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    Modeling of Snow Load Using Filtered Poisson Process

    New search for: Yin, Y. J.
    New search for: Bulleit, W. M.
    New search for: Li, Y.

    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.

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    Modeling of Snow Load Using Filtered Poisson Process

    New search for: Yin, Y. J.
    New search for: Bulleit, W. M.
    New search for: Li, Y.

    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.

    Access

    Check access
    Check availability in my library
    Order at Subito €

    Modeling of Snow Load Using Filtered Poisson Process

    New search for: Yin, Y. J.
    New search for: Bulleit, W. M.
    New search for: Li, Y.

    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.

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    Title:

    Modeling of Snow Load Using Filtered Poisson Process

    Contributors:

    Yin, Y. J. (author) / Bulleit, W. M. (author) / Li, Y. (author)

    Conference:

    14th Conference on Cold Regions Engineering ; 2009 ; Duluth, Minnesota, United States

    Published in:

    Cold Regions Engineering 2009 ; 618-626

    Publication date:

    2009-08-27

    ISBN:

    9780784410721

    DOI:

    https://doi.org/10.1061/41072(359)60

    Type of media:

    Conference paper

    Type of material:

    Electronic Resource

    Language:

    English

    Keywords:

    Pavement management , Iran , Canada , United States , Numerical models , Frost , Waste treatment plants , Railroad tracks , Cold regions , Filtration , Cold weather construction , Denmark , Snow loads , Stochastic processes , Russia (after 1991) , Japan

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