scholarly journals Study on Typhoon Characteristic Based on Bridge Health Monitoring System

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Xu Wang ◽  
Bin Chen ◽  
Dezhang Sun ◽  
Yinqiang Wu
Keyword(s):  
Wind Speed ◽  
Monitoring System ◽  
Wind Velocity ◽  
Gaussian Distribution ◽  
Full Range ◽  
Integral Scale ◽  
Gust Factor ◽  
Wind Speeds ◽  
Bridge Health Monitoring ◽  
Mean Wind Speed

Through the wind velocity and direction monitoring system installed on Jiubao Bridge of Qiantang River, Hangzhou city, Zhejiang province, China, a full range of wind velocity and direction data was collected during typhoon HAIKUI in 2012. Based on these data, it was found that, at higher observed elevation, turbulence intensity is lower, and the variation tendency of longitudinal and lateral turbulence intensities with mean wind speeds is basically the same. Gust factor goes higher with increasing mean wind speed, and the change rate obviously decreases as wind speed goes down and an inconspicuous increase occurs when wind speed is high. The change of peak factor is inconspicuous with increasing time and mean wind speed. The probability density function (PDF) of fluctuating wind speed follows Gaussian distribution. Turbulence integral scale increases with mean wind speed, and its PDF does not follow Gaussian distribution. The power spectrum of observation fluctuating velocity is in accordance with Von Karman spectrum.

Boundary Layer Wind Characteristics over Urban Area

2014 ◽  
Vol 501-504 ◽  
pp. 2297-2300
Author(s):  
Lun Hai Zhi
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Urban Area ◽  
Atmospheric Turbulence ◽  
Wind Velocity ◽  
Three Dimensional ◽  
Tall Buildings ◽  
Gust Factor ◽  
Mean Wind Speed ◽  
Wind Characteristics

This paper presents statistical analysis results of wind speed and atmospheric turbulence data measured from a meteorological station in Beijing and is primarily intended to provide useful information on boundary layer wind characteristics for wind-resistant design of tall buildings and high-rise structures. Wind velocity data in longitudinal, lateral and vertical directions, which were recorded from an ultrasonic anemometer during windstorms, are analyzed and discussed. Atmospheric turbulence information such as turbulence intensity, gust factor, turbulence integral length scale and power spectral densities of the three-dimensional fluctuating wind velocity are presented and used to evaluate the adequacy of existing theoretical and empirical models. The objective of this study is to investigate the profiles of mean wind speed and atmospheric turbulence characteristics over a typical urban area.

scholarly journals Wind Power potential in Kigali and Western provinces of Rwanda

2015 ◽  
Vol 2 (1) ◽  
pp. 25-36
Author(s):  
Otieno Fredrick Onyango ◽  
Sibomana Gaston ◽  
Elie Kabende ◽  
Felix Nkunda ◽  
Jared Hera Ndeda
Keyword(s):  
Wind Speed ◽  
Probability Density ◽  
Wind Power ◽  
Wind Direction ◽  
Small Scale ◽  
Energy Potential ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Energy Potential ◽  
Low Wind Speeds

Wind speed and wind direction are the most important characteristics for assessing wind energy potential of a location using suitable probability density functions. In this investigation, a hybrid-Weibull probability density function was used to analyze data from Kigali, Gisenyi, and Kamembe stations. Kigali is located in the Eastern side of Rwanda while Gisenyi and Kamembe are to the West. On-site hourly wind speed and wind direction data for the year 2007 were analyzed using Matlab programmes. The annual mean wind speed for Kigali, Gisenyi, and Kamembe sites were determined as 2.36m/s, 2.95m/s and 2.97m/s respectively, while corresponding dominant wind directions for the stations were ,  and  respectively. The annual wind power density of Kigali was found to be  while the power densities for Gisenyi and Kamembe were determined as and . It is clear, the investigated regions are dominated by low wind speeds thus are suitable for small-scale wind power generation especially at Kamembe site.

scholarly journals A Wind Tunnel Study on the Correlation between Urban Space Quantification and Pedestrian–Level Ventilation

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 564 ◽  
Author(s):  
Li ◽  
Peng ◽  
Ji ◽  
Hu ◽  
Ding
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Velocity ◽  
Urban Space ◽  
Speed Ratio ◽  
Spatial Indices ◽  
Spatial Characteristics ◽  
Spatial Partition ◽  
Mean Wind Speed ◽  
Partition Method

