English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Estimation of extreme wind speed potential at a region is of importance while designing tall structures such as cooling towers, stacks, transmission line towers, etc. Assessment of wind speed can expediently be carried out by probabilistic modelling of historic wind speed data using extreme value distribution, or by using standard procedures available under BIS code of practices for building and structures. This paper illustrates the use of extreme value distributions such as Gumbel, Frechet and Weibull for modelling wind speed data recorded at Kanyakumari. Method of Least Squares (MLS), maximum likelihood method and order statistics approach are used for determination of parameters of the distributions. Kolmogorov-Smirnov test is used for checking the adequacy of fitting the method/ distribution to the recorded data. D-index is used for selection of suitable method/ distribution for estimation of design wind speed. The study shows that the Gumbel distribution using MLS is better suited for estimation of design wind speed for Kanyakumari. A comparative study of wind speed estimates obtained using MLS of Gumbel and with BIS code of practices is carried out; and results presented

Comparison of Estimators of Extreme Value Distributions for Wind Data Analysis