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Abstract The CFD (Computational Fluid Dynamics) analysis is normally used to evaluate the hydrodynamic performance of hull forms in the process of hull form design. The hull form candidates are improved through the iterative process of editing them if their performance is not good enough. However, since the CFD analysis is computationally expensive, the estimation of the hydrodynamic performance using it requires a long time. Due to the limited time for the design, the hull form iterations are not enough to find the optimal hull form. To solve this problem, we proposed a method to estimate the hydrodynamic performance of the hull forms using deep learning. The use of deep learning has the disadvantage that it takes a long time to accumulate data and learn but has the advantage that it takes only a very short time to run the model and obtain the result once training is complete. In this study, the hull form of a small ship was first parameterized with dozens of parameters to generate various hull forms. Then, a number of hull forms were created by randomly generating thousands of parameter sets that determine the hull form. Finally, the hydrodynamic performance for the ground truth was derived by performing CFD analysis on the hull forms. We considered multiple deep learning models to estimate the performance more accurately and selected the best model among them. The proposed method was applied to a small ship. As a result, with the proposed model, the hydrodynamic performance of the hull forms can be estimated shortly with a certain level of error.
Publication Date 2022-11-06

Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo, Ki-Su Kim, "Estimation of the Hydrodynamic Performance of the Parameterized Hull Forms Using Deep Learning", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10


List of Articles
번호 분류 제목 Publication Date
466 International Conference Ji-Hyun Hwang, Young-Joo Ahn, Joon-Ho Min, Gwang-No Lee, Ho-Jin Jeong, Mung-Yu Kim, Hee-Chang Kim, Myung-Il Roh, Kyu-Yeul Lee, "Application of an Integrated Basic Process Engineering Solution to Generic LNG FPSO Topsides", Proceedings of ISOPE 2009 file 2009-06-21
» International Conference Jin-Hyeok Kim, Myung-Il Roh, In-Chang Yeo, Ki-Su Kim, "Estimation of the Hydrodynamic Performance of the Parameterized Hull Forms Using Deep Learning", Proceedings of G-NAOE 2022, Changwon, Korea, 2022.11.06-10 2022-11-06
464 International Conference 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 file 2022-10-09
463 International Conference 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 file 2020-11-23
462 International Conference 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 file 2019-10-16
461 International Conference 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 file 2022-10-10
460 International Conference Jisang Ha, Myung-Il Roh, Min-Chul Kong, Mijin Kim, Jeoungyoun Kim, Nam-Kug Ku, "An Automated Method for Pipe Routing in Ship Unit Modules", Proceedings of IMDC 2024, Amsterdam, Netherland, 2024.06.02-06 2024-06-02
459 International Conference Jisang Ha, Myung-Il Roh, Sung-Jun Lee, Ki-Su Kim, Seung-Min Lee, "Toward Rapid Analysis Using Surrogate Model by Deep Learning and Application to Ship Flooding Analysis", Proceedings of ISCDE 2017, Ho Chi Minh, Vietnam, pp. 1-2, 2017.12.13-16 file 2017-12-15
458 International Conference Jisang Ha, Myung-Il Roh, Sung-Jun Lee, Ki-Su Kim, Seung-Min Lee, "Toward Rapid Flooding Analysis of a Ship Using Surrogate Model by Deep Learning", Proceedings of the 31st Asian-Pacific TEAM 2017, Osaka, Japan, pp. 397-400, 2017.09.25-28 file 2017-09-26
457 International Conference John-Kyu Hwang, Geun-Jae Bang, Myung-Il Roh, Kyu-Yeul Lee, "Detailed Design and Construction of the Hull of an FPSO(Floating, Production, Storage, and Off-loading unit)", Proceedings of ISOPE 2009, Osaka, Japan, pp. 151-158, 2009.06.21-26 file 2009-06-21
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