High Wind Research Articles

Adaptive formation control for obstacle avoidance of USVs with asymmetric input saturation

Due to the complex maritime navigation environment, Unmanned Surface Vessels (USVs) are influenced by unknown nonlinear dynamics arising from external disturbances and internal uncertainties. Achieving effective formation control while maintaining obstacle avoidance performance presents significant challenges. This article proposes a Neural Networks (NNs) adaptive formation Artificial Potential Field (APF) obstacle avoidance control method for multiple USVs. By employing online updates of Radial Basis Function (RBF) NNs technology, the unknown nonlinear dynamics are approximated, thus addressing complex nonlinear dynamics problems. In scenarios involving multiple USVs navigating under high wind and wave conditions, collisions with obstacles frequently occur. To tackle this issue, a leader-follower control strategy is designed that effectively addresses risk assessment and obstacle avoidance under such challenging conditions. Additionally, to account for saturation constraints or potential faults in the controller inputs commonly encountered in engineering applications, it implements an asymmetric auxiliary control system. Furthermore, the Lyapunov stability theorem is utilized to ensure the stability of both the formation control and obstacle avoidance algorithms for multiple USVs. Finally, the effectiveness of the proposed algorithm is validated through simulations.

Updated method of estimating heat load for grazing dairy cattle

ABSTRACT Understanding heat stress in dairy cows is important for ensuring their welfare and productivity. While the Temperature Humidity Index is commonly used to determine heat stress conditions it does not consider outdoor factors (e.g. wind speed and solar radiation). To address this, the Grazing Heat Load Index (GHLI) which predicts respiration rate, an indicator of heat stress, was previously developed using data from the Waikato region in New Zealand. This study updated the GHLI using a weather data and animal heat stress indicators (e.g. respiration rate and drooling), collected from dairy herds in the Northland, Waikato, Canterbury, and Southland regions. A mixed-effects linear model, which included air temperature, solar radiation and wind speed as inputs was developed using data from these diverse locations. The updated model slightly outperformed the previous model on a validation dataset when predicting respiration rate. While air temperature remained the primary driver of respiration rate, solar radiation was an exacerbating factor, whereas wind exerted a mitigating effect. Challenges persist in characterising heat stress in conditions such as high wind speed. Non-linear modelling techniques could enhance the predictive capability of the GHLI model, thereby refining heat stress assessment in pasture-based dairy systems nationwide.

Chemical Activation Boosted Interface Interaction between Poly(tetrafluoroethylene-co-hexafluoropropylene) Film and Silver Coating.

To enhance the interfacial adhesion between poly(tetrafluoroethylene-co-hexafluoropropylene) (FEP) film and functional coatings, such as silver (Ag) coating, among others, the surface activation of FEP film has to be performed. Among various activation strategies, chemical activation, such as using naphthalene sodium system, is one of the most efficient methods. However, the effect of chemical activation on the interface interaction between the activated FEP and functional coating is rarely investigated. Herein, the FEP film was activated by naphthalene sodium solution under different conditions, and then the Ag layer was coated onto its surface by vacuum Ag deposition. Based on experimental results and density function theory (DFT) calculation, it is indicated that oxygen-containing functional groups (such as C=O and C-OH groups), introduced onto the surface of FEP by the chemical activation, play a key role in boosting the interface interaction, which is due to the strong interaction between the oxygen-containing functional groups and Ag atoms. In addition, the concentration of naphthalene sodium solution, activation time, and winding speed of Ag- deposition can have a significant impact on the microstructures of Ag coating and the interfacial adhesion between the activated FEP and Ag coating. Under the conditions of high concentration (0.9 M), medium activation time (15 min), and high winding speed (0.8 m min-1), there is the best interface adhesion.

Numerical investigation on behaviour of mooring line system for container ship at berth

The constant growth of the world’s maritime industry has led to the need to increase the size of ships as wellas accelerate the trend of moving ports to open sea areas and outside estuaries. Increasing the size of ships,especially container ships, has the potential to cause unsafe ship anchoring in ports. Furthermore, the mooringof ships at the harbor also lacks international guidelines on the layout of the mooring system. Meanwhile, relocating seaports outside estuaries and open seas can create conditions for high winds, high tidal fluctuationsand strong currents to penetrate the port basin. This paper presents a study using the MIKE 21 MA numericalmodel to determine the most optimal mooring layout for a container ship as well as clarify the influence offactors (wind, current, water level and ship’s draft) on the tension force of the mooring lines. The most optimal mooring layout in the study scenarios was uncovered from the simulation results. In addition, wind wasidentified as the factor with the greatest influence on the tension force of the mooring system.

