Chinese Journal of Ship Research, Volume. 17, Issue 6, 174(2022)

Time domain modeling and simulation of warship flooding process based on counter-flooding activities

Shiyao WANG1, Yue HOU1, Kangbo WANG2, and Li GONG2
Author Affiliations
  • 1College of Power Engineering, Naval University of Engineering, Wuhan 430033, China
  • 2Warship Integrated Testing and Training Baser, Naval University of Engineering, Wuhan 430033, China
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    Objectives

    Warship damage flooding is an interactive process between progressive flooding and counter-flooding measures under battle-damaged conditions. Traditional damage stability theory cannot simulate the influence of counter-flooding measures on the damaged warship flooding process, and there is no method for predicting this process in the full-time domain.

    Methods

    By analyzing a coupling relationship between the damage flooding process and counter-flooding measures, a flooding process time domain model is established and a numerical solving algorithm obtained. Case studies are analyzed on the basis of the model and algorithm, and an interactive visual simulation system is developed.

    Results

    The simulation systemcan comprehensively assess the flooding process and various counter-flooding measures, providing an important supplement for warship damage stability theory.

    Conclusions

    This study can help designers to understand the effectiveness of counter-flooding design schemes on the flooding process and guide the design of counter-flooding systems. In addition, it can be used for shipboard flooding decision-making, giving it high military application value.

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    Shiyao WANG, Yue HOU, Kangbo WANG, Li GONG. Time domain modeling and simulation of warship flooding process based on counter-flooding activities[J]. Chinese Journal of Ship Research, 2022, 17(6): 174

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    Paper Information

    Category: Ship Design and Performance

    Received: Sep. 7, 2020

    Accepted: --

    Published Online: Mar. 26, 2025

    The Author Email:

    DOI:10.19693/j.issn.1673-3185.02312

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