Jisang Ha, Myung-Il Roh, Ki-Su Kim, Min-Chul Kong, "Integrated Method for the Arrangement Design of a Ship for Implementing Digital Twin in Design", Proceedings of International Symposium on PRADS(Practical Design of Ships and Other Floating Structures) 2022, pp. 21, Dubrovnik, Croatia, 2022.10.09-13
Jisang Ha, Myung-Il Roh, Ki-Su Kim, Min-Chul Kong, "Integrated Method for the Arrangement Design of a Ship for Implementing Digital Twin in Design", Proceedings of PRADS 2022, Dubrovnik, Croatia, 2022.10.09-13
첨부 '1' |
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Abstract | The arrangement design of the ship mainly depends on the previous mothership data or the experience of experts because there are various restrictions of the owner and the classification regulations. Therefore, it is difficult to select the optimal design by examining various alternatives. Accordingly, a method that can review and optimize various arrangement designs before construction is required. Digital twin technology is one of the methods by which alternatives can be considered before production by creating digital replicas of real physical entities. This study propose a method for designing an optimal arrangement that satisfies the requirements of the ship-owner and several design rules and implements the result as a virtual twin. In the arrangement design process, locations of partitions dividing compartments and locations of each equipment are set as design variables. Furthermore, as objective functions, building cost, stability, and the feasibility for expert knowledge are considered. Also, the arrangement designed during the optimization process can be reviewed by the designer in advance as if the arrangement is actually manufactured through virtual twin. The effectiveness of the method proposed in this study is verified by applying it to selecting the optimal arrangement design for an actual ship. In particular, it has a differentiated advantage from the existing arrangement design optimization method in that the designer can visually review the design first. |
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Publication Date | 2022-10-10 |
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Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo, Ki-Su Kim, Min-Jae Oh, Sejin Oh, "Estimation Model of Hydrodynamic Performance Using Hull Form Variation and Deep Learning", Proceedings of PRADS 2022, Dubrovnik, Croatia, pp. 82, 2022.10.09-13
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Jisang Ha, Myung-Il Roh, Ki-Su Kim, Min-Chul Kong, "Integrated Method for the Arrangement Design of a Ship for Implementing Digital Twin in Design", Proceedings of PRADS 2022, Dubrovnik, Croatia, 2022.10.09-13
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Hye-Won Lee, Myung-Il Roh, Seung-Ho Ham, "Method for the Accurate and Automatic Operation of Offshore Floating Cranes for the Block Erection in Shipyards", Proceedings of OMAE 2020, Held in Virtual Conference, 2020.08.03-07
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Jisang Ha, Myung-Il Roh, Hye-Won Lee, Jong-Ho Eun, Jong-Jin Park, Hyun-Joe Kim, "A Method of the Collision Avoidance of a Ship Using Real-time AIS Data", Proceedings of ACSMO 2020, Seoul, Korea, pp. 106, 2020.11.23-25
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Ki-Su Kim, Myung-Il Roh, "Optimization of the Arrangement Design of a Ship Considering the Multiple Performance", Proceedings of ACSMO 2020, Seoul, Korea, pp. 167, 2020.11.23-25
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Jisang Ha, Myung-Il Roh, Jong-Hyeok Lee, Jin-Hyeok Kim, Min-Chul Kong, Seung-Ho Ham, "Integrated Ship Remote Operating System Based on Digital Twin Technology", Proceedings of TEAM 2019, Tainan, Taiwan, pp. 106, 2019.10.14-17
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Luman Zhao, Myung-Il Roh, Hye-Won Lee, Do-Hyun Chun, Sung-Jun Lee, "A Collision Avoidance Method of Multi-ships Based on Deep Reinforcement Learning Considering COLREGs," Proceedings of ICCAS 2019, Rotterdam, Netherlands, pp. 85-88, 2019.09.24-26
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Do-Hyun Chun, Myung-Il Roh, Hye-Won Lee, Seung-Ho Ham, "A Crane Movement Control for Stability of Block Erection Based on Deep Reinforcement Learning", MIM 2019, Berlin, Germany, 2019.08.28-30
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Do-Hyun Chun, Myung-Il Roh, Seung-Ho Ham, Hoon-Kyu Oh, Sang-Ok Lee, "Optimum Layout Design of Wedges of Panel for an LNG Tank Considering Amount of Resin Ropes", Proeedings of ISOPE 2019, Honolulu, Hawaii, pp. 1289-1292, 2019.06.16-21
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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