• Wind and Structures
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• v.37 no.2
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• pp.153-161
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• 2023

Wind speed data from Nepal and adjoining countries have been analyzed to estimate an extreme wind speed climatology for the region. Previously wind speed information for Nepal was adopted from the Indian National Standard and applied to two orographically different regions: above and below 3000 m elevation respectively. Comparisons of the results of this analysis are made with relevant codes and standards. The study confirms that the assigned basic wind speed of 47 m/s for the plains and hills of Nepal (below 3000 m) is appropriate, however, data to substantiate a basic wind speed of 55 m/s above 3000 m is unavailable. Using a composite analysis of 15 geographically similar stations, the study also generated 435 years of annual maxima wind data and fitted them to Type I and Type III extreme value distributions. The results suggest that Type III distribution may better represent the data. The findings are also consistent with predictions made by Holmes and Weller (2002) and to a certain extent those of Sarkar et al. (2014), but lower than the analysis undertaken by Lakshmanan et al. (2009) for northern India. The study also highlights that the use of a load factor of 1.5 on wind load implies lower strength design MRI's of around 260 years compared to the 700 years of ASCE 7-22.

• Wind and Structures
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• v.34 no.6
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• pp.469-482
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• 2022

The generalized extreme value distribution (GEVD) is frequently used to fit the block maximum of environmental parameters such as the annual maximum wind speed. There are several methods for estimating the parameters of the GEV distribution, including the least-squares method (LSM). However, the application of the LSM with the expected order statistics has not been reported. This study fills this gap by proposing a fitting method based on the expected order statistics. The study also proposes a plotting position to approximate the expected order statistics; the proposed plotting position depends on the distribution shape parameter. The use of this approximation for distribution fitting is carried out. Simulation analysis results indicate that the developed fitting procedure based on the expected order statistics or its approximation for GEVD is effective for estimating the distribution parameters and quantiles. The values of the probability plotting correlation coefficient that may be used to test the distributional hypothesis are calculated and presented. The developed fitting method is applied to extreme thunderstorm and non-thunderstorm winds for several major cities in Canada. Also, the implication of using the GEVD and Gumbel distribution to model the extreme wind speed on the structural reliability is presented and elaborated.

• Wind and Structures
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• v.15 no.2
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• pp.177-188
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• 2012

The meteorological events that cause most strong winds in Brazil are extra-tropical cyclones, downbursts and tornadoes. However, one hurricane formed off the coastline of southern Brazil in 2005, a tropical storm formed in 2010 and there are predictions that others may form again. Events such as those described in the paper and which have occurred before 1987, generate data for the wind map presented in the Brazilian wind loading code NBR-6123. This wind map presents the reference wind speeds based on 3-second gust wind speed at 10 m height in open terrain, with 50-year return period, varying from 30 m/s (north half of country) to 50 m/s (extreme south). There is not a separation of the type of climatological event which generated each registered velocity. Therefore, a thunderstorm (TS), an extra-tropical pressure system (EPS) or even a tropical cyclone (TC) are treated the same and its resulting velocities absorbed without differentiation. Since the flow fields generated by each type of meteorological event may be distinct, the indiscriminate combination of the highest wind velocities with aerodynamic coefficients from boundary layer wind tunnels may lead to erroneous loading in buildings.

• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.45-50
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• 1996

This paper mainly describes the wind load assumption of 765kV transmission towers. We analyzed wind velocity data a meteorological observatories to get the wind velocity of 50 years return period by using Gumbel I type extreme value distribution. By multi-correlative regression analysis method, wind velocity at no observation site was obtained. Reference dynamics wind pressure map was obtained from above analysis and the wind pressure was classified as three regio in high temperature season.

• Wind and Structures
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• v.19 no.5
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• pp.467-480
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• 2014

The estimation of wind speed values used in codes and standards is an integral part of the wind load evaluation process. In a number of codes and standards, wind speeds outside of tropical cyclone prone regions are estimated using a single probability distribution developed from observed wind speed data, with no distinction made between the types of causal wind hazard (e.g., thunderstorm). Non-tropical cyclone wind hazards (i.e., thunderstorm, non-thunderstorm) have been shown to possess different probability distributions and estimation of non-tropical cyclone wind speeds based on a single probability distribution has been shown to underestimate wind speeds. Current treatment of non-tropical cyclone wind hazards in worldwide codes and standards is touched upon in this work. Meteorological data is available at a considerable number of United States (U.S.) stations that have information on wind speed as well as the type of causal wind hazard. In this paper, probability distributions are fit to distinct storm types (i.e., thunderstorm and non-thunderstorm) and the results of these distributions are compared to fitting a single probability distribution to all data regardless of storm type (i.e., co-mingled). Distributions fitted to data separated by storm type and co-mingled data will also be compared to a derived (i.e., "mixed") probability distribution considering multiple storm types independently. This paper will analyze two extreme value distributions (e.g., Gumbel, generalized Pareto). It is shown that mixed probability distribution, on average, is a more conservative measure for extreme wind speed estimation. Using a mixed distribution is especially conservative in situations where a given wind speed value for either storm type has a similar probability of occurrence, and/or when a less frequent storm type produces the highest overall wind speeds. U.S. areas prone to multiple non-tropical cyclone wind hazards are identified.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.26 no.1
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• pp.16-24
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• 2014

