Field measurements of boundary layer wind characteristics and wind-induced responses of super-tall buildings

Fu, Jiyang; Li, Qiusheng; Wu, Jie; Xiao, Yingying; Song, Lili

doi:10.1016/j.jweia.2008.03.004

Cited by 74 publications

(41 citation statements)

References 24 publications

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“…Choi (1983) proposed that the gust factor G is proportional to I 1.27 based on the wind speed data measured in Hong Kong. This was supported by Xu and Zhan (2001) and Fu et al (2008). The simplified expression used commonly is given by…”

Section: Gust Factor and Turbulence Intensitymentioning

confidence: 87%

Wind gust and turbulence statistics of typhoons in South China

Wang

Cheng

2011

Acta Meteorol Sin

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The wind data of four typhoons were obtained and analyzed. The wind speeds were measured by sonic anemometers at four observation sites in Guangdong and Hainan provinces. Detailed analysis of the wind data was conducted to investigate the turbulence characteristics of the typhoons. Characteristics of the gust factor and the turbulence integral scale of the typhoons were concluded with high confidence. The relationships among the gust factor, gust duration time, mean wind speed, roughness length, and turbulence intensity were described. The turbulence integral scale was found to be closely related to the segment length and turbulence intensity.

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Section: Gust Factor and Turbulence Intensitymentioning

confidence: 87%

Wind gust and turbulence statistics of typhoons in South China

Wang

Cheng

2011

Acta Meteorol Sin

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“…The differences between the field measurement results and the wind tunnel data were in the range of 9.3-19.1% for the four super-tall buildings. Fu et al [36] presented the boundary layer wind characteristics and the corresponding wind-induced responses of two super-tall buildings measured on the location. By comparing the full-scale measurement results with the wind tunnel test data, it was found that the acceleration data measured on the location were consistent with those obtained from the model tests, although the model test results were generally conservative.…”

Section: High-rise Buildingsmentioning

confidence: 99%

“…Typical discrepancies were: (1) Mean and peak negative pressures at corners and separated flow regions on low-rise building roofs were underestimated in wind tunnels [7,12,[18][19][20]24]; (2) Local fluctuating pressures attributable to vortex shedding on high-rise building models differed from those on the prototype [27]; (3) Aero-elastic model tests for high-rise buildings underestimated the dynamic structural responses in the intermediate-frequency range [4]; (4) Differences between rms accelerations measured on the location and those obtained from the force balance model test were in the range of 4-25% for high-rise buildings [32,[34][35][36][37]; (5) Long-span bridges' vertical VIV amplitudes obtained using section models and full bridge aero-elastic models were much lower than those observed on the location [42,44]; (6) The pressure fluctuations measured on real structures followed non-Gaussian distributions, while the corresponding samples obtained from model tests followed Gaussian distribution [37,47,48,50]; (7) Model test results were conservative with respect to the spectral characteristics of wind-induced pressures measured on building models [17,50], since the normalized pressure spectra obtained in the wind tunnel were usually higher at high-frequency ranges than the full-scale values, and the coherences between pressure fluctuations tended to be stronger in the wind tunnel than at full scale. Taking a step forward, many related researchers explained the causes of the observed differences:…”

Section: Researchers' Explanations For the Observed Differencesmentioning

confidence: 99%

Full-Scale/Model Test Comparisons to Validate the Traditional ABL Wind Tunnel Simulation Technique: A Literature Review

Dong¹,

Peng²,

Zhao³

et al. 2017

Preprint

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Abstract:Full-scale/model test comparison studies to validate the traditional atmospheric boundary layer (ABL) wind tunnel simulation technique are reviewed. According to the literature review, notable discrepancies between full-scale measurement results and model test results were observed by most performed comparison studies, but the causes of the observed discrepancies were not revealed in a scientific way by those studies. In this regard, a new research scheme for future full-scale/model test comparison studies is proposed in this article, which utilizes the multiple-fan actively controlled wind tunnel simulation technique. With the new research scheme, future full-scale/model test comparison studies are expected to reasonably disclose the main problems with the traditional ABL wind tunnel simulation technique, and the technique can be improved correspondingly.Keywords: comparison study; full-scale measurement; wind tunnel model test; multiple-fan actively controlled wind tunnel; research scheme IntroductionAs a mature technique applied in aviation industry, the wind tunnel model test was introduced into the field of wind-engineering research and design in 1960s. After Jensen [1] proposed that the flow field simulated in the wind tunnel should be similar to the actual atmospheric boundary layer (ABL) flow field for wind-engineering model tests, simulating ABL has become an indispensable test procedure. To fulfill the task of simulating realistic ABL turbulent flow fields in the wind tunnel, passive simulation devices, including spires, roughness elements, grids and barriers, can jointly be used. It has been found that the target flow fields can be obtained by adjusting the position and the number of some devices placed in the beginning of the wind tunnel [2,3]. During the past 50 years, most scientific researches and engineering practices made by the wind-engineering community utilized the traditional ABL wind tunnel simulation technique. With this technique, theoretical achievements were made, and numerous engineering structures' safety against extreme wind events was ensured.

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“…Basically, pre-processing involved two steps: the first step identified potential data contamination and the second addressed these concerns. The quality control methods presented in the literature are based on the check of consistency with the adjacent anemometers or independent observation platforms (Schroeder et al, 2009;Fu et al, 2008;Yu et al, 2008;Vickers and Mahrt, 1997). In this study, the data pre-processing included: (1) determination of spikes in data and replacing these with five-point weighted averages; (2) decomposition of records into three dimensional components (longitudinal, lateral and vertical component); (3) separation of wind data time history into 10-min segments; (4) computation of the mean value and standard deviation for a series of moving windows with a length of 1 min; (5) considering any point in the window beyond 3.5 times the standard deviation around mean value as a spike and replacing it with five-point weighted averages; (6) moving the 1-min window with a 30 s step length and repeating step (5); (7) discarding segments if the total number of spikes in a 10-min segment exceeded 5% of the total number.…”

Section: Quality Control and Sample Selecting Criteriamentioning

confidence: 99%

“…To better understand tropical cyclone wind characteristics and their power spectra, a number of measurements have been (Xu and Zhan, 2001;Fu et al, 2008;Cao et al, 2009;Schroeder et al, 2009;Hui et al, 2009aHui et al, , 2009bMasters et al, 2010;Wang et al, 2011). A majority of these measurements found that tropical wind spectra matched von Karman spectrum (Karman, 1948).…”

Section: Introductionmentioning

confidence: 99%