Fast Wind Speed Research Articles

Biomechanics of human locomotion in the wind.

In laboratory settings, human locomotion encounters minimal opposition from air resistance. However, moving in nature often requires overcoming airflow. Here, the drag force exerted on the body by different headwind or tailwind speeds (between 0 and 15 m·s-1) was measured during walking at 1.5 m·s-1 and running at 4 m·s-1. To our knowledge, the biomechanical effect of drag in human locomotion has only been evaluated by simulations. Data were collected on eight male subjects using an instrumented treadmill placed in a wind tunnel. From the ground reaction forces, the drag and external work done to overcome wind resistance and to sustain the motion of the center of mass of the body were measured. Drag increased with wind speed: a 15 m·s-1 headwind exerted a drag of ∼60 N in walking and ∼50 N in running. The same tailwind exerted -55 N of drag in both gaits. At this wind speed, the work done to overcome the airflow represented ∼80% of the external work in walking and ∼50% in running. Furthermore, in the presence of fast wind speeds, subjects altered their drag area (CdA) by adapting their posture to limit the increase in air friction. Moving in the wind modified the ratio between positive and negative external work performed. The modifications observed when moving with a head- or tailwind have been compared with moving uphill or downhill. The present findings may have implications for optimizing aerodynamic performance in competitive running, whether in sprints or marathons.NEW & NOTEWORTHY This is the first study to assess the biomechanical adaptations to a wide range of wind speeds inside a wind tunnel. Humans increase their mechanical work and alter their drag area (CdA) by adapting their posture when walking and running against increasing head and tailwinds. The observed drag force applied to the subject is different between walking and running at similar headwind speeds.

Assessing the abundance, sources, and potential ecological risk assessment of microplastics using their particle and mass units in Uiam Lake, South Korea

Microplastics (MPs) enter lakes through various pathways, including effluents from wastewater treatment plants (WWTPs), surface runoff, and improperly disposed of plastic waste. In this study, the extent of MPs pollution in Uiam Lake in fall of 2022 and spring of 2023 was assessed by determining both the number (n/m3) and mass concentrations (μg/m3) of MPs. Moreover, the correlation between water quality parameters and MP properties was analyzed, and an ecological risk assessment was conducted. MPs abundance was higher in spring than in fall, probably due to the lifting of coronavirus disease-19 restrictions, melting of ice, higher rainfall, and faster wind speed. Fragment was the dominant shape of the MPs collected, while polyvinyl chloride (PVC) and polyester/polyethylene terephthalate were the frequently detected polymer types of MPs in fall and spring, respectively. There was a moderate positive correlation between the number concentration of MPs and the total nitrogen, total phosphorus (T-P), and total organic carbon levels; in contrast, there was no significant relationship between the mass concentration of MPs and all water quality parameters. However, the abundance (μg/m3) of PVC and polymethyl methacrylate MPs were positively correlated with T-P and electrical conductivity. The pollution load index, polymer hazard index, and potential ecological risk index (PERI) were generally higher when the mass unit of MPs was used due to the presence of large-sized MPs composed of highly hazardous polymers (e.g., polyurethane, PVC, and alkyd). For instance, the PERI value of the WWTP effluent was at the very high level (>1200) in both seasons, regardless of the abundance unit of MPs. Therefore, WWTP effluents may have increased the ecological toxicity of MPs pollution in Uiam Lake.

Comparison of horizontal wind speed and direction measurements from dual-Doppler radar and profiling lidars

Dual-Doppler radar is a relatively new technology in the wind energy community and thus not yet studied vastly. This paper aims to compare horizontal wind speed and direction data retrieved from dual-Doppler radar and profiling lidars within the American WAKE experimeNt (AWAKEN) to investigate the influence of measurement height, wind direction and speed on the comparison. The 10-min averaged data show a better agreement of the measurements for higher altitudes, especially at faster wind speeds. For the wind direction, two sectors of larger differences in the measurements were detected: around 270° transient winds occur with a higher frequency than in other sectors. To explain the different measurement values in the wind direction sector around 90°, further studies, e.g. on the influence of atmospheric stability, are necessary.