Long-term measured wind data are absolutely necessary to estimate extreme offshore wind speed. However, it is almost impossible to collect offshore wind measured data. Therefore, typhoon simulation is widely used to analyze offshore wind conditions. In this paper, 74 typhoons which affected the western sea of Korea during 1978-2012(35 years) were simulated using Holland(1980) model. The results showed that 49.02 m/s maximum wind speed affected by BOLAVEN(1215) at 100 m heights of HeMOSU-1 (Herald of Meteorological and Oceanographic Special Unit - 1) was the biggest wind speed for 35 years. Meanwhile, estimated wind speeds were compared with observed data for MUIFA, BOLAVEN, SANBA at HeMOSU-1. And to estimate extreme wind speed having return periods, extreme analysis was conducted by assuming 35 annual maximum wind speed at four site(HeMOSU-1, Gunsan, Mokpo and Jeju) in western sea of the Korean Peninsular to be Gumbel distribution. As a results, extreme wind speed having 50-year return period was 50 m/s, that of 100-year was 54.92 m/s at 100 m heights, respectively. The maximum wind speed by BOLAVEN could be considered as a extreme winds having 50-year return period.

• Wind and Structures
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• v.13 no.1
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• pp.83-94
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• 2010

Wind tunnel measurements on T-shaped free-standing walls and inclined free-standing walls have been carried out. Mean net pressure coefficients have been derived and compared with previous research. It was observed that the high loads at the free ends are differently distributed than those derived from the pressure coefficients for free-standing walls in EN 1991-1-4. In addition net pressure coefficients based on extreme value analysis have been obtained. The lack of correlation of the wind induced pressures at windward and leeward side result in lower values for the net pressure coefficients when based on extreme value analysis. The results of this wind tunnel study have been included in Dutch guidelines for noise barriers.

• Wind and Structures
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• v.9 no.3
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• pp.179-191
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• 2006

Parent wind data are often acknowledged to fit a Weibull probability distribution, implying that wind epoch maxima should fall into the domain of attraction of the Gumbel (Type I) extreme value distribution. However, observations of wind epoch maxima are not fitted well by this distribution and a Generalised Extreme Value (GEV) analysis leading to a Type III fit empirically appears to be better. Thus there is an apparent paradox. The reasons why advocates of the GEV approach seem to prefer it are briefly summarised. This paper gives a detailed analysis of the errors involved when the GEV is fitted to epoch maxima of Weibull origin. It is shown that the results in terms of the shape parameter are an artefact of these errors. The errors are unavoidable with the present sample sizes. If proper significance tests are applied, then the null hypothesis of a Type I fit, as predicted by theory, will almost always be retained. The GEV leads to an unacceptable ambiguity in defining design loads. For these reasons, it is concluded that the GEV approach does not seem to be a sensible option.

• Proceedings of the KSRS Conference
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• v.1
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• pp.390-393
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• 2006

It is well known that synthetic aperture radar (SAR) provides information on ocean winds and surface waves. SAR data are of particularly high value in extreme weather conditions, as radar is able to penetrate the clouds providing information on different ocean surface processes. In this presentation some recent results on SAR observation of extreme wind and ocean wave conditions is summarised. Particular emphasize is put on the investigation of typhoons and extratropical cyclones in the North Pacific. The study is based on the use of ENVISAT ASAR wide swath images. Wide swath and scansar data are well suited for a detailed investigation of cyclones. Several examples like, e.g., typhoon Talim will be presented, demonstrating that these data provide valuable information on the two dimensional structure of the both the wind and the ocean wave field. Comparisons of the SAR observation with parametric and numerical model data will be discussed. Some limitations of standard imaging models like, e.g., CMOD5 for the use in extreme wind conditions are explained and modifications are proposed. Finally the study summarizes the capabilities of new high resolution TerraSAR-X mission to be launched in October 2006 with respect to the monitoring of extreme weather conditions. The mission will provide a spatialresolution up to 1m and has full polarimetric capabilities.

• Wind and Structures
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• v.17 no.2
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• pp.227-244
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• 2013

Non-stationary extreme winds such as thunderstorm downbursts are responsible for many structural damages. This research presents a time domain approach for estimating along-wind load effects on tall buildings using multiple wind speed time history samples, which are simulated from evolutionary power spectra density (EPSD) functions of non-stationary wind fluctuations using the method developed by the authors' earlier research. The influence of transient wind loads on various responses including time-varying mean, root-mean-square value and peak factor is also studied. Furthermore, a simplified model is proposed to describe the non-stationary wind fluctuation as a uniformly modulated process with a modulation function following the time-varying mean. Finally, the probabilistic extreme response and peak factor are quantified based on the up-crossing theory of non-stationary process. As compared to the time domain response analysis using limited samples of wind record, usually one sample, the analysis using multiple samples presented in this study will provide more statistical information of responses. The time domain simulation also facilitates consideration of nonlinearities of structural and wind load characteristics over previous frequency domain analysis.