Wind Effects on Structures: An Introduction to Wind Engineering and Wind Forces in Engineering (2nd Edition)

Simiu, Emil; Scanlan, Robert H.; Sachs, Peter L.; Griffin, O. M.

doi:10.1115/1.3240751

Cited by 102 publications

(130 citation statements)

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“…It would appear sensible to test for non-zero k using, for example, the methods reviewed by Hosking (1984). It is important to recall, as shown by Figure 2, that the Type III distribution will normally give lower extreme gust or wind speeds for a given return period than the Type I form (Simiu & Scanlan, 1986;Walshaw, 1994). To quote Walshaw (1994), it then 'becomes essential to make adequate allowance for the margins of error associated with return level estimation'.…”

Section: Distribution Typementioning

confidence: 99%

“…He terms the result the basic wind speed. Grigoriu (1984) and Simiu & Scanlan (1986) enlarged their available data set of extremes for classical analysis based on the Gumbel distribution by selecting the largest value in each month, i.e., using the month as the epoch rather than the year. (Note that this is not the same procedure used to control for seasonality, since the monthly extremes are combined in a single analysis.)…”

Section: Techniques To Lengthen the Available Datasetmentioning

confidence: 99%

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A review of methods to calculate extreme wind speeds

Palutikof

Brabson

Lister

et al. 1999

Meteorological Applications

326

209

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High wind speeds pose a threat to the integrity of structures, particularly those at exposed sites such as bridges, wind turbines and radio masts. In any design project for large structures, safety considerations must be balanced against the additional cost of 'over-design'. Accurate estimation of the occurrence of extreme wind speeds is an important factor in achieving the correct balance. Such estimates are commonly expressed in terms of the quantile value X T , i.e., the maximum wind speed which is exceeded, on average, once every T years, the return period. Typically, for most users of wind data, estimates of the 50-year return period gust or wind speed are required, based on 10-20 (and often fewer) available years of observations. For this situation, the data are generally fitted to a theoretical distribution in order to calculate the quantiles. Fisher & Tippett (1928) showed that if a sample of n cases is chosen from a parent distribution, and the maximum (or minimum) of each sample is selected, then the distribution of the maxima (or minima) approaches one of three limiting forms as the size of the samples increases. Gumbel (1958) argued that, in the case of floods, each year of record constitutes a sample with 365 cases and that the annual extreme flood is the maximum value of the sample. Thus, the Fisher-Tippett distributions could be fitted to the set of annual maxima. This is the basis of all classical extreme value theory. The aim is to define the form of the limiting distribution and estimate the parameters, so that values of X T can be calculated.Here, we review and summarize the portion of the extensive literature on extreme value theory relevant to the analysis of wind and gust speed data. The review is carried out with reference to the requirements of a user seeking to select and apply a method appropriate to a particular real data set. We discuss first the available techniques and then the choices required for successful selection and implementation. The methods are organized broadly according to the length of the time series of observations available for analysis, beginning with those which require longer data sets, and moving towards those developed for use with short-duration series. The length of the observational data set is often a problem for those wishing to calculate extreme wind speed quantiles but is a common concern for users of geophysical data, and a substantial literature exists on estimation of extremes from short time series.Note that we do not consider here the matter of anemometer exposure. As with all analyses of wind data, the results of an extreme value analysis will be flawed if the data on which they are based are taken from an anemometer with a non-standard exposure (e.g., sheltered in one or more directions, or at a height above the ground different from the 10 m standard).Meteorol. Appl. 6, 119-132 (1999) A review of methods to calculate extreme wind speeds

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Section: Distribution Typementioning

confidence: 99%

Section: Techniques To Lengthen the Available Datasetmentioning

confidence: 99%

A review of methods to calculate extreme wind speeds

Palutikof

Brabson

Lister

et al. 1999

Meteorological Applications

326

209

View full text Add to dashboard Cite

show abstract

“…Information on transformation procedures to determine terrain-related contributions can be found in e.g. Simiu and Scanlan (1986) and Verkaik (2006). The design-related contribution (i.e.…”

Section: Context Of Virtual Special Issuementioning

confidence: 99%

CFD simulation of pedestrian-level wind conditions around buildings: Past achievements and prospects