Rancang Bangun Prototipe Alat Ukur Kecepatan dan Arah Angin Berbasis Arduino Pro Mini Studi Kasus Penerapan pada Olahraga Paralayang di Parangtritis

Wind is a phenomenon observable a mass movement of air the effect and experienced in everyday life due to differences in the air pressure in two separate places so there the airflow from a having the air pressure is higher to a lower have pressure air. Fast slowness wind speed depends on how big a pressure difference of the two it. Essentially any need sports facilities must meet the standard sports itself. Sports paralayang, on the need facilities able to meet a need the related sports development. This study aims to to build a helmet safety to users paralayang on sports paralayang in parangritis. A helmet these were designed based microcontroller to help users paralayang, so users of paralayang would quickly get information that can be used as an effort to safety. The helmet worn by paralayang, which in upon the helmet these there were instrument that serves to measuring wind speed. When the wind is fast , this instrument will sound and paralayang must be down. So risk can minimize accident. The result of this study graphic display the output of a system for conducting the process of wind measurements is expected to measuring changes wind is more precision by means of sensors optocoupler which are cheap and have good qualities.

A comprehensive wind speed prediction system based on intelligent optimized deep neural network and error analysis

At present, wind power is one of the most promising clean energy sources. Due to its high variability, accurate wind speed forecasting is an essential part of the wind power industry. This paper proposes a comprehensive forecasting system consisting of three parts: Firstly, the novel SC-EWT wind speed signal reconstruction system proposed in this article can effectively extract information from wind speed signals. Secondly, the QBGA-GRU model is used for signal reconstruction prediction, where QBGA is an improved genetic algorithm proposed in this article that can improve prediction accuracy. Finally, the IPSO-BLS algorithm is used to quickly analyze and predict prediction errors and further correct the predicted results. The system can provide users with adaptive signal decomposition, high-precision deep learning prediction and error analysis functions to achieve efficient and fast short-term wind speed forecasting, which can be used in the fields of wind power integration deployment and wind turbine early warning. The experiments show that the proposed prediction strategy has good predictive ability for wind speed samples in two regions, and its error is smaller than that of commonly used intelligent algorithms. Compared with other models, the proposed comprehensive prediction strategy has better predictive performance and smaller prediction errors than other combination models.

The electric fields and “lightning jets” of the Sun and solar wind

A model of electric energization of the solar wind and corona is developed, including electro-magnetic particle effects precluded by traditional magneto-hydro (MHD) assumptions. Using standard 1D radial solar models for particle density and temperature, the core gravito-electric field is calculated; and the range of possible photospheric photo-electric fields is estimated. The extant DC field apparently arises from about 460 C of charge displacement, mainly caused by the immense solar energy flux pushing electrons outward. Energetically, this electric field can accelerate surface protons out of the 2 keV gravity well and up to the 4 keV energies observed in the fast solar wind. The electrical energy is released in pervasive, persistent “proton lightning jets,” which are proton beams, charge-neutralized by co-propagating electrons. The jets are formed by pinched “avalanche breakdown” of the weakly ionized photosphere, probably initiated on the down-welling edges of solar surface granulations. These energetic jets will glow as discrete filamentary surface spicules and will be observed in reflected solar light as the diffuse K-corona. Significantly, the total charge displacement and observed fast wind speed are quantitatively predicted by a novel “virial limit”: the (positive) electrical potential energy at r = 0 is limited in magnitude to the 10 keV gravitational well at r = 0.