Correlation research on urban space and pedestrian–level wind (PLW) environments is helpful for improving the wind comfort in complex urban space. It could also be significant for building and urban design. Correlation research is usually carried out in a space with clear urban spatial characteristics, so it is necessary to define the space first. In this paper, a typical urban area in Nanjing, China, is selected as the research object, and a spatial partition method is used to divide the real complex urban space into subspaces. The urban spatial characteristics of such subspaces are quantified using three urban spatial indices: openness (O), area (A), and shape (S). By comparing the quantitative results, 24 (12 pairs) subspaces with prominent urban spatial indices are selected as the correlation research cases. The 24 subspaces also provide a reference for the layout of the measurement points in a wind tunnel experiment. This is a new arrangement for locating the measurement points of a wind tunnel for correlation research. In the experiment, 45 measurement points are located, and the mean wind velocity of four different wind directions at 45 measurement points is experimented. The results clearly show that, when the experimental conditions are the same, the changes of mean wind velocity ratio (UR) of 24 (12pairs) subspaces under the four experimental wind directions are close. The URs of the subspaces are not significantly affected by the wind direction, which is affected more by the subspaces’ spatial characteristics. When making the correlation analysis between mean wind speed ratio and spatial characteristics’ indices, a direct numerical comparison was not able to find a correlation. By comparing the difference values of mean wind speed (△UR) and indices between each pair of subspaces, the correlation between UR and openness of subspaces were found. Limited by spatial partition method, the correlation between UR and the other indices was not obvious.

Field measurement of near-surface typhoon characteristics using a smart monitoring system on a long-span arch bridge site

2019 ◽  
Vol 22 (8) ◽  
pp. 1977-1987
Author(s):  
Xu Wang ◽  
Huaqiang Li ◽  
Zengshun Chen ◽  
Yuanhao Qian ◽  
Yanru Wang ◽  
...  
Keyword(s):  
Monitoring System ◽  
Wind Velocity ◽  
Turbulence Intensity ◽  
Eastern China ◽  
Mean Flow ◽  
Time Duration ◽  
Lateral Direction ◽  
Near Surface ◽  
Gust Factor ◽  
The Mean

During landfall of Typhoon Haikui in Eastern China in 2012, ground level wind data were recorded using a smart monitoring system installed on JiuBao Bridge in Hangzhou, China. This article documents the mean flow and turbulence characteristics from data recorded during the storm. The results show that both turbulence intensity and gust factor decrease with the increase in the mean wind velocity. However, as the mean wind velocity increases, this trend gradually attenuates. The peak factor distribution with gust averaging time duration derived with the Typhoon Haikui data agrees well with the Durst curve. However, the longitudinal gust factor derived from the typhoon wind-speed record in this study is higher compared with the curves proposed by Durst and Krayer-Marshall. Analyses of the gust factor distribution with the turbulence intensity during the passage of the storm reveal a similarity to the empirical curves of Ishizaki and Choi. Results show that the relationship between lateral turbulence and gust factors can be well represented by a quadratic polynomial. Turbulence scale increased with mean wind velocity. The values of autocorrelation coefficients in longitudinal direction are larger than those in lateral direction. There has no obvious dependency of cross-correlation coefficients with mean wind velocity. In general, the wind characteristics in this study are shown to be very similar to those of winds under normal circumstance.

scholarly journals Validation of Dual-Doppler Wind Profiles with in situ Anemometry

2015 ◽  
Vol 32 (5) ◽  
pp. 943-960 ◽  
Author(s):  
W. Scott Gunter ◽  
John L. Schroeder ◽  
Brian D. Hirth
Keyword(s):  
High Resolution ◽  
Wind Speed ◽  
Doppler Radar ◽  
Heavy Precipitation ◽  
Atmospheric Conditions ◽  
Wind Speeds ◽  
Time Histories ◽  
Mean Wind Speed ◽  
Wind Profiles

