J. Cent. South Univ. (2017) 24: 2421-2430

DOI: https://doi.org/10.1007/s11771-017-3653-z

Near ground wind characteristics during typhoon Meari:Turbulence intensities, gust factors, and peak factors

WANG Xu(王旭)^{1, 2}, HUANG Peng(黄鹏)², YU Xian-feng(余先锋)³, HUANG Chao(黄超)¹

1. State Key Laboratory Breeding Base of Mountain Bridge and Tunnel Engineering,Chongqing Jiaotong University, Chongqing 400074, China;

2. State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai 200092, China;

3. State Key Laboratory of Subtropical Building Science, South China University of Technology,Guangzhou 510640, China

Central South University Press and Springer-Verlag GmbH Germany 2017

Abstract: Wind data were collected during the 2011 typhoon Meari at heights of 10, 20, 30, and 40 m above the ground using a 40 m high anemometer tower in the coastal area near Shanghai Pudong International Airport. Wind speeds and directions, turbulence intensities, gust factors, and peaks were analyzed using the time records of wind speed. The results show that turbulence intensity components in longitudinal, lateral, and vertical directions decrease with mean wind speed, regardless of elevations, and the turbulence intensities are in a linear relationship with mean wind speeds. The ratios of three turbulence intensity components (i.e. I_u, I_v, I_w) at heights of 10, 20 and 40 m were calculated and equal to be 1:0.88:0.50, 1:0.84:0.57, and 1:0.9:0.49, respectively. In addition, the gust factors in three directions exhibit a reduction with increasing mean wind speed. The peak factors at different heights show a similar trend and slightly decrease with mean wind speed; average peak factors for all 10-min data from Typhoon Meari are 2.43, 2.48, and 2.47, respectively.

Key words: typhoon Meari; wind characteristics; turbulence intensity; gust factor; peak factor

1 Introduction

China experiences frequent typhoon disasters. Typhoons often form in the West Pacific Ocean and the South China Sea and strike the southern and southeastern coastal areas of China. Landfalling typhoons usually lead to multiple hazards, including extreme winds, heavy rainfall, strong storm surge, hails, and tornadoes [1, 2], which could cause huge economic losses and pose a threat to life safety. Based on post-typhoon surveys in the China coastal areas, structural damages, especially low-rise buildings, account for more than 50% of total losses. In order to mitigate typhoon-induced structural damage and improve structural performance during high winds, it is of significance to have a better understanding of the characteristics of typhoons, including the distribution and magnitude of wind fields. Field measurement has been regarded as the most effective approach to the identification of wind-field characteristics and has gradually determined the basic long-term direction of wind-resistance research in structures. This research is of great importance to engineering design and hazard prevention and mitigation.

In past decades, worldwide researchers obtained valuable results through large-scale observation and study of typhoons [3–7], and some countries have established databases of wind characteristics to develop win load standard and codes. Several developed countries, e.g., America, Japan, Canada, United Kingdom, and Australia, have incorporated existing field measurements into their wind load provisions to guide structural design under extreme climatic conditions. However, due to the requirement of accurate data acquisition system and cost, typhoon observation projects are by far limited. In China, a lack of measured data during extreme wind events has significantly affected the improvement to building codes and the development of structural retrofits.

Based on field surveys and assessment of residential building characteristics in the China southeast coast area [8–10], a full-scale experiment was set up in the coastal area of Pudong Airport in Shanghai to study near ground wind characteristics and wind effects on the low-rise building. The system consists of a full-scale experimental building and a 40-m tower upwind of the building, in the prevailing wind directions [11]. This study presents the wind data recorded during Typhoon Meari that are used to analyze the main characteristics of the typhoon, including wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and the power spectrum of wind speeds. These research results will provide a basis for wind-resistant design of low-rise buildings in China’s coastal areas.

2 Experimental setup

2.1 Description of typhoon Meari

The 2011 Typhoon Meari is characterized by a wide range of influence, fast forward motion, and small intensity variations. The minimum distance between the observation site and the eyewall of the typhoon is about 250 km. Winds of force 7–8 occurred along the Pudong coast of Shanghai and winds of force 6–8 in Shanghai.