NIRwave: A wave-turbulence-driven solar wind model constrained by PSP observations

Aims. We generate a model description of the solar wind based on an explicit wave-turbulence-driven heating mechanism, and constrain our model with observational data. Methods. We included an explicit coronal heating source term in the general 3D magnetohydrodynamic code NIRVANA to simulate the properties of the solar wind. The adapted heating mechanism is based on the interaction and subsequent dissipation of counter-propagating Alfvén waves in the solar corona, accounting for a turbulent heating rate Qp. The solar magnetic field is assumed to be an axisymmetric dipole with a field strength of 1 G. Our model results are validated against observational data taken by the Parker Solar Probe (PSP). Results. Our NIRwave solar wind model reconstructs the bimodal structure of the solar wind with slow and fast wind speeds of 410 km s−1 and 650 km s−1 respectively. The global mass-loss rate of our solar wind model is 2.6 × 10−14 M⊙ yr−1. Despite implementing simplified conditions to represent the solar magnetic field, the solar wind parameters characterising our steady-state solution are in reasonable agreement with previously established results and empirical constraints. The number density from our wind solution is in good agreement with the derived empirical constraints, with larger deviations for the radial velocity and temperature. In a comparison to a polytropic wind model generated with NIRVANA, we find that our NIRwave model is in better agreement with the observational constraints that we derive.

Optimal Controller Design for Wind Turbine using Sliding Sector and Genetic Algorithms

This present work presents a major contribution to the field of wind turbine control which is the more challenging context that this paper is focused. This manuscript gives a novel design of a high-performance controller using the sliding sector law optimized by genetic algorithms. This developed design gives an improvement in the robustness of wind energy systems compared to the traditional law known as sliding mode control (SMC). The proposed design is based on the idea of extending the SMC by transforming the sliding surface into a sliding sector. Genetic algorithms are used to optimize the switching gain in its control structure in real-time. The benefits of this design under fast and random wind speed variations are utility for non-linear systems, achieving maximum power tracking, ensuring robust stability, eliminating the chattering problem, and faster response time. The strengths of this design are proved by simulation results of the main parameters of the two-mass model of wind turbines using Matlab software.

AIRFLOW EVALUATION IN CLASSROOM DURING COVID-19 PANDEMIC

The COVID-19 pandemic that hit Indonesia caused transition of the education process to online in 2020. The government seeks to improve the quality of student education in this pandemic era by preparing limited face-to-face learning. It is crucial to conduct a study on air because it is one of the mediums used to transfer viruses. This research took one sample of a classroom at SDN 27 North Pontianak. This research uses a Computational Fluid Dynamics simulation to display the air flow conditions of a room. The results showed that the fastest wind speed in the class ranged from 0.12 m/s to 0.44 m/s with green, yellow and red parameter color. The slowest wind speed was 0.01 m/s to 0.12 m/s with blue and green parameter color. The parameter shows levels are within limits suggested by ASHRAE and the effect of the availability of smooth air circulation for the classroom and stable air change. They were limiting the virus ability to spread by improving airflow. Rapid air exchange in the classroom lowers the risk of infection for students and teaching staff.

Understanding subjective and situational factors of wind turbine noise annoyance

One of the most relevant acceptance factors of local wind turbines (WTs) are noise emissions. To better understand why some residents experience stress effects from wind turbines a field study with strongly annoyed residents (SAR) was conducted. A convenience sample of residents (N = 148) in the proximity of a wind farm in Germany were interviewed using a standardised questionnaire. Objective features, such as number of visible WTs and distance to the nearest WT, could not explain the experienced noise annoyance substantially. Instead, SAR were characterised by a negative perception of both procedural as well as distributive fairness, the assumed decrease of property value due to the WTs, a negative attitude towards the local wind farm (but not to WTs in general), and higher noise sensitivity. Additionally, SAR reported to be affected daily during the night in their bedrooms, while other residents experience annoying situations more likely when they are directly exposed to WTs. Fast wind speeds, wet weather and, occasionally, frost or fog were associated with annoying situations. In accord with recent research, we recommend to increase consideration of participation and fairness in the initial planning of a wind farm to increase acceptance and reduce annoyance. Additionally, to reduce the fear of negative health impacts and to increase acceptance, mitigation measures depending on specific weather conditions seem to be promising.