Spatiotemporal Climatology of Georgia Tropical Cyclones and Associated Rainfall

Tropical cyclones (TCs), often characterized by high wind speeds and heavy rainfall, cause widespread devastation, affecting millions of people and leading to economic losses worldwide. TC-specific research in Georgia is scarce, likely due to the minimal geographical extent of its coast and the infrequency of direct landfalls. Research on Georgia TCs does not account for storms that make landfall in other southeastern states (e.g., Florida) and continue north, northeast, or northwest into Georgia. This study used the North Atlantic Basin hurricane database (HURDAT2) to quantify the spatiotemporal patterns of direct and indirect landfalling of Georgia tropical cyclones (>16 ms−1) from 1851 to 2021. TC-induced rainfall was also quantified using rainfall data (nClimGrid-Daily and nClimGrid) from 1951 to 2021 to estimate the proportion of Georgia’s total annual and monthly rainfall attributed to TCs. A multi-methodological approach, incorporating statistics and mapping, is employed to assess the trends of Georgia’s tropical cyclones and the associated rainfall. The study analyzed 113 TCs and found that, on average, less than one TC annually (x¯ = 0.66) traverses the state. September averaged the highest percentage (25%) of TC-induced rainfall, followed by October (14%), and August (13%). This pattern aligns with the TC season, with the highest frequency of TCs occurring in September (n = 35), followed by August (n = 25), and October (n = 18). We found that 10% of tropical storms make landfall on the coastline, while the remaining 91% enter Georgia by making landfall in Florida (92%), Louisiana (7%), or South Carolina (1%) first. A threat of TCs during the peak of the season emphasizes the importance of heightened awareness, increased planning practices, and resource allocation during these periods to protect Georgia’s history and natural beauty, and its residents.

Enhancing pitch angle control in variable speed doubly fed induction generator based wind energy conversion system using advanced adaptive neuro-fuzzy approach with particle swarm optimization

Pitch angle control is a common method used to smooth out output power fluctuations in the wind turbines. This paper focuses on Particle Swarm Optimization (PSO) based Adaptive Neuro-Fuzzy Inference System (ANFIS) pitch angle control scheme for a variable speed Doubly Fed Induction Generator (DFIG) based wind energy conversion system designed for operation in high wind speed regions. The proposed enhanced adaptive controller comprises both Sugeno type fuzzy inference system (FIS) and neural network architecture. In the Sugeno type FIS, the membership functions are optimized using a revisited PSO method. The primary objective is to control the pitch angle to ensure that generator power and speed operate within desired references, reducing fluctuations and minimizing mechanical blade stress. A MATLAB/SIMULINK model of wind energy conversion system setup is prepared and simulations are conducted using different control methods. The effectiveness of the proposed approach is confirmed based on the simulation results.

Robust fractional-order load frequency control for hybrid power system concerning high wind penetration

Hybrid power systems concerning wind farms have witnessed significant dynamic characteristic changes due to unpredicted generation output and integration mode conversion between frequency-sensitive wind plants and non-scheduled ones. This work presents a robust fractional-order load frequency control (LFC) method for a multi-area hybrid power system in the presence of wind penetration uncertainties. To characterize the injection effect of wind farms, the power system is described by a model with an uncertain wind penetration factor in a pre-estimated range. Then, an enhancement of Levy’s identification method is developed to convert this model into a fractional-order reduced structure to design the load frequency controller, which is in a form of fractional-order PID with a filter for ease of engineering implementation. The closed-loop stability is analyzed by the stability boundary locus (SBL) method under different wind penetration levels. It is shown that superior frequency response performance and system robustness can be obtained if the controller is designed in terms of the model with the worse-case wind penetration. Illustrative examples including a three-area hybrid power system under a variety of wind penetration variations are given to show the effectiveness of the proposed method.

