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    Application of reinforcement learning to fire suppression system of an autonomous ship in irregular waves

    Application of reinforcement learning to fire suppression system of an autonomous ship in irregular waves

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    In fire suppression, continuous delivery of water or foam to the fire source is essential. The present study concerns fire suppression in a ship under sea condition, by introducing reinforcement learning technique to aiming of fire extinguishing nozzle, which works in a ship compartment with six degrees of freedom movement by irregular waves. The physical modeling of the water jet and compartment motion was provided using Unity 3D engine. In the reinforcement learning, the change of the nozzle angle during the scenario was set as the action, while the reward is proportional to the ratio of the water particle delivered to the fire source area. The optimal control of nozzle aiming for continuous delivery of water jet could be derived. Various algorithms of reinforcement learning were tested to select the optimal one, the proximal policy optimization.

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    Titel :

    Application of reinforcement learning to fire suppression system of an autonomous ship in irregular waves

    Beteiligte:
    Eun-Joo Lee (Autor:in) / Won-Sun Ruy (Autor:in) / Jeonghwa Seo (Autor:in)
    Erschienen in:

    International Journal of Naval Architecture and Ocean Engineering, Vol 12, Iss , Pp 910-917 (2020)

    Erscheinungsdatum :

    2020

    ISSN :

    2092-6782

    DOI :

    https://doi.org/10.1016/j.ijnaoe.2020.11.001

    Medientyp :

    Aufsatz (Zeitschrift)

    Format :

    Elektronische Ressource

    Sprache :

    Unbekannt

    Schlagwörter :

    Automatic fire suppression , Reinforcement learning , Position based fluids , Ocean engineering , TC1501-1800 , Naval architecture. Shipbuilding. Marine engineering , VM1-989

    Metadata by DOAJ is licensed under ​CC BY-SA 1.0

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