Long-term monitoring of wind characteristics at Sutong Bridge site

Wang, Hao; Li, Aiqun; Niu, Jie; Zong, Zhouhong; Li, Jian

doi:10.1016/j.jweia.2013.01.006

Cited by 99 publications

(44 citation statements)

References 28 publications

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“…From the stochastic point of view, wind direction is also a random variable, characterized by its inherent variability and its association structure with wind speed. Moreover, the modelling of wind direction seems to play an increasingly important role in a vast variety of applications such as the fast developing technology of floating wind turbines (Soukissian, 2014) and the micro-siting of offshore wind farms (Song et al, 2016), the design/static stability of bridge structures (Wang et al, 2013), beach morphological dynamics and sediment transport (Sedrati and Anthony, 2007;Walker et al, 2009), etc. For wind climate analysis and identification of wind variability, long-term wind data are required. For local assessment purposes, usually, wind measurements at offshore locations are performed by installing a meteorological mast or a lidar on an existing offshore structure or an on-site buoy.…”

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confidence: 99%

Offshore wind climate analysis and variability in the Mediterranean Sea

Soukissian

Karathanasi

Axaopoulos³

et al. 2017

Intl Journal of Climatology

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ABSTRACT:The long-term offshore wind characteristics in the Mediterranean Sea are assessed using the ERA-Interim dataset for the period 1979-2014. Three main aspects of the wind climate analysis are examined in detail; the spatio-temporal behaviour (including variability characteristics) of wind speed and direction for the annual and monthly time scale; the joint association of wind speed and direction for the annual and monthly time scale, and; the wind speed trends and wind direction changes. From this analysis, the systematic wind flow patterns are identified and the general features of the wind climatology patterns are revealed. The most typical examples of stable and intense regional winds are the Mistral (throughout the year) in the Gulf of Lion and the Etesians (during summer) in the Aegean Sea. High values of mean annual variability of wind speed occur over the western part of the basin (Balearic, Tyrrhenian and Ligurian sub-basins) as well as over the Adriatic and N Aegean Seas, and the E Levantine Basin. Moreover, the assessment of the joint association of wind speed and direction indicates that areas with high values of linear-circular correlation are the ones characterized by intense wind climate. As regards, long-term changes of wind speed and direction, the linear trend for the former and the angular distance for the latter variable are provided. The fastest increasing wind speed trends are observed in the Ionian, the N Tyrrhenian and N Adriatic Seas, the eastern part of the Algerian Basin up to Balearic Isl. and the western part of the S Levantine Basin while the fastest decreasing ones are observed offshore Monaco, the central Aegean and the E Alboran Seas and the N Levantine Basin. The highest values of angular variance and mean angular distances are depicted for the Ligurian, Balearic and Alboran Seas.

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confidence: 99%

Offshore wind climate analysis and variability in the Mediterranean Sea

Soukissian

Karathanasi

Axaopoulos³

et al. 2017

Intl Journal of Climatology

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“…In typhoon prone regions, the optimal prediction of typhoon design wind speed is using extreme wind speed analysis on the basis of annual maximum typhoon wind speeds derived from wind measurement data. However, normally, only a few decades wind measurement data can be used and this is not enough for a reliable prediction of typhoon design wind speed . Therefore, typhoon simulation method that integrates typhoon wind field model, probability distributions of typhoon key parameters, and Monte Carlo simulation method was developed for the prediction of typhoon design wind speed and was widely used in engineering applications .…”

