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Probability distributions of extreme pressure coefficients

Holmes, J.D. / Cochran, L.S.

AbstractSeveral thousand extreme pressure coefficients from repeated time-history samples, from a wall tap and a roof tap on a model of the Texas Tech University Building in a simulated atmospheric boundary layer, were used to better determine the appropriate probability distributions for the data. Both the Type I (Gumbel) Extreme Value Distribution, and the Generalized Extreme Value (GEV) distribution, with variable shape factor, k, were used to fit the data; in the latter case the method of probability weighted moments was used. The GEV with small positive shape factor was found to fit the data well. The distributions obtained indicated upper limits of peak pressures about 35% higher than the highest values actually measured.

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Probability distributions of extreme pressure coefficients

Holmes, J.D. / Cochran, L.S.

AbstractSeveral thousand extreme pressure coefficients from repeated time-history samples, from a wall tap and a roof tap on a model of the Texas Tech University Building in a simulated atmospheric boundary layer, were used to better determine the appropriate probability distributions for the data. Both the Type I (Gumbel) Extreme Value Distribution, and the Generalized Extreme Value (GEV) distribution, with variable shape factor, k, were used to fit the data; in the latter case the method of probability weighted moments was used. The GEV with small positive shape factor was found to fit the data well. The distributions obtained indicated upper limits of peak pressures about 35% higher than the highest values actually measured.

Probability distributions of extreme pressure coefficients

Holmes, J.D. / Cochran, L.S.

AbstractSeveral thousand extreme pressure coefficients from repeated time-history samples, from a wall tap and a roof tap on a model of the Texas Tech University Building in a simulated atmospheric boundary layer, were used to better determine the appropriate probability distributions for the data. Both the Type I (Gumbel) Extreme Value Distribution, and the Generalized Extreme Value (GEV) distribution, with variable shape factor, k, were used to fit the data; in the latter case the method of probability weighted moments was used. The GEV with small positive shape factor was found to fit the data well. The distributions obtained indicated upper limits of peak pressures about 35% higher than the highest values actually measured.

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Title:

Probability distributions of extreme pressure coefficients

Contributors:

Holmes, J.D. (author) / Cochran, L.S. (author)

Published in:

Journal of Wind Engineering and Industrial Aerodynamics ; 91 ; 893-901

Publication date:

2003-02-21

Size:

9 pages

ISSN:

DOI:

https://doi.org/10.1016/S0167-6105(03)00019-9

Type of media:

Article (Journal)

Type of material:

Electronic Resource

Language:

English

Keywords:

Extreme values , Probability , Wind pressures

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