Detection and characterization of aeolian sand strips on the beach using permanent laser scanning

Aeolian sand strips are bedforms that often form on the beach during high wind events. The sand strips can move across the beach resulting in sediment transport, but these sediment fluxes have not yet been quantified. Permanent laser scanning (PLS) provides an opportunity to gather long-term and detailed information about sand strips. Here, we present a method that detects sand strips in PLS reflectance images and extracts their wavelength, orientation, and height. The detection method is used on a month-long hourly dataset of Noordwijk beach, the Netherlands. The average sand strip wavelength (13 m), height (3 cm), and orientation (onshore-oblique) found in this dataset are consistent with previous research. Migration rates are obtained by examining successive images of sand strip patterns. Using the concurrent sand strip height, the sediment transport rate associated with sand strips is estimated. During a single 8-hour event, a total sediment flux of 0.16 m3/m is observed of which 0.07 m3/m in onshore direction. Furthermore, the detection method is shown to be applicable to other beaches by calibrating its thresholds. This opens a new possibility for future research to use PLS to investigate the behavior and sediment transport rates of aeolian sand strips.

Rapid cycling and emission of volatile sulfur compounds in the eastern Indian Ocean: Impact of runoff inputs and implications for balancing atmospheric carbonyl sulfide budget

Volatile sulfur compounds, such as dimethyl sulfide (DMS), carbonyl sulfide (OCS), and carbon disulfide (CS2), significantly influence atmospheric chemistry and climate change. Despite the oceans being an important source of these sulfides, the limited understanding of their biogeochemical cycles in seawater introduces considerable uncertainties in quantifying their oceanic emissions and assessing atmospheric OCS budgets. To address this issue, we conducted a comprehensive field survey in the tropical eastern Indian Ocean (EIO) to examine the spatial distributions, source-sink dynamics, and sea-air exchange fluxes of marine DMS, OCS, and CS2. Our study indicates that nutrients, organic matter, and freshwater input from terrestrial runoff significantly affect most of the source-sink processes of these sulfides in the Bay of Bengal and even the tropical EIO. The resulting sulfide accumulation in seawater combined with high wind speeds establishes the tropical EIO as a considerable direct and indirect atmospheric OCS source. These insights underscore the potentially critical role of marine environments influenced by runoff in contributing to the atmospheric OCS budget. However, by integrating these results with previous field surveys, we believe that actual OCS emissions from tropical oceans exceed some bottom-up box-model simulations, yet fall significantly below those predicted by top-down models, still insufficient to bridge the atmospheric OCS source gap. Our detailed examination of source-sink dynamics offers deeper insights into the marine sulfur cycle and has potential implications for refining future box-models, thus mitigating uncertainties in estimating marine sulfur emissions.

Numerical investigation of the effect of winglet configurations with multiple cant angles on the aerodynamic performance of wind turbine blade

ABSTRACT A numerical investigation of the effects of winglets with multiple cant angles on the power output of the blade of a horizontal axis wind turbine (HAWT) is conducted. Several winglet configurations with single and multiple cant angles are designed and their performance is evaluated. Numerical solutions obtained by RANS equations and moving reference frame method were compared with the experiments and demonstrated that they concur well with the experimental data. In the torque and thrust comparison, the ones with multiple cant angles present better power output enhancement than those with a single cant angle at a relatively high wind speed. The configurations of multiple cant angles are effective in reducing the influence of wing tip vortices, resulting in a higher torque while maintaining the same winglet length and height.

Energy harvesting using rooftops in urban areas: Estimating the electricity generation potential of PV and wind turbines considering the surrounding environment

Building rooftops, rich in sunlight and with high wind speeds, are among the most ideal locations for installing renewable energy systems (RES) in urban areas. However, not all rooftops are suitable for RES installation. Therefore, this study aimed to maximize energy harvesting using limited rooftop space. To this end, four scenarios were established based on a district in Seoul, South Korea, and the annual electricity generation of the RES was then estimated. This process was refined further into seven scenarios to assess economic feasibility. The principal findings of this research are as follows. First, depending on the type of RES installed on rooftops, it is possible to generate between 755,124 kWh and 3,236,918.3 kWh of electricity annually. Second, in terms of economic feasibility, scenarios predominantly featuring photovoltaic (PV) installations proved economically viable, whereas those mainly involving vertical axis wind turbines (VAWTs) did not guarantee economic feasibility. Third, for VAWTs scenarios with lower economic viability, adjusting the Renewable Energy Certificate weight and providing government subsidies up to USD1,131/kW could improve the profitability. These results provide a foundation for RES operators to design appropriate projects based on economic evaluations, and for policymakers to formulate effective policies to better promote the diffusion of RES.