A Wind-Tunnel Assessment of Parameters That May Impact Spray Drift during UAV Pesticide Application

The objective of this study was to investigate the impact of varying wind speeds (1.5, 3.0, and 4.5 m/s), initial payload volumes (2 and 10 L), and nozzle droplet size characteristics (fine, medium, coarse) on drift during spray applications from an unmanned aerial vehicle (UAV) hovering freely in a wind tunnel. Along the length of the wind tunnel, glass slides were used to collect spray droplets at 14 points distributed in upwind, in-swath, and downwind distances. Analysis of the results showed that there are distinguishable shifts of up to 2 m in-swath as wind speed increases. Downwind of the UAV, a regression of the combined variables indicated that tunnel wind speed changed deposition the most overall, followed by nozzle/droplet size. Initial payload volume was less impactful. Overall, faster wind speeds, finer droplet sizes, and a heavier initial payload were associated with more drift on average. Wind directions and speeds were also measured on a finer scale of tunnel locations to record airflow pattern variability especially closer to the UAV. These findings may provide guidance to regulators and applicators to identify operating conditions for UAVs that limit off-target movement during applications.

Energy management of renewable energy sources incorporating with energy storage device

The best solution to exploit renewable energy sources (RES) together is by using the application of microgrid (MG). This indeterminate of resources such as solar panels, wind farm, diesel generator, and battery storage system paired with load profile result in random changes within the generation and the load phases, which create it is challenging to properly manage an MG. Due to this problem energy management technique for real-time scheduling of an MG takes into consideration the uncertainty of load demand, renewable energy, and electricity price are proposed. In this paper, linear programming with two methods (optimized problem and solver based) of dual-simplex are suggested to tackle the energy management issue of the renewable microgrid. The simulation is done in each method using four cases fast wind speed with clear solar irradiance, fast wind speed with cloudy solar irradiance, slow wind speed with clear solar radiation, and slow wind speed with clear solar irradiance. The result showed that the first and second cases in the first method are higher cost than the two corresponding cases in the second method. In addition, the third and fourth cases in the first method are lower cost than the two corresponding cases in the second method.

Offshore wind speed short-term forecasting based on a hybrid method: Swarm decomposition and meta-extreme learning machine

As the share of global offshore wind energy in the electricity generation portfolio is rapidly increasing, the grid integration of large-scale offshore wind farms is becoming of interest. Due to the intermittency of wind, the stability of power systems is challenging. Therefore, accurate and fast offshore short-term wind speed forecasting tools play important role in maintaining reliability and safe operation of the power system. This paper proposes a novel hybrid offshore wind forecasting model based on swarm decomposition (SWD) and meta-extreme learning machine (Meta-ELM). This approach combines the advantages of SWD which has proven efficiency for non-stationary signals, with Meta-ELM which provides faster calculation with a lower computational burden. In order to enhance accuracy and stability, the signal is decomposed by implementing a swarm-prey hunting algorithm in SWD. To validate the model, a comparison against four conventional and state-of-the-art hybrid models is performed. The implemented models are tested on two real wind datasets. The results demonstrate that the proposed model outperforms the counterparts for all performance metrics considered. The proposed hybrid approach can also improve the performance of the Meta-ELM model as a well-known and robust method.

Variations in outdoor thermal comfort in an urban park in the hot-summer and cold-winter region of China

• Outdoor thermal comfort is evaluated in an urban park in a hot-summer and cold-winter region of China (Chengdu). • Machine learning techniques are applied to determine the (nonlinear) relationship between thermal sensation vote and meteorological factors. • The effect of landscape spaces on human thermal comfort varies across the season. • NTR of PET is 6.79 °C to 19.90 °C, and NTR of UTCI is 13.27 °C to 27.25 °C. TAR of PET is 2.8 °C to 21.9 °C, and TAR of UTCI is 8.1 °C to 28.3 °C. Global warming and rapid urbanization have exacerbated the urban heat island effect. Urban parks contribute to alleviating such an effect and achieving the “carbon emission peak before 2030” and “carbon neutrality before 2060” goals of China. Their popularity is considerably influenced by human thermal comfort. However, limited thermal comfort studies have been conducted in the hot-summer and cold-winter region of China. This study examines human thermal comfort in different landscapes of an urban park in Chengdu and determines the thermal benchmarks. A machine learning (random forest) analysis shows that human thermal sensation is affected by different meteorological factors in different seasons. In addition, the influences of landscape space on human thermal comfort have considerable differences in different seasons. Residents prefer strong solar radiation in winter but fast wind speed in summer. UTCI (universal thermal climate index) is better than PET (physiological equivalent temperature) for outdoor thermal comfort assessment in the study area. This study serves as a valuable baseline and technical reference, contributing to sustainable urban park design.

