Volume 15, Number 1, January 2012
Wind characteristics of a strong typhoon in marine surface
Lili Song, Q.S. Li, Wenchao Chen, Peng Qin, Haohui Huang and Y.C. He
Full Text (2220K)
High-resolution wind data were acquired from a 100-m high offshore tower during the passage of Typhoon Hagupit in September, 2008. The meteorological tower was equipped with an ultrasonic anemometer and a number of cup anemometers at heights between 10 and 100 m. Wind characteristics of the strong typhoon, such as mean wind speed and wind direction, turbulence intensity, turbulence integral length scale, gust factor and power spectra of wind velocity, vertical profiles of mean wind speed were investigated in detail based on the wind data recorded during the strong typhoon. The measured results revealed that the wind characteristics in different stages during the typhoon varied remarkably. Through comparison with non-typhoon wind measurements, the phenomena of enhanced levels of turbulence intensity, gust factors, turbulence integral length scale and spectral magnitudes in typhoon boundary layer were observed. The monitored data and analysis results are expected to be useful for the wind-resistant design of offshore structures and buildings on seashores in typhoon-prone regions.
strong typhoon; wind characteristic; wind data measurement.
Lili Song : Guangzhou Institute of Tropical and Marine Meteorology, Guangzhou, 510080, China
Q.S. Li : Department of Building and Construction, City University of Hong Kong, Hong Kong
Wenchao Chen , Peng Qin and Haohui Huang : Guangdong Climate Centre, Guangzhou, 510080, China
Y.C. He : Department of Building and Construction, City University of Hong Kong, Hong Kong
Computing turbulent far-wake development behind a wind turbine with and without swirl
Yingying Hu, Siva Parameswaran, Jiannan Tan, Suranga Dharmarathne, Neha Marathe, Zixi Chen, Ronald Grife and Andrew Swift
Full Text (1178K)
Modeling swirling wakes is of considerable interest to wind farm designers. The present work is an attempt to develop a computational tool to understand free, far-wake development behind a single rotating wind turbine. Besides the standard momentum and continuity equations from the boundary layer theory in two dimensions, an additional equation for the conservation of angular momentum is introduced to study axisymmetric swirl effects on wake growth. Turbulence is simulated with two options: the standard k-e model and the Reynolds Stress transport model. A finite volume method is used to discretize the governing equations for mean flow and turbulence quantities. A marching algorithm of
expanding grids is employed to enclose the growing far-wake and to solve the equations implicitly at every axial step. Axisymmetric far-wakes with/without swirl are studied at different Reynolds numbers and swirl numbers. Wake characteristics such as wake width, half radius, velocity profiles and pressure profiles are computed. Compared with the results obtained under similar flow conditions using the
computational software, FLUENT, this far-wake model shows simplicity with acceptable accuracy, covering large wake regions in far-wake study.
far wake; swirl; boundary layer; self-similarity; k-e model; Reynolds Stress transport model.
Yingying Hu, Siva Parameswaran, Jiannan Tan, Suranga Dharmarathne and Zixi Chen: Department of Mechanical Engineering, Texas Tech University, Lubbock, Texas, USA
Neha Marathe and Andrew Swift : Wind Science and Engineering Research Center, Department of Civil Engineering, Texas Tech University, Lubbock, Texas, USA
Ronald Grife : Vestas Technology R&D Americas, Inc., USA
A proposed technique for determining aerodynamic pressures on residential homes
Tuan-Chun Fu, Aly Mousaad Aly, Arindam Gan Chowdhury, Girma Bitsuamlak, DongHun Yeo and Emil Simiu
Full Text (3429K)
Wind loads on low-rise buildings in general and residential homes in particular can differ significantly depending upon the laboratory in which they were measured. The differences are due in large part to inadequate simulations of the low-frequency content of atmospheric velocity fluctuations in the laboratory and to the small scale of the models used for the measurements. The imperfect spatial coherence of the low frequency velocity fluctuations results in reductions of the overall wind effects with respect to the case of perfectly coherent flows. For large buildings those reductions are significant. However, for buildings with sufficiently small dimensions (e.g., residential homes) the reductions are relatively small. A technique is proposed for simulating the effect of low-frequency flow fluctuations on such buildings more effectively from the point of view of testing accuracy and repeatability than is
currently the case. Experimental results are presented that validate the proposed technique. The technique eliminates a major cause of discrepancies among measurements conducted in different laboratories. In addition, the technique allows the use of considerably larger model scales than are possible in conventional testing. This makes it possible to model architectural details, and improves Reynolds number similarity. The technique is applicable to wind tunnels and large scale open jet facilities, and can help to standardize
flow simulations for testing residential homes as well as significantly improving testing accuracy and repeatability. The work reported in this paper is a first step in developing the proposed technique. Additional tests are planned to further refine the technique and test the range of its applicability.
aerodynamics; atmospheric surface layer; building technology; low-rise structures; open jet facilities; residential buildings; wind engineering; wind tunnels.
Tuan-Chun Fu,Arindam Gan Chowdhury and Girma Bitsuamlak :Department of Civil and Environ. Engineering, Florida International University, Miami, Florida 33174, USA
Aly Mousaad Aly :Intl. Hurricane Research Center, Florida International University, Miami, Florida 33174, USA
DongHun Yeo and Emil Simiu : National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA
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 networkbased 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.
wind tunnel; small wind turbine; wind energy; micrositing; wake prediction; anemometer; sheltering; neural network.
Andrew William Brunskill and William David Lubitz : University of Guelph, School of Engineering. 50 Stone Road East, Guelph, Ontario, Canada. N1G 2W1
Over the last decade substantial improvements have been made in our ability to observe the tropical cyclone boundary layer. Low-level wind speed maxima have been frequently observed in Global Positioning System dropwindsonde (GPS sonde) profiles. Data from GPS sondes and coastal Doppler radars were employed to evaluate the characteristics of tropical cyclone vertical wind profiles in open ocean conditions and at landfall. Changes to the mean vertical wind profile were observed azimuthally
and with decreasing radial distance toward the cyclone center. Wind profiles within the hurricane boundary layer exhibited a logarithmic increase with height up to the depth of the wind maximum.
tropical cyclones; GPS dropwindsonde; radar; wind; profiles; low-level jets; velocity azimuth display.
Ian M. Giammanco and John L. Schroeder: Wind Science and Engineering Research Center, Texas Tech University, Lubbock, Texas USA
Mark D. Powell : NOAA/AOML Hurricane Research Division, Miami, Florida, USA