scholarly journals Comments on “The Variation of Gust Factors with Mean Wind Speed and with Height”

1969 ◽  
Vol 8 (1) ◽  
pp. 167-167 ◽  
Author(s):  
Gerald C. Gill
Keyword(s):  
Wind Speed ◽  
Mean Wind Speed ◽  
Gust Factors

scholarly journals Drifting-snow studies over an instrumented mountainous site: II. Measurements and numerical model at small scale

2001 ◽  
Vol 32 ◽  
pp. 175-181 ◽  
Author(s):  
Jean-Luc Michaux ◽  
Florence Naaim-Bouvet ◽  
Mohamed Naaim
Keyword(s):  
Wind Speed ◽  
Numerical Model ◽  
Small Scale ◽  
Wind Gust ◽  
Strong Wind ◽  
Experimental Site ◽  
In Situ Data ◽  
Drifting Snow ◽  
Mean Wind Speed ◽  
Gust Factors

AbstractThe Érosion torrentielle, neige et avalanche (Etna) unit of CEMAGREF and the Centre d’Etudes de la Neige of Météo-France have been working on snowdrift for 10 years. A numerical model was developed at CEMAGREF to simulate snowdrift (Naaim and others, 1998). To validate this model on in situ data, a high-altitude experimental site was developed, located at 2700 m a.s.l. at the Lac Blanc Pass near the Alpe d’Huez ski resort. It is a nearly flat area and faces winds primarily from north and south. After describing the experimental site, we present the processed data of winter 1998/99. First, we analyze the data from CEMAGREF’s acoustic snowdrift sensor. It is sensitive to snow depth and snow-particle type, so additional calibration is necessary. Nevertheless, it allowed us to study non- stationary aspects of drifting snow. An analysis of gust factors for wind and drifting snow indicates that strong wind-gust factors exist in the mountains, and that drifting snow is more important during a regular and strong wind episode than during high wind-gust periods. Therefore, the numerical model presented here uses only the recorded mean wind speed. The model, which attempts to reproduce several days of storm, takes into account the modification of input parameters (e.g wind speed) as a function of time. The comparison between numerical results and measurements for a given meteorological event shows good agreement.

scholarly journals An Examination of Tropical and Extratropical Gust Factors and the Associated Wind Speed Histograms

2005 ◽  
Vol 44 (2) ◽  
pp. 270-280 ◽  
Author(s):  
B. M. Paulsen ◽  
J. L. Schroeder
Keyword(s):  
Wind Speed ◽  
Tropical Cyclones ◽  
Deep Convection ◽  
Transitional Flow ◽  
Wind Gust ◽  
Measuring Device ◽  
Gust Factor ◽  
Mean Wind Speed ◽  
Landfalling Tropical Cyclones ◽  
Gust Factors

Abstract A gust factor, defined as the ratio between a peak wind gust and mean wind speed over a period of time, can be used along with other statistics to examine the structure of the wind. Gust factors are heavily dependent on upstream terrain conditions (roughness), but are also affected by transitional flow regimes (specifically, changes in terrain and the distance from the upstream terrain change to the measuring device), anemometer height, stability of the boundary layer, and, potentially, the presence of deep convection. Previous studies have yielded conflicting results regarding differences in gust factors that might exist between winds generated by tropical cyclones and those generated by extratropical systems. Using high-resolution wind speed data collected from both landfalling tropical cyclones and extratropical systems, two databases of wind characteristics were developed. Gust factors from tropical cyclone and extratropical winds were examined, summarized, and compared. Further analysis was conducted to examine and compare the characteristics of the associated tropical and extratropical wind speed histograms. As expected, the mean gust factor was found to increase with increasing upstream surface roughness. Some differences were observed between data from the tropical environment and the extratropical environment. Mean gust factors from the tropical regime were found to be higher than mean gust factors from the extratropical environment within each roughness regime and the wind speed histograms generated from data from the two environments indicated some differences.

scholarly journals Wind Characteristics Investigation on The Roofs of Three Adjacent High-Rise Buildings in a Coastal Area during Typhoon Meranti

2019 ◽  
Vol 9 (3) ◽  
pp. 367 ◽  
Author(s):  
Chequan Wang ◽  
Zhengnong Li ◽  
Qizhi Luo ◽  
Lan Hu ◽  
Zhefei Zhao ◽  
...  
Keyword(s):  
Wind Speed ◽  
Turbulence Intensity ◽  
Wind Direction ◽  
Time Interval ◽  
Integral Scale ◽  
High Rise ◽  
Wind Turbulence ◽  
Mean Wind Speed ◽  
The Mean ◽  
Gust Factors

