Journal of the Society of Naval Architects of Korea (대한조선학회논문집)

The Society of Naval Architects of Korea (대한조선학회)
권호 표지
DOI QR코드

DOI QR Code

Development of Maneuvering Scenario for Data-Driven Modeling of Ship Dynamics

선박 동역학의 데이터 기반 모델링을 위한 조종 시나리오 개발

  • Dong-Hwan Kim (Research Institute of Future Mobility System, Chungnam National University) ;
  • Minchang Kim (Department of Autonomous Vehicle System Engineering, Chungnam National University) ;
  • Seungbeom Lee (Department of Autonomous Vehicle System Engineering, Chungnam National University) ;
  • Jeonghwa Seo (Department of Naval Architecture and Ocean Engineering, Chungnam National University)
  • 김동환 (충남대학교 미래모빌리티연구소) ;
  • 김민창 (충남대학교 자율운항시스템공학과) ;
  • 이승범 (충남대학교 자율운항시스템공학과) ;
  • 서정화 (충남대학교 선박해양시스템공학과)
  • Received : 2024.03.18
  • Accepted : 2024.06.10
  • Published : 2024.08.20
Download PDF
⟨ Previous Next ⟩

Abstract

A method for quantifying the adaptability of ship maneuver scenarios for data-driven modeling of ship dynamics is developed based on the principal component analysis. A random maneuver scenario is suggested as a reference for ship dynamics, which can obtain the converged principal components of ship dynamics features by the Monte Carlo simulation. Principal components of conventional maneuver scenarios defined by the International Maritime Organization (IMO) are compared to that of the random maneuver. A conventional ship dynamics model for a container carrier vessel for four degrees of freedom dynamics is introduced to simulate the random and IMO maneuver scenarios. It is confirmed that the IMO tests follow the tendency of random maneuver scenario in terms of execution time and adaptability.

Keywords

Acknowledgement

이 연구는 2024년 정부(방위사업청)의 재원으로 국방과학연구소의 지원을 받아 수행된 미래도전국방기술 연구개발사업임(No.915071101)

References

  1. Abkowitz, M.A., 1980. Measurement of hydrodynamic characteristics from ship maneuvering trials by system identification. Annual Meeting of the Society of Naval Architects and Marine Engineers, Jersey City, NJ.
  2. Araki, M., Sadat-Hosseini, H., Sanada, Y., Tanimoto, K., Umeda, N. and Stern, F., 2012. Estimating maneuvering coefficients using system identification methods with experimental, system-based, and CFD free-running trial data. Ocean Engineering, 51, pp.63-84. https://doi.org/10.1016/j.oceaneng.2012.05.001
  3. Casado, M.H., Ferreira, R. and Velasco, F.J., 2007. Identification of nonlinear ship model parameters based on the turning circle test. Journal of Ship Research, 51(2), pp.174-181. https://doi.org/10.5957/jsr.2007.51.2.174
  4. Chillcce, G. and el Moctar, O., 2023. Data-driven system identification of hydrodynamic maneuvering coefficients from free-running tests. Physics of Fluids, 35, Article No. 057122.
  5. Hamamoto, M. and Kim, Y.-S., 1993. A new coordinate system and the equations describing manoeuvring motion of a ship in waves. Journal of the Society of Naval Architects of Japan, 173, pp.209-220. https://doi.org/10.2534/jjasnaoe1968.1993.209
  6. ITTC, 2017. Captive model test. International Towing Tank Conference - Recommended Procedures and Guidelines, 7.5-02-06-02.
  7. Jeon, M., Yoon, H.K., Park, J., Rhee, S.H. and Seo, J., 2022. Identification of 4-DoF maneuvering mathematical models for a combatant in intact and damaged conditions. International Journal of Naval Architecture and Ocean Engineering, 14, Article no.100480.
  8. Kim, D., Yun, K., 2021. Simple kinematic model generation by learning control inputs and velocity outputs of a ship. Journal of Navigation and Port Research, 45(6), pp.284-297.
  9. Kim, K., Kim, H., Choi, S., Na, K.-I., Lee, H. and Seo, J., 2022. Development of ship dynamics model by free-running model tests and regression. Journal of the Society of Naval Architects of Korea, 59(3), pp.173-182. https://doi.org/10.3744/SNAK.2022.59.3.173
  10. Kim, D.-H., Kim, M., Lee, S. and Seo, J., 2024. A study on 4DOF ship dynamics in maneuver by principal component analysis. Journal of the Society of Naval Architects of Korea, 61(1), pp.29-44.
  11. Nouri, N.M. and Valadi, M., 2017. Robust input design for nonlinear dynamic modeling of AUV. ISA Transactions, 70, pp.288-297. https://doi.org/10.1016/j.isatra.2017.02.006
  12. Okuda, R., Yasukawa, H. and Matsuda, A., 2023. Validation of maneuvering simulations for a KCS at different forward speeds using the 4-DOF MMG method. Ocean Engineering, 284, 115174.
  13. Sutulo, S. and Guedes Soares, C., 2023. Application of an offline identification algorithm for adjusting parameters on a modular manoeuvring mathematical model. Ocean Engineering, 279, Article No. 114328.
  14. Wakita, K., Maki, A., Umeda, N., Miyauchi, Y., Shimoji, T., R Achman, D.M. and Akimoto, Y., 2022. On neural network identification for low-speed ship maneuvering model. Journal of Marine Science and Technology, 22, pp.772-785. https://doi.org/10.1007/s00773-021-00867-1
  15. Wang, Z., Soares, C.G. & Zou, Z., 2020. Optimal design of excitation signal for identification of nonlinear ship manoeuvring model. Ocean Engineering, 196, Article No. 106778.
  16. Wang, T., Li, G., Hatledal, L. I., Skulstad, R., Æsoy, V. and Zhang, H., 2022. Incorporating approximate dynamics into data-driven calibrator: a representative model for ship maneuvering prediction. IEEE Transactions on Industrial Informatics, 18(3), pp. 1781-1789. https://doi.org/10.1109/TII.2021.3088404
  17. Yasukawa, H., Sakuno, R. and Yoshimura, Y., 2019. Practical maneuvering simulation method of ships considering the roll-coupling effect. Journal of Marine Science and Technology, 24, pp.1280-1296. https://doi.org/10.1007/s00773-019-00625-4
  18. Yoon, H.K. and Rhee, K.P., 2003. Identification of hydrodynamic coefficients in ship maneuvering equations of motion by estimation-before-modeling technique. Ocean Engineering, 30, pp.2379-2404. https://doi.org/10.1016/S0029-8018(03)00106-9