Magnetosonic waves in the Martian ionosphere driven by upstream proton cyclotron waves: Two-point observations by MAVEN and Mars Express

Recent observations from the Mars Atmosphere and Volatile EvolutioN (MAVEN) and Mars Express (MEX) spacecraft have suggested that pressure pulses originating from upstream proton cyclotron waves (PCWs) can “ring” the Martian magnetopause at the same frequency and drive magnetosonic waves in the upper ionosphere of Mars, thereby transporting energy from the solar wind into the ionosphere. However, the limitation of single-spacecraft measurements prevents simultaneous observations of the driver and response of this “ringing” process of the Martian magnetosphere. Here we utilize two-point measurements from MAVEN and MEX to characterize the ringing probability at which upstream PCWs drive compressional fluctuations in the ionospheric magnetic field. We develop an algorithm to identify PCW-driven magnetosonic waves in the upper ionosphere of Mars from the two-point magnetic field data. The derived ringing probability is higher on the dayside, outside strong crustal magnetic fields, and under high solar wind density conditions. We also show that the median power of dayside ionospheric magnetic field fluctuations is enhanced by a factor of ∼2 at corresponding frequencies in the presence of upstream PCWs compared to the median power in the absence of upstream PCWs. These results demonstrate the prevalence of energy deposits into the dayside Martian ionosphere from the solar wind mediated by the PCW-driven ringing of the magnetosphere. Future studies, possibly with new multi-point observations, should address the detailed processes of wave propagation and energy transport through the system and the long-term impact of this chain of processes on the planetary ion heating in the ionosphere and atmospheric loss from Mars.

Long-term observations of the turbid outflow plume from the Russian River, California

Understanding the mechanisms that spread freshwater away from small river systems and form turbid, low-salinity coastal plumes is crucial for assessing water quality in coastal waters. We present an analysis of 15 years (January 2004 to December 2018) of daily MODIS Aqua satellite data and in situ instrument data on the turbid freshwater plume that forms off the Russian River (California, USA), a prototypical Mediterranean-climate, small mountainous river system (SMRS). We present per-pixel statistical metrics and regression analyses to identify and quantify the controls on the extent and configuration of the plume exerted by river discharge, waves, winds, and tides. While freshwater outflow exhibits a persistent signal in nearshore waters, a large-scale plume only extends offshore into coastal waters during high river flow, when plume turbidity can be detected more than 10 km offshore from the river mouth. Our results show times when wave radiation stress exceeds outflow inertia, confining the plume within the surf zone and leading to an absence of detectable plume turbidity in coastal waters. Although tidal currents significantly influence the plume near the inlet, wind forcing is the primary control on plume shape and extent in coastal waters, deflecting the turbid outflow more than 30 km upcoast or downcoast of the river mouth with respective wind directions. Coriolis forcing is also significant and observed most clearly during periods of high river discharge and low wind forcing. In addition to introducing novel remote sensing methodology for SMRS plume analyses, these findings highlight the complex interplay of forcing related to tides, river discharge, winds, and waves in shaping the behavior of SMRS plumes. New insights include the impact of tides on larger discharges, the role of Coriolis forcing in SMRS plumes, and the effect of cross-shore winds on plume compression. Further, by considering the Russian River as a model for SMRS, this study can be used to ground-truth existing numerical models of small river plumes and to contribute to understanding critical for managing coastal water quality and nearshore ecosystems.

