window representation of recent wind–rotor dynamics to estimate the rotor speed at a fixed horizon (t + Δt), and the predicted signal is used as the feedback variable in the PI loop. The method is validated through a high-fidelity MATLAB/Simulink model of 14 kW small horizontal-axis wind turbine, evaluated under four wind scenarios, including two previously unseen conditions characterized by steep gust gradients and quasi-stationary high winds. The simulation results show a reduction in overspeed peaks by up to 35–45%, a decrease in the integral absolute error (IAE) of rotor speed by approximately 30%, and a reduction in pitch-actuator RMS activity of about 25% compared with the conventional PI controller. These findings demonstrate that short-term AI-based rotor-speed prediction can significantly enhance safety, dynamic stability, and control performance in small wind turbines exposed to highly variable atmospheric conditions. Full article

Small flexible-wing aircraft are vulnerable to gusts due to their low inertia and operating regime at low-Reynolds-number regimes, compromising flight stability and mission reliability. This paper introduces a novel active gust alleviation device (AGAD) installed at the wingtip, which works in concert with the conventional tail-plane to form a multi-surface control system. To coordinate these surfaces optimally, a quasi-static aeroelastic aircraft model is established, and a linear–quadratic regulator (LQR) controller is designed. A key innovation is the integration of an extended state observer (ESO) to estimate the unmeasurable, gust-induced angle of attack in real time, allowing the LQR to effectively counteract unsteady disturbances. Comparative simulations against a baseline (tail-plane-only control) demonstrate the superiority of the combined AGAD-tail strategy: the peak gust responses in pitch angle and normal acceleration are reduced by over 57% and 20%, respectively, while structural loads at the wing root are also significantly attenuated. Furthermore, the AGAD enhances maneuverability, reducing climb time by 20% during a specified maneuver. This study confirms that the integrated AGAD and LQR-ESO framework provides a practical and effective solution for enhancing both the stability and agility of small flexible aircraft in gusty environments, with direct benefits for applications like precision inspection and monitoring. Full article

Typhoon-induced hazards in South Korea exhibit strong spatial heterogeneity, requiring localized assessments to support impact-based early warning. This study develops a district-level typhoon hazard framework by integrating high-resolution meteorological fields with structural and hydrological vulnerability indicators. Two impact-oriented indices were formulated: the Strong Wind Risk Index (SWI), based on 3 s gust wind intensity and building-age fragility, and the Heavy Rainfall Risk Index (HRI), combining probable maximum precipitation with permeability and river-network density. Hazard levels were classified into four categories, Attention, Caution, Warning, and Danger, using district-specific percentile thresholds consistent with the THIRA methodology. Nationwide analysis across 250 districts revealed a pronounced coastal–inland gradient: mean SWI and HRI values in Busan were approximately 1.9 and 6.3 times higher than those in Seoul, respectively. Sub-district mapping further identified localized hotspots driven by topographic exposure and structural vulnerability. By establishing statistically derived, region-specific thresholds, this framework provides an operational foundation for integrating localized hazard interpretation into Korea’s Typhoon Ready System (TRS). The results strengthen the scientific basis for adaptive, evidence-based early warning and climate-resilient disaster-risk governance. Full article

With the rise of the low-altitude economy, there is growing demand for performance and safety evaluation of logistics drones and urban aircraft operating in complex turbulent environments. Conventional wind tunnels, however, face challenges in simulating the non-uniform wind fields characteristic of urban low-altitude conditions, such as building wake flows, street canyon winds, and tornadoes. To address this gap, this study proposes a novel simulation device for low-altitude complex wind fields, which utilizes multi-fan coordinated control technology integrated with jet fan arrays, pressure-stabilizing chambers, and swirl fan systems to dynamically replicate horizontal flows, vertical flows, and specialized wind patterns. Numerical simulations using Ansys Icepak validate the effectiveness of the design: the optimized horizontal flow field achieves a wind speed of 83 m/s with a turbulence intensity ranging from 5% to 20%; the gust mode attains rapid response within 3 s; and high-fidelity simulations are achieved for wind shear, tornadoes (with a maximum tangential wind speed of 50 m/s), and downbursts (with a central vertical jet velocity of 40 m/s). Furthermore, for typical urban wind environments such as alley winds and intersection flows, the study elucidates the characteristics of abrupt wind speed variations and vortex dynamics induced by building obstructions. This research provides a new perspective and a potential technical pathway for testing low-altitude aircraft, assessing urban wind environments, and supporting related studies, thereby contributing to the advancement of complex wind field simulation technologies. Full article

