Modeling of snow load using filtered poisson process
Document Type
Conference Proceeding
Publication Date
12-1-2009
Abstract
Stochastic process modeling of snow loads has been applied in structural reliability analysis. However, the snow load is usually modeled by a, random variable with a specific distribution (e.g., Lognormal distribution) in combination with a Bernoulli pulse process. In this paper, the Filtered Poisson Process (FPP) is used to model the snow load. Simulated records are compared with weather records of Stampede Pass, WA. and Buffalo, NY, obtained from the National Climatic Data Center (NCDC). The FPP model is demonstrated to be versatile for both heavy and light snow load areas. Copyright ASCE 2009.
Publication Title
Proceedings of the International Conference on Cold Regions Engineering
Recommended Citation
Yin, Y.,
Bulleit, W.,
&
Li, Y.
(2009).
Modeling of snow load using filtered poisson process.
Proceedings of the International Conference on Cold Regions Engineering, 618-626.
http://doi.org/10.1061/41072(359)60
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/8724