Optimization of Wind Turbine Efficiency during Severe Weather

Due to the importance of energy in society as well as the negative environmental impact of many commonly used energy sources, namely fossil fuels, it is essential to develop and improve sources of renewable energy. Wind energy is a prominent, widely accessible, and environmentally friendly form of renewable energy created when wind turbines convert the kinetic energy of wind to electricity. Severe weather is one area of concern for wind turbines. This article primarily examines the effects of high wind speeds and lightning on wind turbines. To aid in improving and fostering renewable energy, this article aims to study the effects of lightning and high wind speeds on wind turbines, evaluate current solutions, and suggest improvements where possible. After examining several sources, the advantages and disadvantages of current methods were discussed along with proposed improvements. Due to the restrictions of our research being purely virtual, lacking resources, and time constraints, we are unable to conduct tests and physical research of wind turbines and these meteorological events for more thorough first-hand exploration. Following our research, the next step would be to utilize the evaluations and proposed improvements to current wind turbine designs and analyze the effects.

Analysis of rain effects on China-France oceanography satellite scatterometer backscatter measurements

ABSTRACT The rotating fan beam scanning observation mechanism of China-France oceanography satellite (CFOSAT) scatterometer provides more comprehensive ocean measurements. However, its data quality is often impacted by rain contamination. In this study, we analysed the effect of rain on CFOSAT SCATterometer (CSCAT) backscatter measurements by collocating CSCAT data, the Integrated Multi-satellitE Retrievals (IMERG) rain data, and the wind reanalysis from European Centre for Medium-Range Weather Forecasts (ECMWF). The research findings indicate that, rain exhibits an intensification effect on backscatter at low wind speeds, but this effect gradually diminishes with increasing wind speeds, eventually transitioning to an attenuation effect at a wind speed between 10–20 m·s−1. At extremely high wind speeds above 20 m·s−1, the rain initially increases and then decreases CSCAT normalized radar cross section (σ 0) as the rain rate increases. The sensitivity of CSCAT σ 0 to rain rate decreases as the incidence angle increases. Its sensitivity to wind speed decreases as the rain rate increases. The azimuthal modulation becomes more pronounced with higher wind speeds and smaller incidence angles. However, rain weakens the asymmetry and anisotropy. Furthermore, the HH polarization exhibits a more pronounced susceptibility to rain compared to the VV polarization.

Optimization Study of a Tuned Mass Damper for a Large Monopile Wind Turbine

Passively tuned mass dampers (TMDs) are known to effectively mitigate the vibration of wind turbines. However, existing literature predominantly examines their application in damping vibrations of the tower or platform, overlooking the potential benefits of installing TMDs on the turbine blades themselves. This study investigates the impact of wind and wave loads on TMD damping effectiveness and proposes a comprehensive damping strategy involving TMDs installed in both the nacelle and the blades. The design optimized the mass and stiffness of these TMDs to enhance their performance. Results indicate that, as wind speeds increased from 12 m/s to 24 m/s, the power spectral density at the tower’s natural frequency (0.22 Hz) more than doubled. Notably, TMDs exhibited robust vibration damping capabilities under high wind speeds. Specifically, at wind speeds of 24 m/s, TMDs reduced anterior–posterior and lateral displacement at the tower top by 61.2% and 166.8%, respectively, when two TMDs were combined. Conversely, the study found that TMDs did not significantly improve vibration damping at lower to moderate wind speeds. This research underscores the importance of optimizing TMDs for high wind conditions to ensure wind turbine stability and mitigate potential vibration-related risks effectively under varying environmental loads, including wind and waves. It offers valuable insights for the refined design and deployment of TMDs in wind energy applications.

A Physical‐Informed Neural Network for Improving Air‐Sea Turbulent Heat Flux Parameterization

AbstractThe parameterizations of air‐sea turbulent heat flux are one of the major bottlenecks in atmosphere‐ocean coupled model development, which play a crucial role in sea surface temperature (SST) prediction. Recently, neural networks start to be applied for the development of parameterizations of interface turbulent heat flux. However, these new parameterizations are primairily developed for specific regions and have not been tested in real atmosphere‐ocean coupled models. In this study, we propose a new air‐sea heat flux parameterization using a physical‐informed neural network (PINN) based on multiple observational data sets worldwide. Evaluated with an independent observation data set, it is shown that the PINN can significantly reduce the RMSE of latent heat flux by at least about 48.6% compared to three traditional bulk formulas. Moreover, the PINN can be flexibly updated with new observational data by transfer learning. To test the performance of the new parameterization in realistic application, we implement the PINN into a global ocean‐atmosphere coupled model and make seasonal forecasts for the first time. The PINN markedly reduce the errors of equatorial SST forecast, indicating a good performance of the PINN‐based air‐sea turbulent heat flux scheme. Noticeably, due to limited observational data, the NN‐based parameterizations tend to underestimate heat flux at high wind speeds compared with bulk formula‐based parameterizations. With more data available at extreme conditions, the PINN can be improved via transfer learning and need to be futher evaluated. This study suggests that PINN‐based air‐sea heat flux parameterization is promising to improve SST simulation.