2.2 Experimental instruments and facilities

The lattice tower for measuring wind is 40 m in height and is erected on a flat area close to the Yangtze River estuary, approximately 500 m away from the east coast. The field laboratory is located in a flat area, which is very suitable for field measurement. Three types of anemometers are used: three-dimensional sonic anemometers (R.M. Young 81000), two-dimensional sonic anemometers (R.M. Young 85106), and propeller anemometers (R.M. Young 05305V). The sampling frequency is 4 Hz, and the anemometers are installed at heights of 10, 20, 30, and 40 m to record wind speeds and directions. Figure 1 shows a diagram of the arrangement of the anemometers. 0^o wind direction is referenced to face north and the wind angles increase in a clockwise direction. The measured data from the three-dimensional sonic anemometer are selected for analysis, due to this instrument being capable of recording wind-speed fluctuations in three directions. Measured data from the other types of anemometers are used for calibration and correction of the data.

3 Data processing

3.1 Turbulence intensity

Turbulence intensity is one of the main parameters for determining wind load on structures. Given a wind R.M.Young 81000 speed record with duration of T, the turbulence intensity for an average gust time t_g can be expressed as [12, 13]

                  (1)

where I_i(T, t_g) is the turbulence intensity for average gust time t_g and u′_i(t_g is the mean fluctuating wind speed over t_g (N=T/t, i=u, v, w). In this study, the values of t_g range from 1 s to 600 s for a given time interval of 3600 s.

Fig. 1 Layout of anemometers (unit: m)

3.2 Gust factor

Gust factor is defined as a ratio of the maximum value of average gust time t_g to mean wind speed U(T) for a basic time interval T, as follows:

                   (2a)

                       (2b)

                       (2c)

where max(u(T, t_g)), max(v(T, t_g)), and max(w(T, t_g)) are the maximum mean wind speed over t_g for longitudinal, lateral, and vertical wind fluctuations, respectively. In this study, the average gust time t_g is 3 s when the basic time interval T is 10 min. When studying time-interval variations, t_g values range from 1 s to 3000 s when the basic time interval T is 3600 s.

3.3 Peak factor

Peak factor is used to describe the instantaneous intensity of fluctuating wind. Based on the calculation method from YU et al [14], it can be expressed as

                 (3)

where σ_u(T, t_g) is the standard deviation of fluctuating wind speed for the longitudinal component; T is the basic time interval; t_g is the average gust time.

4 Results and discussion

4.1 Mean wind speed and wind direction

Wind speeds were recorded from 14:00 on June 25, 2011 to 18:00 on June 26, 2011, totaling a record duration of 28 h. The records were firstly verified by comparing the data collected from different anemometers. The 28 h time records were truncated into samples of a 10 min time interval; sample information for the measured data is listed in Table 1. Figure 2 shows the time histories of 10 min mean wind speed and wind direction. The mean wind speed increases with observation height, whereas mean wind direction at various observation heights follows the identical trend. The maximum mean wind speed occurred at approximately 19:00 on June 25. The maximum mean wind speeds at heights of 10 m and 40 m were recorded to be 11.51 m/s and 15.05 m/s, respectively, and their lateral wind direction corresponds to 17°.

Table 1 Measured data samples from the typhoon

Fig. 2 10 min mean wind speed and wind direction during typhoon Meari:

4.2 Variations of turbulence intensity with mean wind speed, time interval and height

Figure 3 shows the variations of turbulence intensities at various observation heights with mean wind speed. It is apparent that the turbulence intensities decrease with mean wind speed in a linear fashion. The average longitudinal, lateral, and vertical turbulence intensities are 0.20, 0.18, and 0.10 at an elevation of 10 m above the ground and are 0.15, 0.14, and 0.07 at an elevation of 40 m. The longitudinal and lateral turbulence intensities are similar in magnitude; however, they are approximately twice the vertical turbulence intensity.

Table 2 shows the ratios of three turbulence intensity components at different elevations, along with the results in previous studies. It was observed that the ratio of lateral turbulent intensity to longitudinal turbulent intensity from Typhoon Meari is greater than 0.8, which is close to those observed by SCHROEDER [15], CAO et al [16], LI et al [17], and SONG et al [18]. The ratio of vertical component to longitudinal component obtained using the data from Typhoon Meari is between 0.49 and 0.57, which is close to the results in CAO et al [16].

Figure 4 shows a comparison of mean longitudinal turbulent intensities at various time intervals during the passage of Typhoon Meari and the results of DURST [3] and KRAYER et al [19]. It can be seen that the longitudinal turbulent intensity decreases with time interval and the reduction rate is gradually stable. At heights of 10 and 20 m, the curve obtained using the data from typhoon Meari is located between DURST’s and KRAYER-MARSHALL’s curves. Our result at the height of 40 m is smaller than DURST’s curve when t_g was less than 100 s, where it agrees well with DURST’s curve when t_g is more than 100 s.

