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    Weather Window Analysis in Operations and Maintenance Policies for Offshore Floating Multi-Purpose Platforms

    Source: Journal of Offshore Mechanics and Arctic Engineering:;2022:;volume( 145 ):;issue: 004::page 41701-1
    Author:
    Heo, Taemin
    ,
    Liu, Ding Peng
    ,
    Manuel, Lance
    DOI: 10.1115/1.4056344
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: In an emerging “blue economy,” the use of large multi-purpose floating platforms in the open ocean is being considered. Such platforms could possibly support a diversified range of commercial activities including energy generation, aquaculture, seabed mining, transport, tourism, and sea-based laboratories. A Markov decision process (MDP) framework is proposed to deal with operations and maintenance (O&M) issues that are inevitable; challenges arise from the complex stochastic weather conditions that need to be accounted for. Using data as well as contrasting synthetic simulations of relevant weather variables, we demonstrate the robustness/versatility of the MDP model. Two case studies—one involving constant and another involving time-dependent downtime costs—are conducted to demonstrate how the proposed MDP framework incorporates weather patterns from available data and can offer optimal policies for distinct metocean conditions (i.e., temporal variations in the weather). A realistic example that illustrates the implementation of the proposed framework for multiple O&M issues involving salmon net pens and wave energy converters demonstrates how our optimal policies can minimize O&M costs and maximize crew safety almost as if the true future were known for scheduling.
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      Weather Window Analysis in Operations and Maintenance Policies for Offshore Floating Multi-Purpose Platforms

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4292472
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    • Journal of Offshore Mechanics and Arctic Engineering

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    contributor authorHeo, Taemin
    contributor authorLiu, Ding Peng
    contributor authorManuel, Lance
    date accessioned2023-08-16T18:46:24Z
    date available2023-08-16T18:46:24Z
    date copyright12/26/2022 12:00:00 AM
    date issued2022
    identifier issn0892-7219
    identifier otheromae_145_4_041701.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4292472
    description abstractIn an emerging “blue economy,” the use of large multi-purpose floating platforms in the open ocean is being considered. Such platforms could possibly support a diversified range of commercial activities including energy generation, aquaculture, seabed mining, transport, tourism, and sea-based laboratories. A Markov decision process (MDP) framework is proposed to deal with operations and maintenance (O&M) issues that are inevitable; challenges arise from the complex stochastic weather conditions that need to be accounted for. Using data as well as contrasting synthetic simulations of relevant weather variables, we demonstrate the robustness/versatility of the MDP model. Two case studies—one involving constant and another involving time-dependent downtime costs—are conducted to demonstrate how the proposed MDP framework incorporates weather patterns from available data and can offer optimal policies for distinct metocean conditions (i.e., temporal variations in the weather). A realistic example that illustrates the implementation of the proposed framework for multiple O&M issues involving salmon net pens and wave energy converters demonstrates how our optimal policies can minimize O&M costs and maximize crew safety almost as if the true future were known for scheduling.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleWeather Window Analysis in Operations and Maintenance Policies for Offshore Floating Multi-Purpose Platforms
    typeJournal Paper
    journal volume145
    journal issue4
    journal titleJournal of Offshore Mechanics and Arctic Engineering
    identifier doi10.1115/1.4056344
    journal fristpage41701-1
    journal lastpage41701-12
    page12
    treeJournal of Offshore Mechanics and Arctic Engineering:;2022:;volume( 145 ):;issue: 004
    contenttypeFulltext
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