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Probabilistic modeling of 10-min mean wind speed and its application in analytical simulation of snowdrift on building roofs.

Authors :
Li, Yuanyuan
Mo, Huamei
Zhang, Guolong
Zhang, Qingwen
Fan, Feng
Source :
Journal of Wind Engineering & Industrial Aerodynamics. Jan2024, Vol. 244, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

The typical resolution for long-term wind speed records that are publicly available in China is daily, this is too coarse for a sound analytical simulation of snowdrift on building roofs. Take Harbin, China as an example, an algorithm was proposed in this study to address this issue, where the commonly-used 2-parameter Weibull distribution was applied to fit the distribution of 10-min mean wind speed. A parameter estimation method, which combines the method of moment and cumulative probability, was proposed to estimate the parameters of Weibull distribution using very limited information on wind speed. The fitted probability model was validated using high-resolution wind speed data by comparing the snowdrift estimated by the modeled wind speed and that estimated by the actual wind speed. Finally, an analytical simulation of snowdrift on a flat roof was carried out to illustrate the application of the proposed model, and the probabilistic characteristic of the derived ground-to-roof conversion factors for snow loads were analyzed. It is indicated that the proposed model is easy to implement and provides a good estimation of the snowdrift on building roofs, and the derived conversion factors could be satisfactorily modeled using a Generalized Extreme Value (GEV) distribution or a normal distribution. • An algorithm was proposed to incorporate very limited wind information into the analytical simulation of roof snow load. • The proposed algorithm is the first of its kind. • An analytical simulation of snowdrifts on a flat roof was carried out using the proposed algorithm. • Probabilistic characteristics of the derived ground-to-roof conversion factors were analyzed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01676105
Volume :
244
Database :
Academic Search Index
Journal :
Journal of Wind Engineering & Industrial Aerodynamics
Publication Type :
Academic Journal
Accession number :
174688060
Full Text :
https://doi.org/10.1016/j.jweia.2023.105614