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
| 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. |
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| Publication Date | 2022-11-06 |
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Myung-Il Roh, "Simulation Based Engineering for Ship and Offshore Plant", International Ocean Technology Conference & Expo (IOTCE 2015), Qingdao, China, 2015.09.01-03
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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
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Myung-Il Roh, "Core AI Technologies for Autonomous Ships", 2023 Annual Autumn Meeting, JASNAOE (Japan Society of Naval Architects and Ocean Engineers), Nagasaki, Japan, 2023.11.27-28
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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
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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
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Myung-Il Roh, "Introduction to Program of University Specialized for Offshore Plant Engineering in Korea", Offshore Korea 2016, Busan, Korea, 2016.10.19-20
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Modeling & Simulation II, 2016년도 한국CAD/CAM학회 동계학술발표회, 평창, 2016.01.27-29
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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
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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
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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