AbstractTypical methods used to acquire wind profiles from Doppler radar measurements rely on plan position indicator (PPI) scans being performed at multiple elevation angles to utilize the velocity–azimuth display technique or to construct dual-Doppler synthesis. These techniques, as well as those employed by wind profilers, often produce wind profiles that lack the spatial or temporal resolution to resolve finescale features. If two radars perform range–height indicator (RHI) scans (constant azimuth, multiple elevations) along azimuths separated by approximately 90°, then the intersection of the coordinated RHI planes represents a vertical set of points where dual-Doppler wind syntheses are possible and wind speed and direction profiles can be retrieved. This method also allows for the generation of high-resolution wind time histories that can be compared to anemometer time histories. This study focuses on the use of the coordinated RHI scanning strategy by two high-resolution mobile Doppler radars in close proximity to a 200-m instrumented tower. In one of the first high-resolution, long-duration comparisons of dual-Doppler wind synthesis with in situ anemometry, the mean and turbulence states of the wind measured by each platform were compared in varying atmospheric conditions. Examination of mean wind speed and direction profiles in both clear-air (nonprecipitating) and precipitating environments revealed excellent agreement above approximately 50 m. Below this level, dual-Doppler wind speeds were still good but slightly overestimated as compared to the anemometer-measured wind speeds in heavy precipitation. Bulk turbulence parameters were also slightly underestimated by the dual-Doppler syntheses.

Wind tunnel tests on the characteristics of wind fields over a simplified gorge

2016 ◽  
Vol 20 (10) ◽  
pp. 1599-1611 ◽  
Author(s):  
Peng Hu ◽  
Yongle Li ◽  
Yan Han ◽  
CS Cai ◽  
Guoji Xu
Keyword(s):  
Wind Speed ◽  
Wind Tunnel ◽  
Wind Direction ◽  
Wind Field ◽  
Small Range ◽  
Wind Fields ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Characteristics ◽  
The Mean

Characteristics of wind fields over the gorge or valley terrains are becoming more and more important to the structural wind engineering. However, the studies on this topic are very limited. To obtain the fundamental characteristics information about the wind fields over a typical gorge terrain, a V-shaped simplified gorge, which was abstracted from some real deep-cutting gorges where long-span bridges usually straddle, was introduced in the present wind tunnel studies. Then, the wind characteristics including the mean wind speed, turbulence intensity, integral length scale, and the wind power spectrum over the simplified gorge were studied in a simulated atmospheric boundary layer. Furthermore, the effects of the oncoming wind field type and oncoming wind direction on these wind characteristics were also investigated. The results show that compared with the oncoming wind, the wind speeds at the gorge center become larger, but the turbulence intensities and the longitudinal integral length scales become smaller. Generally, the wind fields over the gorge terrain can be approximately divided into two layers, that is, the gorge inner layer and the gorge outer layer. The different oncoming wind field types have remarkable effects on the mean wind speed ratios near the ground. When the angle between the oncoming wind and the axis of the gorge is in a certain small range, such as smaller than 10°, the wind fields are very close to those associated with the wind direction of 0°. However, when the angle is in a larger range, such as larger than 20°, the wind fields in the gorge will significantly change. The research conclusions can provide some references for civil engineering practices regarding the characteristics of wind fields over the real gorge terrains.

scholarly journals Evaluation of wind characteristics in Bac Lieu in 2016 using the weibull function

2017 ◽  
Vol 17 (4B) ◽  
pp. 37-43
Author(s):  
Pham Xuan Thanh ◽  
Nguyen Xuan Anh ◽  
Le Van Luu ◽  
Hiep Van Nguyen ◽  
Hoang Hai Son ◽  
...  
Keyword(s):  
Wind Speed ◽  
Shape Factor ◽  
Maximum Energy ◽  
Weibull Function ◽  
Data Set ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Characteristics ◽  
Two Parameters ◽  
Factor C

In this paper, the characteristics of wind speed at 20 m height at the Bac Lieu atmospheric physic station (Bac Lieu station) in 2016 were evaluated using the Weibull distribution function. The wind speed data set (every minute) from January 7th  to December 31st, 2016 was used to calculate the two parameters of  Weibull function including Weibull shape factor “k” and Weibull scale factor “c”. The results showed that at the Bac Lieu station in 2016, the values of k and c were 1.69 and 3.91, respectively. Some characteristics of wind speed were also estimated such as wind energy density (Pa/A=57.3 W/m2), wind speed of maximum energy carrier (Vmec=6.2 m/s), the most probable wind speed (Vmp=2.3 m/s), mean wind speed (Vmean­=3.5 m/s)  and standard deviation of wind speeds (s = 2.1 m/s).

scholarly journals Evaluation of the Technical Wind Energy Potential of Kisii Region Based on the Weibull and Rayleigh Distribution Models

