Variation Of Mean Wind Speed Research Articles

A neural networks approach for wind speed prediction

This paper introduces neural networks technique for wind speed prediction and compares its performance with an autoregressive model. First, we studied the statistical characteristics of mean monthly and daily wind speed in Jeddah, Saudi Arabia. The autocorrelation coefficients are computed and the correlogram is found compatible with the real diurnal variation of mean wind speed. The stochastic time series analysis is found to be suitable for the description of autoregressive model that involves a time lag of one month for the mean monthly prediction and one day for the mean daily wind speed prediction. The results on a testing data indicate that the neural network approach outperforms the AR model as indicated by the prediction graph and by the root mean square errors.

市街地上空における気流性状の数値計算 : その2 建物の密度変化に伴う平均風速および乱れの強さの変化

市街地上空における気流性状の数値計算 : その2 建物の密度変化に伴う平均風速および乱れの強さの変化

弾塑性構造物の風応答性状ならびにその予測に関する研究 : その3 提案予測手法の風速変化に対する適用性

While stochastic methods to evaluate wind-induced response of elastic structures are well established, authors have previously proposed stochastic methods to predict wind-induced inelastic response. However, these stochastic methods for elastic and inelastic structures are based on a stationary random process with a fixed mean wind speed and do not consider the rapid variation of mean wind speed as shown in which a typhoon passes through a site. In this paper, inelastic response under wind loads with variation of mean wind speed is predicted by applying methods previously proposed in Ref. [1] and [2]. It is confirmed that proposed methods are also valid for wind loads with variation of mean wind speed by comparison with results of time history response analysis.

Statistical characteristics of wind in Saudi Arabia

The statistical characteristics of wind at 10 locations in the Kingdom of Saudi Arabia are studied. The autocorrelation coefficients are computed and correlograms are found compatible with the real diurnal variation of mean wind speed for almost all the locations. The stochastic time series analysis is found to be suitable for the description of autoregressive models involving time lags of 1 and 24 h. The forecast wind values obtained from these autoregressive models are compared with the observed wind data for almost all the locations and are found to be in very good agreement.

A study on variable amplitude load fatigue and an expert system for fatigue assessment of highway steel bridges. (Dissertation): Melhem, H.G.Diss. Abstr. Int. Sept. 1990 51, (3), 373 pp

This study investigates the effect of variability and uncertainty of wind and wave conditions on the short-term fatigue damage of a 10-MW floating wind turbine drivetrain. Global dynamic responses of a semi-submersible wind turbine are calculated by aero-hydro-servo-elastic simulations in various environmental conditions. Then, rotor and generator loads, as well as nacelle motions from the global analysis are provided to a drivetrain model to investigate its dynamics. One-hour fatigue damage of the drivetrain bearings is calculated based on the bearing loads and speeds, and the effect of uncertainties related to wind and waves is assessed. The results indicate that the variations of mean wind speed, turbulence intensity and wind shear have great effects on the studied drivetrain. The effect of uncertainties of irregular waves on the drivetrain fatigue damage is small. Five wind and wave random samples are sufficient for dynamic analysis of the drivetrain to achieve accurate results at a reasonable computational cost. Among the drivetrain components, the main bearings are generally most sensitive to the investigated environmental variables. Finally, this study discusses the variation of environmental variables in terms of their relative importance for drivetrain analysis. The results provide a basis for establishing improved design standards and engineering practice for design and analysis of floating wind turbine drivetrains.

Characteristics of natural wind - Pt. I: Mean flow

The aerodynamic friction offered by various objects on the earth and the earth itself to the movement of air creates wind forces on structures. These wind forces have become more and more critical due to the more slender and unusual design of present day structures. The available data on mean wind speed measurement in the lower part of the atmospheric boundary layer, as relevant to wind loading on structures, are analysed critically and correlated analytically. It is concluded that under certain conditions the variation of mean wind speed with height ill neutral stability can be satisfactorily represent6d by a simple power law. The index of the power law and the corresponding gradi6llt height must, however, be varied to take account of the roughness of the surface. Further the total change in mean wind direction over a few hundred feet being a few degrees, may be neglected during considerations of most structures. Finally suggestions are made for the power law exponent, gradient height and the surface drag coefficient for the four typical categories of terrain. The suggested values are confirmed by recent measurements of wind speed made in various parts of the world.

Wind structure in the atmospheric boundary layer

The semi-empirical laws for the variation of mean wind speed with height and for the statistical properties of the turbulent fluctuations are briefly outlined. Similarity considerations provide some useful ordering of the mean wind profile characteristics in relation to surface roughness and thermal stratification. Appreciable uncertainties prevail, however, especially as a consequence of the effect of thermal stratification and of variable terrain roughness. Some generalization on similarity grounds can also be made regarding the fluctuations of horizontal wind speed as a function of roughness and stability, but there are wide variations of spectral density and scale which are not immediately explicable and which at present preclude anything more than a relatively coarse specification of the spectrum. Features which are of special relevance to architectural aerodynamics and which are discussed briefly are: ( a ) the difficulty of generalizing about the wind profile and turbulence above an urban complex; ( b ) the requirement for estimating the magnitudes of extreme gusts as a function of mean wind speed, averaging time and height; ( c ) the problem of generalizing about flow properties below roof level; ( d ) the effect of urban airflow on the travel and dispersion of pollutants

The Diurnal Variation of Mean Wind Speed at Four Locations in Kenya and Tanzania

The Diurnal Variation of Mean Wind Speed at Four Locations in Kenya and Tanzania

Gustiness and temperature at Nagpur

Ten years autographic records of wind and temperature have been utilised for the present study. The seasonal and diurnal variations of mean wind speed, average range of gusts and gustiness along with the temperature variations have been worked out.

Wind and Temperature Profile Characteristics from Observations on a 1400 ft Tower

Profiles of mean wind speed obtained from a 1420-ft tower are analyzed on the basis of similarity theory to determine the relationship of profile shape to lapse rate structure. A total of 274 profiles representing four observation times (0600, 1000, 1400, and 1800 CST) are used in the analysis. Thirty minute averages of the wind speed are taken at eleven levels on the tower at these observation times. The wind speed values are normalized by means of the friction velocity as well as a reference height velocity computed at the lowest observation level, and profiles for these wind speeds are grouped according to profile shape characteristics. For each group, an average profile is computed and the vertical variation of mean wind speed is compared to a logarithmic or power law profile form. Results of the study indicate that the mean wind profiles are dependent on the lapse rate structure and can be divided into “non-inversion” (lapse rates greater than isothermal) and “inversion” (lapse rates less than isothermal) profiles. For near adiabatic or slightly unstable lapse rates (mid-day non-inversion profiles), the logarithmic wind law represents the data well to a height of 300 to 400 ft. Above this height the wind speed is nearly constant. The more stable non-inversion wind profiles (lapse rates varying from about 2F to 5F per 1000 ft) generally show greater wind shears. These profiles are represented with a power law. The wind profiles associated with lapse rates containing inversions are highly variable and depend on the nature of the inversion present. There appears to be an inter-dependence of vertical shear and inversion lapse rates for these profiles.