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Weibull and Generalized Extreme Value Distributions for Wind Speed Data Analysis of Some Locations in India

Sarkar, Arnab and Deep, Sneh and Datta, D and Vijaywargiya, Amit and Roy, R and Phanikanth, V S (2019) Weibull and Generalized Extreme Value Distributions for Wind Speed Data Analysis of Some Locations in India. In: KSCE JOURNAL OF CIVIL ENGINEERING, 23 (8). pp. 3476-3492.

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Official URL: https://dx.doi.org/10.1007/s12205-019-1538-4

Abstract

Wind velocity data modeling plays a crucial role for the estimation of wind load and wind energy. Apart from these, the same modeling must also be used in the load cycle analysis of fatigue failure in slender structures to address periodic vortex shedding. Most authors fitted the entire available range of wind velocities of various locations using Weibull models. However, they did not check the validity of the model in describing the range of extreme wind velocity. In this work, the validity of Weibull models for describing parent as well as extreme hourly mean wind velocity data for four places on the east coast of India has been checked. While it predicts lower wind speeds accurately, the Weibull model has been found to become inappropriate for describing wind velocity in the range of extremes, i.e., above a certain threshold value. Therefore, this article focuses on the techniques of determining a limiting wind velocity beyond which the Weibull distribution is rendered unsuitable. In the range where the Weibull distribution fails, various extreme value distributions, such as Gumbel, Frechet and reverse Weibull distributions have been compared, thereby determining the best estimator for each location.

Item Type: Journal Article
Additional Information: copyright for this article belongs to KOREAN SOCIETY OF CIVIL ENGINEERS-KSCE
Keywords: weibull distribution; wind velocities; non-exceedance probability; gumbel distribution; chauvenet's criterion; probability factor
Department/Centre: Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Depositing User: Id for Latest eprints
Date Deposited: 08 Aug 2019 09:31
Last Modified: 08 Aug 2019 09:31
URI: http://eprints.iisc.ac.in/id/eprint/63357

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