A Fast and Accurate Wind Speed and Direction Nowcasting Model for Renewable Energy Management Systems

To plan operations and avoid any grid disturbances, power utilities require accurate power generation estimates for renewable generation. The generation estimates for wind power stations require an accurate prediction of wind speed and direction. This paper proposes a new prediction model for nowcasting the wind speed and direction, which can be used to predict the output of a wind power plant. The proposed model uses perturbed observations to train the ensemble networks. The trained model is then used to predict the wind speed and direction. The paper performs a comparative assessment of three artificial neural network models. It also studies the performance of introducing perturbed observations to the model using six different interpolation techniques. For each technique, the computational efficiency is measured and assessed. Furthermore, the paper presents an exhaustive investigation of the performance of neural network types and several techniques in training, data splitting, and interpolation. To check the efficacy of the proposed model, the power output from a real wind farm is predicted and compared with the actual recorded measurements. The results of the comprehensive analysis show that the proposed model outperforms contending models in terms of accuracy and execution time. Therefore, this model can be used by operators to reliably generate a dispatch plan.

Superconducting magnetic energy storage coupled static compensator for stability enhancement of the doubly fed induction generator integrated system

The presence of intermittent Renewable Energy Sources (RES) has insisted on the need of finding more feasible solutions to the rising stability and reliability issues. The wind-based energy systems have emerged as prominent energy source leading to its large capacity integration in the system. Doubly Field Induction Generator (DFIG) based wind power plant, due to its various advantages are gaining popularity in the energy sector. So, it is very important to examine the stability issues and maintaining the grid connectivity in the presence of DFIG, as these are very sensitive to transient conditions. The energy storage devices can play a crucial role in mitigating these dynamic variations. In this research work,the application of the Static Compensator (STATCOM) coupled Superconducting Magnetic Energy Storage (SMES) controller is investigated for mitigating transient stability issues in the presence of DFIG connected system. The paper represents a novel control scheme for the DC link chopper circuit between STATCOM and SMES. The proposed control scheme considers the impact of three phase symmetrical fault and fast wind speed variations on the system consisting of Synchronous Generator (SG) and DFIG based Wind Energy System (WES). The comparative study of different parameters of SG and DFIG with and without the presence of this controller has been analyzed using MATLAB/Simulink environment. Simulation results indicate that the proposed control scheme can damp the oscillations of the system quickly and can achieve its equilibrium state at earliest, thus improving the stability of the system.

Drift Evaluation of a Quadrotor Unmanned Aerial Vehicle (UAV) Sprayer: Effect of Liquid Pressure and Wind Speed on Drift Potential Based on Wind Tunnel Test

Background: Unmanned Aerial Vehicles (UAVs) applied to agricultural plant protection is widely used, and the field of operation is expanding due to their high efficiency and pesticide application reduction. However, the work on pesticide drift lags behind the development of the UAV spraying device. Methods: We compared the spray drift potential at four liquid pressures of 2, 3, 4, and 5 bar ejected from the hydraulic nozzles mounted on a UAV test platform exposed to different wind speeds of 2, 4, and 6 m/s produced by a wind tunnel. The combination of the wind tunnel and the UAV test platform was used to obtain strict test conditions. The droplet size distribution under spray drift pressures was measured by a laser diffraction instrument. Results: Increasing the pressure leads to smaller droplet volume diameters and produced fine droplets of less than 100 µm. The deposition in the drift area was elevated at most of the sampling locations by setting higher pressure and faster wind speed. The deposition ratios were all higher than the flow ratios under three wind speeds after the adjustment of pressures. For most samples within a short drift distance (2–8 m), the drift with the rotor motor off was more than an order of magnitude higher than that with the rotor motor on at a pressure of 3 bar. Conclusions: In this study, the wind speed and liquid pressure all had a significant effect on the UAV spray drift, and the rotor wind significantly inhibited a large number of droplets from drifting further.