This paper presents the study of the pulsating characteristics of three adjacent high-rise buildings A, B, and C under typhoon ‘Moranti’ (2016) based on the measurement of the actual top wind speed. The studied pulsating characteristics included mean wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, wind speed spectrum and correlation. The relationships between each pulsating parameter and the relationship between the pulsating parameter and gust duration have been investigated. Results show that the mean wind speed and wind direction of three buildings are close. When U ≥ 10 m/s in three different sites at the same time, the turbulence intensity variation of three buildings is consistent and decreases when mean wind speed increases. Once only two locations are acquired simultaneously and the wind angle between 35° and 45°, the mean values of the along-wind and cross-wind turbulence of building A and building C are close. The along-wind turbulence of the three buildings is greater than the predicted Chinese codes for various terrains. The turbulence intensity and gust factors obtained through the analysis of the samples with the mean wind speed U ≥ 10 m/s are reasonable. The turbulence integral scales of buildings A and C are equal to the predicted values of ASCE-7 and AIJ-2004, whereas the turbulent integral scale of building B is evidently small. The gust factors of three buildings increase when the turbulence intensity increases; these two characteristics have a linear relationship. At the same time interval, building B has the maximum along-wind turbulence intensity and gust factors during the low wind speed period and building C achieves the minimum values. Building A acquires the maximum and building C obtains the minimum values in the high wind speed period. The turbulence intensity and gust factors of building B show a certain pulsation. Results show that turbulence intensity and gust factors are mainly affected by the short-term fluctuation of wind. The longitudinal wind speed spectrum of three buildings conforms well to the von Karman model. The correlation of along-wind speed depends on the wind speed, whereas the correlation of cross-wind direction is independent of wind speeds. The measured data and statistical parameters provide useful information for the wind resistance design of high-rise buildings in typhoon-prone areas.

Prediction of Atmospheric Turbulence Characteristics for Surface Boundary Layer using Empirical Spectral Methods

2020 ◽  
Author(s):  
Yagya Dutta Dwivedi ◽  
Vasishta Bhargava Nukala ◽  
Satya Prasad Maddula ◽  
Kiran Nair
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Surface Roughness ◽  
Wind Speed ◽  
Atmospheric Turbulence ◽  
Surface Boundary ◽  
Low Frequencies ◽  
Surface Boundary Layer ◽  
Power Spectral ◽  
Mean Wind Speed

Abstract Atmospheric turbulence is an unsteady phenomenon found in nature and plays significance role in predicting natural events and life prediction of structures. In this work, turbulence in surface boundary layer has been studied through empirical methods. Computer simulation of Von Karman, Kaimal methods were evaluated for different surface roughness and for low (1%), medium (10%) and high (50%) turbulence intensities. Instantaneous values of one minute time series for longitudinal turbulent wind at mean wind speed of 12 m/s using both spectra showed strong correlation in validation trends. Influence of integral length scales on turbulence kinetic energy production at different heights is illustrated. Time series for mean wind speed of 12 m/s with surface roughness value of 0.05 m have shown that variance for longitudinal, lateral and vertical velocity components were different and found to be anisotropic. Wind speed power spectral density from Davenport and Simiu profiles have also been calculated at surface roughness of 0.05 m and compared with k−1 and k−3 slopes for Kolmogorov k−5/3 law in inertial sub-range and k−7 in viscous dissipation range. At high frequencies, logarithmic slope of Kolmogorov −5/3rd law agreed well with Davenport, Harris, Simiu and Solari spectra than at low frequencies.

scholarly journals The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters

2018 ◽  
Vol 7 (2) ◽  
pp. 139-150 ◽  
Author(s):  
Adekunlé Akim Salami ◽  
Ayité Sénah Akoda Ajavon ◽  
Mawugno Koffi Kodjo ◽  
Seydou Ouedraogo ◽  
Koffi-Sa Bédja
Keyword(s):  
Time Series ◽  
Wind Speed ◽  
Time Series Data ◽  
Empirical Method ◽  
Likelihood Method ◽  
Series Data ◽  
New Approach ◽  
Weibull Parameters ◽  
Distribution Histogram ◽  
Mean Wind Speed

In this article, we introduced a new approach based on graphical method (GPM), maximum likelihood method (MLM), energy pattern factor method (EPFM), empirical method of Justus (EMJ), empirical method of Lysen (EML) and moment method (MOM) using the even or odd classes of wind speed series distribution histogram with 1 m/s as bin size to estimate the Weibull parameters. This new approach is compared on the basis of the resulting mean wind speed and its standard deviation using seven reliable statistical indicators (RPE, RMSE, MAPE, MABE, R2, RRMSE and IA). The results indicate that this new approach is adequate to estimate Weibull parameters and can outperform GPM, MLM, EPF, EMJ, EML and MOM which uses all wind speed time series data collected for one period. The study has also found a linear relationship between the Weibull parameters K and C estimated by MLM, EPFM, EMJ, EML and MOM using odd or even class wind speed time series and those obtained by applying these methods to all class (both even and odd bins) wind speed time series. Another interesting feature of this approach is the data size reduction which eventually leads to a reduced processing time.Article History: Received February 16th 2018; Received in revised form May 5th 2018; Accepted May 27th 2018; Available onlineHow to Cite This Article: Salami, A.A., Ajavon, A.S.A., Kodjo, M.K. , Ouedraogo, S. and Bédja, K. (2018) The Use of Odd and Even Class Wind Speed Time Series of Distribution Histogram to Estimate Weibull Parameters. Int. Journal of Renewable Energy Development 7(2), 139-150.https://doi.org/10.14710/ijred.7.2.139-150

scholarly journals Predicting Malaria Transmission Dynamics in Dangassa, Mali: A Novel Approach Using Functional Generalized Additive Models