High-aspect-ratio wings improve aerodynamic efficiency but suffer from greater gust-induced loads, requiring innovative design methods for gust load alleviation (GLA). This study develops a reduced-order aeroelastic model to enable efficient sensitivity analysis and optimization of structural properties for passive GLA in the early design stage. A beam-based structural model was coupled with unsteady potential-flow aerodynamics in the frequency domain. The formulation, implemented in JAX, exploits automatic differentiation (AD) to compute gradients of gust responses with respect to spanwise mass and stiffness distributions. Validation was performed against MSC Nastran results. The model reproduced static and dynamic aeroelastic responses within ~10% error rate compared to MSC Nastran. Sensitivity analyses revealed that the influence of structural properties strongly depends on the chosen objective function, with mass and elastic axis location showing notable but sometimes conflicting trends. Gradient-based optimization demonstrated improved load alleviation but highlighted risks of overfitting to specific gust profiles. The proposed framework enables scalable, differentiable optimization of gust responses, bridging microstructural design and aeroelastic performance. These findings indicate that the proposed differentiable framework constitutes a valuable methodology for early-stage design, offering an efficient means to couple aeroelastic performance with structural optimization. Full article

A new power curve that is suitable for describing large wind turbines with long blades is proposed in this study. Improving the accuracy of power generation curves for large wind turbines not only involves current wind turbine development trends but also facilitates the conversion to low-carbon energy. A large wind turbine in a coastal area (with a hub height of 135 m and a long blade length of 118 m) and multidimensional wind parameters observed by lidar were integrated. Correction factors such as the turbulence intensity (TI), gust factor, and wind shear exponent (WSE) were integrated into the velocity parameter Uc to establish a multi-parameter correction prediction model suitable for describing the power generation of large wind turbines. The daily variation and distribution depending on the atmospheric stability of the correction factor were analyzed. The power generation was closer to the classical power output curve after the correction factor was applied, and the corresponding correction coefficients were proposed. The power output was enhanced with the correction factor for small winds (<4 m s⁻¹), however, the combined effects of turbulence, gust and wind shear mainly weakened the power generation for large winds of the wind turbine. Full article

This work addresses the critical need for documentation and validation of structural flight loads for Medium-Altitude Long-Endurance (MALE) Unmanned Aerial Systems (UAS). Despite the increasing prevalence of these aircraft, the industrial and research landscape still exhibits a significant data gap regarding loads under extreme operating conditions, particularly for unconventional geometric configurations. This study presents a rigorous and comprehensive load analysis for the certification of a fixed-wing MALE UAS, which is distinguished by its unique V-Tail configuration, characteristic of platforms such as the Elbit Hermes series. The entire investigation was conducted in strict adherence to the requirements of the NATO airworthiness standard STANAG 4671, aiming to precisely define the aerodynamic behavior and structural integrity of the airframe under an exhaustive set of critical flight conditions. The implemented methodology relies on the use of high-fidelity Computational Fluid Dynamics (CFD) data, derived from RANS simulations to create a complete aerodynamic database. This advanced approach is crucial for the accurate modeling of forces and moments, especially those generated by the coupled control surfaces, known as the ruddervators of the V-Tail. The results obtained include the precise derivation of the operational envelope, which defines the maximum load factors for both maneuver and atmospheric gust conditions. A detailed analysis of balancing and specific loads on the control surfaces was performed, leading to the definition of structural load distributions essential for subsequent stress analysis. Notably, the analysis identified the Unchecked Pitch-Up maneuver performed at the maximum load factor as the dimensioning design condition, particularly for the empennage structure. This work not only provides fundamental data for demonstrating compliance with applicable airworthiness criteria but also establishes a robust and repeatable methodology for the evaluation of flight loads in structurally complex UAS configurations. Full article