PMSM Design for Elevators: Determination of the Basic Topology Affecting Performance

In recent years, with the increase in high-rise building construction, there has been a rise in demand for elevators. This demand has spurred mutual growth between the vertical transportation sector and high-rise building construction. Both sectors are improving technology, security, and comfort standards. Traditional elevator traction machines typically employ asynchronous motors coupled with geared reducers, despite their low energy efficiency and requirement for large machine rooms. However, with the proliferation of rare-earth magnet materials and advancements in driver technologies, the use of Permanent Magnet Synchronous Motors (PMSMs) in elevator traction machines has increased. PMSMs operate with direct drive, eliminating the need for reducers. High efficiency and passenger comfort are crucial parameters for elevator traction machines. This study focuses on identifying the fundamental topology that could influence the performance of PMSMs for gearless elevator machines. Factors such as stator materials, rotor structures, permanent magnets, winding configurations, slot/pole combinations, cogging torque and torque ripple have been examined to select suitable design topologies for elevator motors. Important topics such as the magnetic properties of grain-oriented silicon steel sheets used in stator construction, B-H curves, lamination forming and stacking factors have been addressed. Two different rotor topologies and magnet arrangements, namely internal and external, have been investigated in PMSM designs. Additionally, the use of four different magnet materials, namely AlNiCo, Ferrite, NdFeB, and SmCo have been compared for PMSM traction motors in elevators. Single-layer and double-layer winding configurations, distributed and concentrated winding configurations have been compared. Fractional slot/pole combinations, which directly affect the performance and comfort of PMSMs, have also been examined based on information obtained from the literature. Particularly, structures with high winding factors, such as 12/10, 12/14, 18/16, 18/20, 24/22, and 24/26 have been identified. Finally, studies on skewing to reduce cogging torque and torque ripple have been addressed.

Case studies of the winds in the urban area of Hong Kong – Microclimate station observations and high resolution numerical simulations

Hong Kong, renowned for its densely packed urban areas, poses unique challenges for understanding the effects of buildings on local meteorological conditions. To address this, the Hong Kong Observatory has started building a network of urban meteorological monitoring stations since 2017 for monitoring, analysing and studying urban microclimate. This paper presents an observational and numerical study focusing on wind measurements obtained from wind sensors installed on two smart lampposts in Tsim Sha Tsui, a major urban area in Hong Kong. Two representative high wind conditions in Hong Kong, Super Typhoon Saola in 2023 and a strong monsoon case characterized by prevailing easterly winds, are considered. With the use of high resolution computational fluid dynamic simulations, major features of actual observations can be reproduced. This suggests that district scale or even street scale weather services could be possible in the future with sufficient computational power.

Murmansk Marine Biological Institute of Kola Scientific Center of the Russian Academy of Sciences

The authors assess the wind potential indicators and the scale of its use for power supply of hard-to-reach off-grid settlements in the eastern Russian Arctic. The primary challenge facing autonomous power plants is fuel delivery due to long distances and underdeveloped transport infrastructure. The use of wind power plants will reduce fuel consumption and cut the cost of energy production. The researchers use ground-based measurement data and the characteristics of existing autonomous power plants as initial data when assessing the rational capacity of wind power plants. They employ authoring research methods. Via Wind-MCA program they estimate wind potential indicators: average wind speed, capacity factor, and coefficient of wind speed variation. The research results are presented in cartographic form. The rational capacities of wind power plants as part of hybrid energy systems are determined using the generalized dependencies method based on the maximum load of a populated area and calculated wind potential indicators, taking into account the characteristic intra-annual distribution of wind speeds. The best conditions for the development of wind energy are observed on the coast of the Arctic seas in the Krasnoyarsk Territory and the Chukot Autonomous Area. The rational capacity of wind power plants in zones of high wind potential in hard-to-reach areas of eastern Russian Arctic is estimated at 12,5 MW.