Fig. 3 Three turbulence intensity components versus mean wind speeds:

Table 2 Ratios of three turbulence intensity components

Fig. 4 Variation of turbulence intensity with average gust time (T=3600 s):

The variation of turbulence intensity, especially longitudinal turbulence intensity, with height is the focus of this research, and empirical formulas for variation of turbulence intensity with height have been provided in several existing structural design standards. Figure 5 shows the variation of turbulence intensity with height and the available empirical curves from various standards and code are also provided for comparison. Results indicate that the longitudinal turbulence intensities at various heights are larger than the curves in European wind load provision; however, the fitted curve for longitudinal turbulence intensity show a good agreement with the American and Japanese wind load provisions. For the purpose of engineering application, the measured turbulence intensity profiles are fitted based on the profile expression form I_i=c(10/z)^d in ASCE/ESI7-10 [20]. The expressions for three turbulence intensity components are summarized in Table 3.

Fig. 5 Turbulence intensity profiles:

Table 3 Fitted turbulence intensity profiles

4.3 Variations of gust factors with mean wind speed, time interval and height

Figure 6 shows the variation in longitudinal, lateral, and vertical gust factors for t_g=3 s with 10 min mean wind speed. It is apparent that the gust factors of the three-dimensional components decrease with wind speed. The rate of change decreases rapidly when the mean wind speed is less than 8 m/s, but more slowly when the mean wind speed is greater than 8 m/s. After fitting using a third-order polynomial, the gust factor shows an increasing tendency when the mean wind speed is greater than a certain value, which agrees with the results of YELLAND and TAYLOR [21, 22]. Table 4 shows the average values of the three-dimensional gust factors for t_g=3 s at various heights. It can be seen that the three- dimensional gust factors decrease with height. The average value of the longitudinal gust factors at the various heights is 1.39, which is smaller than result of GAO et al [16] for typhoon Maemi and larger than result of HU et al [23] below a height of 10 m.

Fig. 6 Variation of gust factors with mean wind speed:

The gust factor was found to vary significantly for different average gust time intervals t_g. In 1960, based on normal strong wind data, the variation curve of longitudinal gust factor with average gust time was determined by DURST [3]. This research result has been used as an American standard. Since then, many related studies based on measured data for different areas around the world have been carried out. However, large variability exists among the results of these studies because of the complex interactions of wind characteristics, surrounding terrain, and observation height. As an illustration of the importance of this research to structural wind engineering, Fig. 7 shows the statistical relationship between the gust factors over various time intervals at heights of 10, 20, and 40 m with a basic time interval of one hour. At the same time, for comparison, the figure shows the empirical curves of DURST [3] and KRAYER-MARSHALL [19]. It is evident that the variations in gust factor at various heights with time interval are similar. The gust factor decreases with time interval, and the rate of change generally decreases with time interval. Under the same time interval, the gust factors decrease with height. At a height of 10 m, the measured gust factors were obviously larger than DURST’s results and slightly smaller than KRAYER- MARSHALL’s results when t_g was less than 100 s, but were larger than DURST’s results and close to KRAYER-MARSHALL’s results when t_g was greater than 100 s. At a height of 20 m, the measured gust factors were smaller than that at a height of 10 m, which was similar to DURST’s results, but generally deviated from KRAYER-MARSHALL’s results. At a height of 40 m, the measured gust factors were less than DURST’s results when t_g was less than 100 s.

Table 4 Average values of gust factors

Studies of the variation of lateral and vertical gust factors with time interval are few, but this research plays an important role in wind-resistant structural design. Figure 8 shows the variations in gust factor for lateral and vertical components for various time intervals. It is apparent that the variations in lateral and vertical gust factors were similar, decreasing with height. Under the same time interval, the lateral value is larger than the vertical value. The measured lateral gust factor at 20 m is close to that at a height of 40 m, but the measured vertical gust factor at 10 m is close to that at a height of 20 m. When the average gust time t_g=1 s, the lateral gust-factor values for observation heights of 10, 20, and 40 m were 0.68, 0.57, and 0.52, and the vertical values were 0.38, 0.36, and 0.27, respectively.

Unlike turbulence intensity, there is no empirical expression for gust-factor profile in the standards of leading countries, and the existing measured results are unsuitable for the situation in Shanghai. Therefore, based on Eq. (2), the variations in gust factor with height for the three-dimensional components were calculated and are shown in Fig. 9. The measured results were fitted using the formula G_i=α(z/10)^β, and the fitting expression is provided in Fig. 10.

