• Wind and Structures
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• v.17 no.6
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• pp.609-627
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• 2013

The Yingxian wooden tower in China is currently the tallest wooden tower in the world. It was built in 1056 AD and is 65.86 m high. Field measurements of wind speed and wind-induced response of this tower are conducted. The wind characteristics, including the average wind speed, wind direction, turbulence intensity, gust factor, turbulence integral length scale and velocity spectrum are investigated. The power spectral density and the root-mean-square wind-induced acceleration are analyzed. The structural modal parameters of this tower are identified with two different methods, including the Empirical Mode Decomposition (EMD) combined with the Random Decrement Technique (RDT) and Hilbert transform technique, and the stochastic subspace identification (SSI) method. Results show that strong wind is coming predominantly from the West-South of the tower which is in the same direction as the inclination of the structure. The Von Karman spectrum can describe the spectrum of wind speed well. Wind-induced torsional vibration obviously occurs in this tower. The natural frequencies identified by EMD, RDT and Hilbert Transform are close to those identified by SSI method, but there is obvious difference between the identified damping ratios for the first two modes.

• Plant Journal
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• v.12 no.3
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• pp.32-38
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• 2016

In this study, the effect of wake on the energy production of a downstream wind turbine was analyzed on the base of operation practices of wind farm in the coastal complex terrain which has 2 row array of wind turbines. And changes in the variation of wind speed and turbulence intensity was analyzed. In case wind turbines are spaced 4-rotor diameter-apart in the prevailing wind direction, reduction in energy production was confirmed due to the decrease of wind speed and the increase of turbulence intensity by wake. Especially a radical change of wind direction caused wind turbine a sudden stop and energy production significantly reduced. It is considered improvement of yaw brake can prevent the sudden stop and increase energy production.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.222-227
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• 2008

Complex terrain like hill, mountain, and escarpment etc. makes complex air flow. This topographic condition will affect not only speed but also turbulence of wind over the complex terrain. In this paper, turbulence intensities are considered to investigate characteristics of wind over cone-type hills. There are five simple hill models with different slope 0.1${\sim}$0.5(tan${\theta}$) for wind tunnel test. It was observed through wind tunnel tests that turbulence intensities of down-slope wind at the end of the 3-Dimensional hills remarkably increased but ones of windward slope wind at the front side of the hills slightly increased. Also, turbulence intensities proportionally increased with slope of the cone-type hills.

• Wind and Structures
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• v.11 no.2
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• pp.137-152
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• 2008

This paper discusses engineering aspects of the rear-flank downdraft that was recorded near Lubbock, Texas on 4 June 2002, and produced a gust wind speed nearly equal to the design value (50-year return period) for the region. The general characteristics of the storm, and the decomposition of the time histories into deterministic 'running mean' and random turbulence components are discussed. The fluctuating wind speeds generated by the event can be represented as a dominant low-frequency 'running mean' with superimposed random turbulence of higher frequencies. Spectral and correlation characteristics of the residual turbulence are found to be similar to those of high-frequency turbulence in boundary-layer winds. However, the low-frequency components in the running-mean wind speeds are spatially homogeneous, in contrast to the low-frequency turbulence found in synoptic boundary-layer winds. With respect to transmission line design, this results in significantly higher 'span reduction factors'.

• Wind and Structures
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• v.15 no.1
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• pp.43-64
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• 2012

Many potential small wind turbine locations are near obstacles such as buildings and shelterbelts, which can have a significant, detrimental effect on the local wind climate. A neural network-based model has been developed which predicts mean wind speed and turbulence intensity at points in an obstacle's region of influence, relative to unsheltered conditions. The neural network was trained using measurements collected in the wakes of 18 scale building models exposed to a simulated rural atmospheric boundary layer in a wind tunnel. The model obstacles covered a range of heights, widths, depths, and roof pitches typical of rural buildings. A field experiment was conducted using three unique full scale obstacles to validate model predictions and wind tunnel measurements. The accuracy of the neural network model varies with the quantity predicted and position in the obstacle wake. In general, predictions of mean velocity deficit in the far wake region are most accurate. The overall estimated mean uncertainties associated with model predictions of normalized mean wind speed and turbulence intensity are 4.9% and 12.8%, respectively.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.32 no.7
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• pp.549-557
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• 2008

Despite of the laminar-turbulent transition region co-exist with fully turbulence region around the leading edge of an airfoil, still lots of researchers apply to fully turbulence models to predict aerodynamic characteristics. It is well known that fully turbulent model such as standard k-model couldn't predict the complex stall and the separation behavior on an airfoil accurately, it usually leads to over prediction of the aerodynamic characteristics such as lift and drag forces. So, we apply correlation based transition model to predict aerodynamic performance of the NREL (National Renewable Energy Laboratory) Phase IV wind turbine. And also, compare the computed results from transition model with experimental measurement and fully turbulence results. Results are presented for a range of wind speed, for a NREL Phase IV wind turbine rotor. Low speed shaft torque, power, root bending moment, aerodynamic coefficients of 2D airfoil and several flow field figures results included in this study. As a result, the low speed shaft torque predicted by transitional turbulence model is very good agree with the experimental measurement in whole operating conditions but fully turbulent model(${\kappa}-\;{\varepsilon}$) over predict the shaft torque after 7m/s. Root bending moment is also good agreement between the prediction and experiments for most of the operating conditions, especially with the transition model.

• Wind and Structures
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• v.18 no.1
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• pp.69-82
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• 2014

Flow around a small white fir tree was investigated with varying the length of the bottom trunk (hereafter referred to as bottom gap). The velocity fields around the tree, which was placed in a closed-type wind tunnel test section, were quantitatively measured using particle image velocimetry (PIV) technique. Three different flow regions are observed behind the tree due to the bottom gap effect. Each flow region exhibits a different flow structure as a function of the bottom gap ratio. Depending on the gap ratio, the aerodynamic porosity of the tree changes and the different turbulence structure is induced. As the gap ratio increases, the maximum turbulence intensity is increased as well. However, the location of the local maximum turbulence intensity is nearly invariant. These changes in the flow and turbulence structures around a tree due to the bottom gap variation significantly affect the shelter effect of the tree. The wind-speed reduction is increased and the height of the maximum wind-speed reduction is decreased, as the gap ratio decreases.

• Wind and Structures
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• v.24 no.2
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• pp.185-204
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• 2017

High-resolution wind measurements at 2.25 m in height were used to investigate the mean and turbulence properties of an extreme thunderstorm wind event in West Texas. These data were combined with single Doppler scans from the Texas Tech University Ka-band mobile Doppler radars systems (TTUKa) to provide meteorological context over the surface measurement stations for portions of the outflow. Several features characteristic of a severe wind event were noted in the radar data, including a bowing portion of the thunderstorm complex and a small circulation on the leading edge. These features were reflected in the surface wind time histories and provided natural separation between various regions of the outflow. These features also contributed to the peak 1-s gust at all measurement stations. The turbulence characteristics of each outflow region were also investigated and compared. Reduced values of running turbulence intensity and elevated values of longitudinal integral scales were noted during the period of peak wind speed. Larger scales of turbulence within the outflow were also suggested via spectral analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.283-284
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• 2008