Blocken

Stathopoulos

2013

Journal of Wind Engineering and Industrial Aerodynamics

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Context of Virtual Special IssueA Virtual Special Issue (VSI) is a Special Issue that consists of previously published papers in a given journal. The aim of a VSI is to identify and group a coherent set of such papers and to provide some post-publication perspectives. This VSI deals with papers on CFD simulation of pedestrian-level wind conditions around buildings, published in the Journal of Wind Engineering and Industrial Aerodynamics (JWEIA).Wind comfort and wind safety for pedestrians are important requirements for urban areas. In particular near high-rise buildings, high wind velocities are often introduced at pedestrian level that can be experienced as uncomfortable or even dangerous. Uncomfortable wind conditions have proven detrimental to the success of new buildings (Durgin and Chock 1982). Wise (1970) reports about shops that are left untenanted because of the windy environment that discouraged shoppers. Lawson and Penwarden (1975) report dangerous wind conditions to be responsible for the death of two old ladies after being blown over by sudden wind gusts near a high-rise building. Many urban authorities nowadays recognize the importance of pedestrian wind comfort and wind safety and require such studies before granting building permits for new buildings or new urban areas.Studies of wind comfort and wind safety involve combining statistical meteorological data with aerodynamic information and with wind comfort and wind safety criteria. The aerodynamic information is needed to transform the statistical meteorological data from the weather station (meteorological site) to the location of interest at the building site. At this location, the transformed statistical data are combined with the comfort and safety criteria to assess local wind comfort and safety. This procedure is schematically depicted in Figure 1. Wind statistics at the meteorological site can be expressed as potential wind speed (U pot ), i.e. corresponding to a terrain with aerodynamic roughness length z 0 = 0.03 m. The aerodynamic information usually consists of two parts: the terrain-related contribution and the design-related contribution. The terrain-related contribution represents the change in wind statistics from the meteorological site to a reference location near the building site, i.e. the transformation of U pot to U 0 . The design-related contribution represents the change in wind statistics due to the local urban design, i.e. the transformation of U 0 to the local wind speed U. Information on transformation procedures to determine terrain-related contributions can be found in e.g. Simiu and Scanlan (1986) and Verkaik (2006). The design-related contribution (i.e. the wind-flow conditions around the buildings at the building site) can be obtained by either wind-tunnel modelling or CFD. Wind comfort and safety criteria generally exist of a threshold value of the wind speed and an allowed exceedance probability of this threshold.

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“…Special attention should be given to poorly streamlined shapes (Geurts, van Bentum 2010). Wind flow, vortices around such buildings and distribution of pressure on their surfaces hard to predict (Holmes 2007;Simiu, Scanlan 1986, 1996. In such cases, during the design stage of a building, the most reliable results are obtained through experiments.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Testing Results of Three Poorly Streamlined Entertainment Venues / Trijų Sudėtingo Pavidalo Pramoginių Statinių Maketų Bandymų Rezultatų Gretinimas

Pavlovsky

Lebedich²,

Samofalov

et al. 2012

Journal of Civil Engineering and Management

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Abstract. The article discusses experimental investigations of wind effects and use of design codes for solving aerodynamic problems. It provides data regarding wind-tunnel tests conducted on three buildings with poorly streamlined shapes, including: methodology and test conditions, aerodynamic properties of the designed structures, features of physical models and research results. All three civil buildings are multi-purpose stadiums of the European level. Despite the identical functional purpose, each building has a unique shape and volume. The paper analyses and compares testing conditions in the wind tunnel and some selective results. The authors propose a criterion for estimating aerodynamic properties of the overhanging roof over spectator stands. The article also considers dependencies of model surface pressures on airflow directions under various test conditions.

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Wind Effects on Structures: An Introduction to Wind Engineering and Wind Forces in Engineering (2nd Edition)

Cited by 102 publications

References 0 publications

A review of methods to calculate extreme wind speeds

A review of methods to calculate extreme wind speeds

CFD simulation of pedestrian-level wind conditions around buildings: Past achievements and prospects

Comparison of Testing Results of Three Poorly Streamlined Entertainment Venues / Trijų Sudėtingo Pavidalo Pramoginių Statinių Maketų Bandymų Rezultatų Gretinimas

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