Fig. 7 Variation of longitudinal gust factors with average gust time (T =3600 s):

4.4 Relationship between gust factor and turbulence intensity

Based on measured typhoon data combined with a theoretical derivation, an empirical relationship between gust factor and turbulence intensity was obtained by ISHIZAKI [24]. This expression is given:

                         (4)

where T is the basic time interval and t_g is the average gust time; ISHIZAKI proposed a=0.5 and b=1.0. Clearly, the relationship of gust factor and turbulence intensity was considered by ISHIZAKI to be linear. More recently, based on Eq.(4) combined with measured data, the relationship expression was revised by CHOI [25], and values of a=0.62, b=1.27 were recommended. Recently, the near-ground wind characteristics of typhoon Maemi were analyzed by CAO et al [16], and the relationship of gust factor and longitudinal turbulence intensity was fitted on the basis of Eq. (4); the fitted results for a and b were 0.5 and 1.15, respectively.

Fig. 8 Variation of lateral and vertical gust factors with average gust time (T =3600 s):

The relationships between longitudinal gust factor and turbulence intensity at heights of 10, 20, and 40 m were obtained by means of measured data; for comparison, the empirical curves proposed by ISHIZAKI [24] and CHOI [25] are given, as shown in Fig. 10. The results suggested by ISHIZAKI are larger than the measured results, but the results presented by CHOI are close to the measured results. In addition, based on Eq. (4), the best-fit parameters were developed using least-squares fitting of the measured results, and the fitted parameters a and b at different heights are shown in Table 5.

Fig. 9 Variation of longitudinal gust factors with turbulence intensity:

Fig. 10 Gust-factor profiles in longitudinal, lateral, and vertical directions

4.5 Variations of peak factor with mean wind speed and time interval

Figure 11 shows the variation of peak factor with 10 min wind speed for t_g=3 s at different heights. It is clear that the peak factor decreased with mean wind speed during the passage of Typhoon Meari and that this change tendency was more and more obvious with increasing observation height. The average values of peak factor over various 10 min samples at heights of 10, 20, and 40 m were 2.43, 2.48, and 2.47, respectively.

Table 5 Fitted values of a and b

Fig. 11 Variation of peak factor (T=3 s) with 10 min mean wind speed

Figure 12 shows the variation of average peak- factor values with various average gust time. It was found that the relationship between peak factor and average gust time shows little dependence on the observation height. Overall, the measured results were close to DURST’s results. The measured results at 40 m were smaller than DURST’s results when t_g was less than 10 s, but larger than DURST’s results when t_g exceeded 10 s.

Fig. 12 Variation of peak factor with average gust time (T=3600 s)

5 Conclusions

In the present study, the near-ground wind characteristics of the 2011 Typhoon Meari, including wind speed, wind direction, turbulence intensity, gust factor, and peak factor, was identified using 10-min wind data at elevations of 10, 20, 30 and 40 m in a coastal area of eastern China. The following important conclusions were made:

1) The turbulence intensity components in the longitudinal, lateral, and vertical directions decrease with observation height, and the relationship between the turbulence intensity and the height is basically linear. The longitudinal turbulence intensity components decrease with increasing average gust time.

2) The gust factors in three directions decrease with mean wind speed and exhibit a rapid falloff with increasing wind speed when wind speed is less than 8 m/s. In addition, the three-dimensional gust factors decrease with observation height.

3) The relationship between the longitudinal gust factor and turbulence intensity obtained using the measurements was studied and compared with the results in previous studies. Results show that CHOI’s equation fits the current data better than ISHIZAKI’s equation. In addition, the relationships between the gust factor and the lateral and vertical turbulence intensity components were analyzed.

4) The peak factors at different elevations show consistent trend and slightly decrease with mean wind speeds. Averaged peak factors in three directions using the data from Typhoon Meari are 2.43, 2.48, and 2.47, respectively. It was observed that the relationship between peak factor and average gust time shows little dependence on the observation height. In addition, the peak factor-average gust time curves in the present study are in a good agreement with the DURST curve.

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(Edited by YANG Hua)

Cite this article as: WANG Xu, HUANG Peng, YU Xian-feng, HUANG Chao. Near ground wind characteristics during typhoon Meari: Turbulence intensities, gust factors, and peak factors [J]. Journal of Central South University, 2017, 24(10): 2421–2430. DOI:https://doi.org/10.1007/s11771-017-3653-z.

Foundation item: Projects(51378396, 51678452, 51708074, 2014M560706) supported by General Program of National Natural Science Foundation of China; Project(2014M560706) supported by the China Postdoctoral Science Foundation

Received date: 2015-11-26; Accepted date: 2016-03-17

Corresponding author: HUANG Peng, Professor, PhD; Tel: +86–21–65982881; E-mail: huangtju@tongji.edu.cn