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A Bayesian Network Approach to Evaluate Shipboard Launch and Recovery Performance in Early-Stage Ship Design

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Practical Design of Ships and Other Floating Structures (PRADS 2019)

Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 65))

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Abstract

Vessel performance in shipboard launch and recovery operations is a critical element of its overall mission effectiveness. Both commercial and military vessels are required to launch and recover a variety of manned and unmanned platforms including submersibles, small boats, aircraft, and amphibious vehicles. A fundamental attribute of these launch and recovery operations is their dependence on a number of probabilistic factors such as environmental conditions and design factors associated with the vessel and the platforms. To facilitate effective launch and recovery operations, ship designers require a design method that takes into account these probabilistic factors to gain a better understanding the implications of launch and recovery on a variety of early stage design decisions. Recent advancements in design tools and methodologies have pushed critical decisions earlier in the design process which necessitates evaluating mission critical systems sooner as well.

This paper presents an application of Bayesian networks for evaluating the performance of shipboard launch and recovery operations. Bayesian networks provide a framework for understanding system interdependencies by modeling and analyzing conditional probabilities between variable pairs. In previous ship design research, Bayesian networks have been applied to risk modeling and the examination of principal particulars.

This research utilizes Bayesian networks to model the environmental and design factors that contribute to the performance of launch and recovery operations, using a level of information that is consistent with early-stage ship design. These networks are analyzed and examined to assess the impact of the overall design attributes on those factors. A ship design case study is presented to demonstrate the method and elucidate the driving interdependencies in launch and recovery operations.

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Authors and Affiliations

  1. Department of Naval Architecture and Marine Engineering, University of Michigan, Ann Arbor, MI, USA

    James A. Coller & David J. Singer

Authors
  1. James A. Coller
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  2. David J. Singer
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Correspondence to James A. Coller .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, Yokohama National University, Yokohama, Kanagawa, Japan

    Tetsuo Okada

  2. School of Engineering, The University of Tokyo, Bunkyo-ku, Tokyo, Japan

    Katsuyuki Suzuki

  3. Faculty of Engineering, Yokohama National University, Yokohama, Japan

    Yasumi Kawamura

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Coller, J.A., Singer, D.J. (2021). A Bayesian Network Approach to Evaluate Shipboard Launch and Recovery Performance in Early-Stage Ship Design. In: Okada, T., Suzuki, K., Kawamura, Y. (eds) Practical Design of Ships and Other Floating Structures. PRADS 2019. Lecture Notes in Civil Engineering, vol 65. Springer, Singapore. https://doi.org/10.1007/978-981-15-4680-8_1

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  • DOI: https://doi.org/10.1007/978-981-15-4680-8_1

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-4679-2

  • Online ISBN: 978-981-15-4680-8

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