International Journal of Science , Engineering and Management (IJSEM)

Monthly Journal for Science , Engineering and Management

Volume3,February 2018,

Topic : A Comparative Study on Design Wind Speed Using Extreme Value Type-1 Distribution and IS875 Approach

Authors:N. Vivekanandan ||

Abstract:Assessment of wind speed in a region is a pre-requisite while designing tall structures viz. cooling towers, stacks, transmission line towers, etc. This can expediently be carried out by Extreme Value Analysis (EVA) of hourly wind speed (HWS) data using probability distribution, or by using standard procedures available under Bureau of Indian Standards code of practices (IS 875) for building and structures. This paper details a study on EVA of HWS data recorded at India Meteorological Department observatories of Delhi and Visakhapatnam adopting five parameter estimation methods of Extreme Value Type-1 (EV1) distribution. The adequacy of fitting of EV1 distribution was quantitatively assessed by Goodness-of-Fit (GoF) tests such as Anderson-Darling and Kolmogorov-Smirnov, and diagnostic test using root mean squared error. The GoF and diagnostic tests results present the order statistics approach (OSA) is better suited amongst five methods adopted for estimation of wind speed for Delhi and Visakhapatnam. The results of 3-second average wind speed obtained from EVA of hourly rainfall adopting EV1 (using OSA) distribution are compared with IS 875 approach for arriving at a design wind speed. Based on the results obtained from EV1 distribution and IS 875 approach, the recommendations are made and presented in the paper. .

Keywords: Anderson-Darling, Extreme Value Type-1 distribution, Kolmogorov-Smirnov, Order Statistics Approach, Wind speed.

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DOI: 01.1617/vol5/iss2/pid85931

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Editor Image

Dr.Muhammad Ishtiaq,
Mirpur University of
Science & Technology,
Mirpur, Azad Kasmir.

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ISSN(Online): 2456-1304

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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Journal Code : IJSEM
Electronic ISSN : 2456-1304
Impact Factor : 2.7
Frequency : Monthly
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