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    The Safety Assessment of Civil Ships Against Capsizing Based on the Probability Analysis of Multiple Threshold-Crossings of Stochastic Sea Waves

    Source: ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2024:;volume( 011 ):;issue: 003::page 31205-1
    Author:
    Zhang, Zhenhao
    ,
    Wei, Guoqing
    ,
    Zeng, Zhe
    ,
    Teng, Fengwei
    DOI: 10.1115/1.4066829
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper investigates the impact of threshold-crossing events on ship capsizing through a probabilistic model that predicts random wave heights. Utilizing statistical data from wave height observations, this paper proposes that random waves can be approximated and modeled using the Wiener process, employing autocorrelation function identification and probabilistic statistical verification methods. The threshold-crossing duration of a random wave is just the period of the wave exceeds a given threshold, which can reflect the frequency property of the stochastic sea waves. And the probability distribution of the period can theoretically be determined using the derived probability density function for the time interval between any two adjacent crossings of the Wiener process and a threshold. Based on the above theories, the capsizing probabilities of a civil ship sailing in different wave areas are analyzed under different safety thresholds considering certain ratios of the ship's intrinsic period and wave period. The research results can provide a reference for the anti-overturning design of the ships under the action of random waves.
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      The Safety Assessment of Civil Ships Against Capsizing Based on the Probability Analysis of Multiple Threshold-Crossings of Stochastic Sea Waves

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4306643
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    • ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering

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    contributor authorZhang, Zhenhao
    contributor authorWei, Guoqing
    contributor authorZeng, Zhe
    contributor authorTeng, Fengwei
    date accessioned2025-04-21T10:39:43Z
    date available2025-04-21T10:39:43Z
    date copyright11/22/2024 12:00:00 AM
    date issued2024
    identifier issn2332-9017
    identifier otherrisk_011_03_031205.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4306643
    description abstractThis paper investigates the impact of threshold-crossing events on ship capsizing through a probabilistic model that predicts random wave heights. Utilizing statistical data from wave height observations, this paper proposes that random waves can be approximated and modeled using the Wiener process, employing autocorrelation function identification and probabilistic statistical verification methods. The threshold-crossing duration of a random wave is just the period of the wave exceeds a given threshold, which can reflect the frequency property of the stochastic sea waves. And the probability distribution of the period can theoretically be determined using the derived probability density function for the time interval between any two adjacent crossings of the Wiener process and a threshold. Based on the above theories, the capsizing probabilities of a civil ship sailing in different wave areas are analyzed under different safety thresholds considering certain ratios of the ship's intrinsic period and wave period. The research results can provide a reference for the anti-overturning design of the ships under the action of random waves.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleThe Safety Assessment of Civil Ships Against Capsizing Based on the Probability Analysis of Multiple Threshold-Crossings of Stochastic Sea Waves
    typeJournal Paper
    journal volume11
    journal issue3
    journal titleASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering
    identifier doi10.1115/1.4066829
    journal fristpage31205-1
    journal lastpage31205-12
    page12
    treeASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg:;2024:;volume( 011 ):;issue: 003
    contenttypeFulltext
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