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Abstract Design of a ship hull form is very complex and time consuming process. It starts from the selection of a parent ship, and a designer modifies the selected ship to meet the owner’s and Class requirements. When the hull form is modified, the hydrodynamic analysis is conducted. If the hydrodynamic performance is acceptable, the verification is done through the model test. If the hydrodynamic performance is not acceptable, a designer modifies the hull form manually until it satisfies a certain requirement. During this process, a lot of time is consumed, and it requires the designer’s experiences. The modification methods can be different, and the quality of the hull form can be varied from the designer’s proficiency. In this study, the optimization method is proposed to obtain the optimized hull form automatically using the reinforcement learning that is one of the deep learning methods. The smallest total resistance of a hull form is used as the reward in the reinforcement learning, but the other hydrodynamic performance values can be used as the rewards. The KVLCC2 tanker that is a public hull form is used to get the optimal hull form, and the result shows that the proposed method can generate the optimal hull form. It is expected that the proposed method can be used in the hull form design to reduce the time and enhance the performance.
Publication Date 2019-07-08

Min-Jae Oh, Myung-Il Roh, Young-Soo Seok, and Sung-Jun Lee, "Optimization of a Ship Hull Form using Deep Learning", Proceedings of ACDDE(Asian Conference on Design and Digital Engineering) 2019, Penang, Malaysia, 2019.07.07-10

List of Articles
번호 분류 제목 Publication Date
392 International Conference Min-Chul Kong, Myung-Il Roh, Ki-Su Kim, Jongoh Kim, Hogyun Park, Jeongyoul Lee, "A Method of Variable Recognition and Connection for Reviewing Ship Regulations", Proceedings of ICCAS 2022, Yokohama, Japan, pp. 171-175, 2022.09.13-15 file 2022-09-14
391 International Conference Min-Jae Oh, Myung-Il Roh, "Hull Form Surface Generation Using T-Spline", Proceedings of the 31st Asian-Pacific TEAM 2017, Osaka, Japan, 2017.09.25-28 file 2017-09-25
390 International Conference Min-Jae Oh, Myung-Il Roh, Sung-Woo Park, Do-Hyun Chun, In-Il Kim, Chang-Yong Kim, Won-Joon Lee, "Estimation of Ship Energy Efficiency from Big Data Analysis", Proceedings of the 32nd Asian-Pacific TEAM 2018, Wuhan, China, pp. 262-264, 2018.10.15-18 file 2018-10-17
389 International Conference Min-Jae Oh, Myung-Il Roh, Sung-Woo Park, Do-Hyun Chun, Jeong-Youl Lee, Myeong-Jo Son, "Operational Analysis of Container Ships Using AIS Data", Proceedings of ACDDE 2018, Okinawa, Japan, 2018.11.1-3 file 2018-11-01
» International Conference Min-Jae Oh, Myung-Il Roh, Young-Soo Seok, and Sung-Jun Lee, "Optimization of a Ship Hull Form using Deep Learning", Proceedings of ACDDE 2019, Penang, Malaysia, 2019.07.07-10 file 2019-07-08
387 Conference Chairman Modeling & Simulation II, 2016년도 한국CAD/CAM학회 동계학술발표회, 평창, 2016.01.27-29 2016-01-28
386 Invited Seminar Myung-Il Roh, "Introduction to Program of University Specialized for Offshore Plant Engineering in Korea", Offshore Korea 2016, Busan, Korea, 2016.10.19-20 2016-10-20
385 Invited Seminar Myung-Il Roh, "SNU Education Programs for Offshore Engineering", The 30th Asian-Pacific TEAM(Technical Exchange and Advisory Meeting on Marine Structures) 2016, Mokpo, Korea, 2016.10.10.10 2016-10-11
384 International Conference Myung-Il Roh, "Applications of Deep Learning in Ship Design, Production, and Operation Stages", Proceedings of ICDM(International Conference on Decarbonization and Digitalization in Marine Engineering) 2022, Siheung, Korea, 2022.04.28-29 2022-04-29
383 International Conference Myung-Il Roh, "Physics-based Simulation for Design, Production, and Installation of Ships and Offshore Structures", International Symposium on Computational Design and Engineering, Ho Chi Minh, Vietnam, 2017.12.13-16 2017-12-15
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