Section: Introductionmentioning

confidence: 99%

Prediction of typhoon design wind speed with cholesky decomposition method

Huang

Sun

2018

Structural Design Tall Build

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Typhoon simulation method that integrates typhoon wind field model, probability distributions of typhoon key parameters, and Monte Carlo simulation method has long been used to predict typhoon design wind speeds of structures. In the research, the empirical typhoon wind field model with a novel parameter B model of Holland's radial pressure profile is first introduced and validated with typhoon Hagupit's simulation. The results show that relatively good typhoons can be simulated with this empirical typhoon wind field model. Then, the cholesky decomposition method used in typhoon simulation method is proposed that allows achieving all correlated typhoon key parameters simultaneously. Finally, the cholesky decomposition method is used to generating typhoon key parameters in Hong Kong, and typhoon design wind speeds for different return periods are predicted with typhoon simulation method. In addition, typhoon design wind speeds derived from historical typhoon key parameters and typhoon key parameters generated without considering cholesky decomposition method are also predicted, respectively. The predicted typhoon design wind speeds are compared and the results demonstrate that the cholesky decomposition method should be incorporated into typhoon simulation method. KEYWORDS cholesky decomposition method, design wind speed, Monte Carlo simulation, typhoon simulation method, typhoon key parameters, typhoon wind field modelIn typhoon prone regions, the optimal prediction of typhoon design wind speed is using extreme wind speed analysis on the basis of annual maximum typhoon wind speeds derived from wind measurement data. However, normally, only a few decades wind measurement data can be used and this is not enough for a reliable prediction of typhoon design wind speed. [1][2][3] Therefore, typhoon simulation method that integrates typhoon wind field model, probability distributions of typhoon key parameters, and Monte Carlo simulation method was developed for the prediction of typhoon design wind speed and was widely used in engineering applications. [4][5][6][7][8] Within this method, probability distributions of typhoon key parameters, including central pressure difference Δp 0 , radius to maximum wind r m , translation velocity c, approach angle θ, and minimum of closest distance d min , are first determined by using historical typhoon wind data obtained from Observatory. Typhoon wind field model with/without filling wind field model after landfall in conjunction with Monte Carlo simulation method is then used to generate a series of typhoons. Typhoon design wind speeds for different return periods in the concerned region are finally determined with extreme wind speed analysis.Typhoon wind field models proposed by Vickery and Twisdale [9] and Meng et al. [10] were widely used in typhoon simulation method. They developed the typhoon wind field model from the momentum equation of three-dimensional Navier-Stokes equations, but then Vickery and the optimum fit method [10] or the empirical statistical model [14] was app...

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“…In recent years, the SHM-based researches on wind resistance of bridges have attracted an increasing amount of attention. Case studies include the Tsing Ma Suspension Bridge [2], Runyang Suspension Bridge [3], Sutong Bridge [4], Dongting Lake Bridge [5], Xihoumen Suspension Bridge [6][7], Hangzhou Jiubao Bridge [8], Humber Bridge [9], Akashi Kaikyo Bridge [10], Hakucho Bridge [11], Fred Hartman Bridge [12], and so on.…”

Section: Introductionmentioning

confidence: 99%

A Full-Scale Measurement of Wind Actions and Effects on a Sea-Crossing Bridge

Zhou¹,

Sun²,

Xie³

2017

CEJ

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Wind loading is critical for the large-span and light-weight structures, and field measurement is the most effective way to evaluate the wind resistance performance of a specific structure. This study investigates the wind characteristics and wind-induced vibration on a seacrossing bridge in China, namely Donghai Bridge, based on up to six years of monitoring data. It is found that: (1) there exists obvious discrepancy between the measured wind field parameters and the values suggested by the design code; and the wind records at the bridge site is easily interfered by the bridge structure itself, which should be considered in interpreting the measurements and designing structural health monitoring systems (SHMS); (2) for strong winds with high non-stationarity, a shorter averaging time than 10-min is preferable to obtain more stable turbulent wind characteristics; (3) the root mean square (RMS) of the wind-induced acceleration of the girder may increase in an approximately quadratic curve relationship with the mean wind speed; and (4) compared to traffic load, the wind dominates the girder's lateral vibration amplitude, while the heavy-load traffic might exert more influence on the girder's vertical and torsional vibrations than the high winds. This study provides field evidence for the wind-resistant design and evaluation of bridges in similar operational conditions.

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Long-term monitoring of wind characteristics at Sutong Bridge site

Cited by 99 publications

References 28 publications

Offshore wind climate analysis and variability in the Mediterranean Sea

Offshore wind climate analysis and variability in the Mediterranean Sea

Prediction of typhoon design wind speed with cholesky decomposition method

A Full-Scale Measurement of Wind Actions and Effects on a Sea-Crossing Bridge

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