2018 ◽  
Author(s):  
Laban N. Ongaki ◽  
Christopher M. Maghanga ◽  
Joash Kerongo
Keyword(s):  
Wind Speed ◽  
Rayleigh Distribution ◽  
Series Data ◽  
Energy Potential ◽  
Distribution Models ◽  
Wind Speeds ◽  
Average Wind ◽  
Mean Wind Speed ◽  
Wind Energy Potential

The research sought to investigate the long term characteristics of wind in the Kisii region (elevation 1710m above sea level, 0.68oS, 34.79o E). Wind speeds were analyzed and characterized on short term (per month for a year) and then simulated for long term (ten years) measured hourly series data of daily wind speeds at a height of 10m. The analysis included daily wind data which was grouped into discrete data and then calculated to represent; the mean wind speed, diurnal variations, daily variations as well as the monthly variations. The wind speed frequency distribution at the height 10 m was found to be 2.9ms-1 with a standard deviation of 1.5. Based on the two month’s data that was extracted from the AcuRite 01024 Wireless Weather Stations with 5-in-1 Weather Sensor experiments set at three sites in the region, averages of wind speeds at hub heights of 10m and 13m were calculated and found to be 1.7m/s, 2.0m/s for Ikobe station, 2.4m/s, 2.8m/s for Kisii University stations, and 1.3m/s, 1.6m/s for Nyamecheo station respectively. Then extrapolation was done to determine average wind speeds at heights (20m, 30m, 50m, and 70m) which were found to be 85.55W/m2, 181.75W/m2, 470.4W/m2 and 879.9W/m2 respectively. The wind speed data was used statistically to model a Weibull probability density function and used to determine the power density for Kisii region.

scholarly journals The Potential Wind Power Resource in Central-South of the Constanta County

2019 ◽  
Vol 15 (3) ◽  
pp. 1-12
Author(s):  
Emilian Boboc
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Extreme Values ◽  
Reanalysis Data ◽  
Value Theory ◽  
Physical Models ◽  
Structural Safety ◽  
Energy Yield ◽  
Wind Speeds ◽  
Mean Wind Speed

Abstract Usually, wind turbine generator’s structures or radio masts are located in wind exposed sites. The paper aims to investigate the wind conditions in the nearby area of Cobadin Commune, Constanta County, Romania at heights of 150-200m above the surface using global reanalysis data sets CFSR, ERA 5, ERA I and MERRA 2. Using the extreme value theory and the physical models of the datasets, the research focuses on the assessment of the maximum values that are expected for the wind speeds, but the wind statistics created can be used for a further wind or energy yield calculation. Without reaching the survival wind speed for wind turbine generators, with mean wind speed values higher than 7 m/s and considering the cut-in and cut-out wind speeds of 3 m/s, respectively 25 m/s, the site can be exploited in more than 90% of the time to generate electricity, thus, the paper is addressed to the investors in the energy of renewable sources. At the same time, the insights of the wind characteristics and the knowledge of the extreme values of the wind speed can be useful, not just for the designers, in the rational assessment of the structural safety of wind turbines, but also those evaluating the insured losses.

scholarly journals Assessment of wind energy potential in East Azarbaijan province of Iran (Case Stady: Sahand station)

2015 ◽  
Vol 17 (2) ◽  
pp. 418-425
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Fossil Fuels ◽  
Ground Level ◽  
Energy Potential ◽  
Wind Speeds ◽  
Mean Wind Speed ◽  
Wind Energy Potential ◽  
Seasonal Wind

<p>Today&#39;s world requires a change in how the use of different types of energy. With declining reserves of fossil fuels for renewable energies is of course the best alternative. Among the renewable energy from the wind can be considered one of the best forms of energy can be introduced. Accordingly, most countries are trying to identify areas with potential to benefit from this resource.</p> <p>The aim of this study was to assess the potential wind power in Sahand station of Iran country. Hourly measured long term wind speed data of Sahand during the period of 2000-2013 have been statistically analyzed. In this study the wind speed frequency distribution of location was found by using Weibull distribution function. The wind energy potential of the location has been studied based on the Weibull mode. The results of this study show that mean wind speed measured at 10 m above ground level is determined as 5.16 m/s for the studied period. This speed increases by, respectively, 34.78 % and 41.21 %, when it is extrapolated to 40 and 60 m hub height.</p> <div> <p>Long term seasonal wind speeds were found to be relatively higher during the period from January to September. At the other hand, higher wind speeds were observed between the period between 06:00 and 18:00 in the day. These periods feet well with annual and daily periods of maximum demand of electricity, respectively.&nbsp;</p> </div> <p>&nbsp;</p>

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