Rapid and precise intervention in disaster and medical-aid scenarios demands aerial platforms that can both survey and physically interact with their environment. This study presents the design, fabrication, modeling, and experimental validation of a one-piece, 3D-printed quadcopter with an integrated six-degree-of-freedom aerial manipulator robotic arm tailored for emergency response. First, we introduce an ‘X’-configured multi-rotor frame printed in PLA+ and optimized via variable infill densities and lattice cutouts to achieve a high strength-to-weight ratio and monolithic structural integrity. The robotic arm, driven by high-torque servos and controlled through an Arduino-Pixhawk interface, enables precise grasping and release of payloads up to 500 g. Next, we derive a comprehensive nonlinear dynamic model and implement an Extended Kalman Filter-based sensor-fusion scheme that merges Inertial Measurement Unit, barometer, magnetometer, and Global Positioning System data to ensure robust state estimation under real-world disturbances. Control algorithms, including PID loops for attitude control and admittance control for compliant arm interaction, were tuned through hardware-in-the-loop simulations. Finally, we conducted a battery of outdoor flight tests across spatially distributed way-points at varying altitudes and times of day, followed by a proof-of-concept medical-kit delivery. The system consistently maintained position accuracy within 0.2 m, achieved stable flight for 15 min under 5 m/s wind gusts, and executed payload pick-and-place with a 98% success rate. Our results demonstrate that integrating a lightweight, monolithic frame with advanced sensor fusion and control enables reliable, mission-capable aerial manipulation. This platform offers a scalable blueprint for next-generation emergency drones, bridging the gap between remote sensing and direct physical intervention. Full article

This paper presents a spectral method to determine the effect of thunderstorm downbursts on structures. The method integrates the dynamic response of single oscillators subject to input accelerations induced by wind, based on classical earthquake engineering theory and the proper characterisation of turbulence. The method validates previous works on synoptic wind, enabled to conduct a parametric analysis to scrutinise its dependence on outflow gust velocity, mechanical and dynamical properties of the structure, and variations in the damping ratio and terrain categories. The design spectra for thunderstorm downbursts were used to estimate the dynamic performance of a high-rise building and the results obtained showed consistency with separate numerical approaches. The proposed method offers an alternative for the rapid and effective evaluation of structural performance under thunderstorm downbursts and could expand to cover other wind environments. Full article

Dunes are key geomorphological features controlling airflow and sediment transport. While these processes are well documented under onshore conditions, this study provides the first high-resolution spatial analysis of dune-beach dynamics under offshore winds, integrating wind flow, sediment transport, and topographic data. The investigated site is a low-elevation (<1 m) dune typical of Mediterranean coasts, characterized by a mixed sand–gravel patch and a distinct beach slope break. Results show that dune height strongly controls the magnitude of airflow adjustment. Directional deflections and accelerations remain limited (<15° and <40%, respectively), and the sheltered zone extends only to the downwind dune toe. During strong wind events (gusts > 50%), sediment transport initiates immediately beyond the crest, feeding offshore-directed fluxes. Under weaker winds (gusts < 20%), enhanced surface roughness from the mixed sand–gravel patch and flow stagnation at the slope break shift the active transport zone toward the lower beach, where the most pronounced morphological changes occur. These findings demonstrate that small dunes provide limited aerodynamic shelter and fail to prevent sediment export under offshore winds. They highlight the need to incorporate additional factors (e.g., microtopography, surface properties) when assessing sediment budgets and the long-term evolution of low-relief coastal systems. Full article