2020 ◽  
Vol 17 (17) ◽  
pp. 6339
Author(s):  
François Freddy Ateba ◽  
Manuel Febrero-Bande ◽  
Issaka Sagara ◽  
Nafomon Sogoba ◽  
Mahamoudou Touré ◽  
...  
Keyword(s):  
Wind Speed ◽  
Malaria Incidence ◽  
Generalized Additive Models ◽  
Community Health Center ◽  
Additive Model ◽  
Additive Models ◽  
Functional Regression ◽  
Novel Approach ◽  
Malaria Incidence Rate ◽  
Mean Wind Speed

Mali aims to reach the pre-elimination stage of malaria by the next decade. This study used functional regression models to predict the incidence of malaria as a function of past meteorological patterns to better prevent and to act proactively against impending malaria outbreaks. All data were collected over a five-year period (2012–2017) from 1400 persons who sought treatment at Dangassa’s community health center. Rainfall, temperature, humidity, and wind speed variables were collected. Functional Generalized Spectral Additive Model (FGSAM), Functional Generalized Linear Model (FGLM), and Functional Generalized Kernel Additive Model (FGKAM) were used to predict malaria incidence as a function of the pattern of meteorological indicators over a continuum of the 18 weeks preceding the week of interest. Their respective outcomes were compared in terms of predictive abilities. The results showed that (1) the highest malaria incidence rate occurred in the village 10 to 12 weeks after we observed a pattern of air humidity levels >65%, combined with two or more consecutive rain episodes and a mean wind speed <1.8 m/s; (2) among the three models, the FGLM obtained the best results in terms of prediction; and (3) FGSAM was shown to be a good compromise between FGLM and FGKAM in terms of flexibility and simplicity. The models showed that some meteorological conditions may provide a basis for detection of future outbreaks of malaria. The models developed in this paper are useful for implementing preventive strategies using past meteorological and past malaria incidence.

Stochastic generation of hourly mean wind speed data

2004 ◽  
Vol 29 (14) ◽  
pp. 2111-2131 ◽  
Author(s):  
Hafzullah Aksoy ◽  
Z Fuat Toprak ◽  
Ali Aytek ◽  
N Erdem Ünal
Keyword(s):  
Wind Speed ◽  
Stochastic Generation ◽  
Wind Speed Data ◽  
Mean Wind Speed

Scale and Lag Effects on Control of Aerodynamic Power and Loads on a HAWT Rotor

2001 ◽  
Vol 123 (4) ◽  
pp. 339-345 ◽  
Author(s):  
P. J. Moriarty ◽  
A. J. Eggers, ◽  
K. Chaney ◽  
W. E. Holley
Keyword(s):  
Control System ◽  
Fatigue Life ◽  
Wind Speed ◽  
Open Loop ◽  
Time Lags ◽  
Large Power ◽  
Lag Effects ◽  
Mean Wind Speed ◽  
The Mean ◽  
High Control

The effects of rotor scale and control system lag were examined for a variable-speed wind turbine. The scale study was performed on a teetered rotor with radii ranging between 22.5m and 33.75m. A 50% increase in radius more than doubled the rated power and annual energy capture. Using blade pitch to actively control fluctuating flatwise moments allowed for significant reductions in blade mass for a fixed fatigue life. A blade operated in closed-loop mode with a 33.75m radius weighed less than an open-loop blade with a 22.5m radius while maintaining the same fatigue life of 5×109 rotations. Actuator lag reduced the effectiveness of the control system. However, 50% reductions in blade mass were possible even when implementing a relatively slow actuator with a 1 sec. time constant. Other practical limits on blade mass may include fatigue from start/stop cycles, non-uniform turbulence, tower wake effects, and wind shear. The more aggressive control systems were found to have high control accelerations near 60 deg/s2, which may be excessive for realistic actuators. Two time lags were introduced into the control system when mean wind speed was estimated in a rapidly changing wind environment. The first lag was the length of time needed to determine mean wind speed, and therefore the mean control settings. The second was the frequency at which these mean control settings were changed. Preliminary results indicate that quickly changing the mean settings (every 10 seconds) and using a moderate length mean averaging time (60 seconds) resulted in the longest fatigue life. It was discovered that large power fluctuations occurred during open-loop operation which could cause sizeable damage to a realistic turbine generator. These fluctuations are reduced by one half or more when aerodynamic loads are actively controlled.

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