A Study on the Prediction of Damage Ranges by Leakages of Seaport-Stored Substances

In order to check the risk of hydrogen peroxide leakage from the seaport, the leakage amount was changed from 1.0 ton to 10.0 tons, with the maximum and minimum diffusion distances per month in 2020 being subsequently calculated. A total of 82 scenarios were created to confirm the change in the diffusion distance according to the amount of leakage. The scenario was analyzed based on the distance at which the risk concentration was maintained through the ALOHA Air Dispersion Models. As indicated by the analysis, when the amount of leakage is relatively large, the temperature is also high and the wind speed is fast - resulting in the maximum spread. However, when the amount of leakage was relatively minimal, the temperature was low and the wind speed remained fast - this kept diffusion to the minimum. Concerning characteristics of fast wind speeds, the dispersion length changed based on amounts of leakages where PAC-1 contains 2.0 tons, PAC-2 contains 4.0 tons, and PAC-3 contains 5.0 tons. In addition, when the amount of leakage equaled 10.0 tons, and the wind speed was high, the dispersion length reached up to 10 kms. In light of this, it was confirmed that even adjacent administrative districts were affected. Therefore, it is necessary to establish appropriate measures to prevent damage by utilizing the diffusion distance caused by chemical leakages.

Model and Experiment on Resistance Loss of Wet Chordal Grid with Spray Pressure and Structural Parameters

To reduce the dedusting resistance of wet vibrating string grille precipitators during dedusting in mine ventilation roadways, we investigated the dedusting resistance characteristics of water fog and water film coupling and determined the relationship between dedusting resistance and spray pressure, vibrating grid filling rate, and wind speed. A mathematical resistance coefficient model is established using hydrodynamics theory and capillary mechanics. The theoretical relationship of dedusting resistance is deduced. The results show that when wind speed is constant, the spray pressure and dedusting resistance are higher and the resistance is smaller with a high filling rate compared with a low filling rate. Constant spray pressure allows faster wind speeds and reverse pressure gradient forces to increase when dust flows around the wet vibrating wire, which makes the pressure distribution asymmetrical around the steel wire and increases resistance. Dust removal resistance of the resonance chord with a high filling rate is substantially lower than that with a low filling rate under the same working conditions. On the basis of satisfying the dedusting efficiency, the resonance chord dedusting system does not affect normal production and resistance is low. The spray pressure is controlled at 0.3–0.7 MPa and the optimal wind speed is 3–4 m/s. According to the theoretical calculation and experimental data, the optimal filling rate of a vibrating string grid plate is 77.8%, spray pressure is 0.7 MPa, and wind speed is 3.5 m/s. Dust removal with low resistance and improved economic benefit can thus be obtained.

Numerical simulation and analysis of outdoor wind environment in a high-rise community with matrix layout model based on computational fluid dynamics

The wind environment is an important factor affecting the comfort of the outdoor environment in high-rise residential communities. The numerical simulation of ventilation situation in the outdoor environment could provide scientific bases for the design of various elements in a community, including space layout, roads, activity spaces, water system, and plants. Taking the Changqingteng community, Xinxiang as the object, this paper numerically simulates the wind environment in summer, winter, and the transition season on THSware VENT2018, and analyzes the wind speed amplification factors, wind speed vector diagrams, and wind speed cloud maps on the outdoor environment of the community. The results show that both wind speed and wind speed amplification factor fall into the comfortable ranges in most places of the community throughout the year. In summer, only a few windless activity spaces are uncomfortable on hot and humid days. In winter, multiple wind corridors appear in the north of the community. These corridors greatly suppress the comfort of residents, owing to their fast wind speed and large wind speed amplification factor. The following measures could be taken to optimize the outdoor environment of the community: adding leisure spaces around the water system to improve comfort in summer, and setting up wind barriers by planting dense evergreen plants between the buildings on the north side to improve comfort in winter.