Validation of 4DOF maneuvering coefficients optimization using hydrodynamic force and moment estimated from free-running model test results

키워드

참고문헌 (49)

1. Measurement of Hydrodynamic Characteristics from Ship Maneuvering Trials by System Identification, "Abkowitz, M. A.", Society of Naval Architects and Marine Engineers, ~ (1980)
2. Araki, M., "Estimating maneuvering coefficients using system identification methods with experimental, system-based, and CFD free-running trial data", Ocean Eng, 51, pp.63~84 (2012)
3. Bonci, M., "Method for establishing parameters of practical ship manoeuvring models based on the combination of RANSE computations and system identification", Appl. Ocean Res, 52, pp.274~294 (2015)
4. Cao, J., "Parametric estimation of ship maneuvering motion with integral sample structure for identification", Appl. Ocean Res, 52, pp.212~221 (2015)
5. Carrica, P. M., "Direct simulation and experimental study of zigzag maneuver of KCS in shallow water", Ocean Eng, 112, pp.117~133 (2016)
6. Casado, M. H., "Identification of nonlinear ship model parameters based on the turning circle test", J. Ship Res, 51(2), pp.174~181 (2007)
7. Chillcce, G., "Data-driven system identification of hydrodynamic maneuvering coefficients from free-running tests", Phys. Fluids, 35 (2023)
8. Dubbioso, G., "Aspects of twin screw ships semi-empirical maneuvering models", Ocean Eng, 48, pp.69~80 (2012)
9. Gou, Y., "Deep Ocean : a general deep learning framework for spatio-temporal ocean sensing data prediction", IEEE Access, 8, pp.79192~79202 (2020)
10. Hamamoto, M., "A new coordinate system and the equations describing manoeuvring motion of a ship in waves", J. Jpn. Soc. Nav. Archit. Ocean Eng, 173, pp.209~220 (1993)
11. Hao, L., "Recurrent neural networks for nonparametric modeling of ship maneuvering motion", Int. J. Nav. Archit. Ocean Eng, 14 (2022)
12. Hooft, J. P., "Maneuverability of frigates in wave", Mar. Technol, 25, pp.262~271 (1988)
13. IMO, "Explanatory notes to the standards for ship manoeuvrability", MSC.Circ, 1053~ (2002)
14. Jeon, M., "Identification of 4-DoF maneuvering mathematical models for a combatant in intact and damaged conditions", Int. J. Nav. Archit. Ocean Eng, 14 (2022)
15. Juan, N. P., "Review of the application of artificial neural networks in ocean engineering", Ocean Eng, 259 (2022)
16. Karagiannidis, P., "Data-driven modeling of ship propulsion and the effect of data pre-processing on the prediction of ship fuel consumption and speed loss", Ocean Eng, 222 (2021)
17. Kawai, T., "Sea state estimation using monitoring data by convolutional neural network (CNN)", J. Mar. Sci. Technol, 26, pp.947~962 (2021)
18. Kijima, K., "On the Manoeuvring performance of a ship with the parameter of loading condition", J. Jpn. Soc. Nar. Archit. Ocean Eng, 168, pp.141~148 (1990)
19. Kim, Y. -G., "Prediction of maneuverability of KCS with 4 degrees of freedom", J. Soc. Nav. Archit. Korea, 48(3), pp.267~274 (2011)
20. Kim, I., "Estimation of the manoeuvrability of the KVLCC2 in calm water using free-running simulation based on CFD", Int. J. Nav. Archit. Ocean Eng, 13, pp.466~477 (2021)
21. Kim, K., "Devleopment of ship dyanmics model by free-running model tests and regression", J. Soc. Nav. Archit. Korea, 59(3), pp.173~182 (2022)
22. Kim, J. -H., "Development of automatic gain-tuning algorithm for heading control using freerunning test data", Int. J. Nav. Archit. Ocean Eng, 15 (2023)
23. Kwon, C., "A study on PID controlled self-propulsion and turning simulations based on the URANS CFD free running approach", Int. J. Nav. Archit. Ocean Eng, 15 (2023)
24. Luo, W., "Manoeuvring simulation of catamaran by using implicit models based on support vector machines", Ocean Eng, 82, pp.150~159 (2014)
25. Luo, W., "Measures to diminish the parameter drift in the modeling of ship manoeuvring using system identification", Appl. Ocean Res, 67, pp.9~20 (2017)
26. Lou, J., "Deep learning method for 3-DOF motion prediction of unmanned surface vehicles based on real sea maneuverability test", Ocean Eng, 250 (2022)
27. Park, J., "Uncertainty assessment of outdoor free-running model tests for maneuverability analysis of a damaged surface combatant", Ocean Eng, 252 (2022)
28. Pokhrel, P., "A transformerbased regression scheme for forecasting significant wave heights in oceans", IEEE J. Ocean. Eng, 47(4), pp.1010~1023 (2022)
29. Sadat-Hosseini, H., "CFD, system-based and EFD study of ship dynamic instability events: surf-riding, periodic motion, and broaching", Ocean Eng, 38(1), pp.88~110 (2011)
30. Sanada, Y., "Trajectories for ONR tumblehome maneuvering in calm water and waves", Ocean Eng, 72, pp.45~65 (2013)
31. Sanada, Y., "ONR tumblehome course keeping and maneuvering in calm water and waves", J. Mar. Sci. Technol, 24, pp.948~967 (2019)
32. Seo, J., "Captive model tests for assessing maneuverability of a damaged surface combatant with initial heel angle", J. Ship Res, 64(4), pp.392~406 (2020)
33. Seo, J., "Free-running model tests for assessing maneuverability of a damaged surface combatant", Proceedings of the 33rd Symposium on Naval Hydrodynamics (2020)
34. Seo, J., "Data-driven modeling of ship dynamics by regression of free-running model test results", Proceedings of the 34th Symposium on Naval Hydrodynamics (2022)
35. Sutulo, S., "An algorithm for offline identification of ship manoeuvring mathematical models from free-running tests", Ocean Eng, 79, pp.10~25 (2014)
36. Sutulo, S., "Application of an offline identification algorithm for adjusting parameters on a modular manoeuvring mathematical model", Ocean Eng, 279 (2023)
37. Ueno, M., "Circular motion tests and uncertainty analysis for ship maneuverability", J. Mar. Sci. Technol, 14, pp.469~484 (2009)
38. Umeda, N., "Model experiments on extreme motions of a wave-piercing tumblehome vessel in following and quartering waves", J. Jpn. Soc. Nav. Archit. Ocean Eng, 8, pp.123~129 (2008)
39. Wakita, K., "On neural network identification for low-speed ship maneuvering model", J. Mar. Sci. Technol, 27, pp.772~785 (2022)
40. Wang, Z., "Identification of ship manoeuvring motion based on nu-support vector machine", Ocean Eng, 183, pp.270~281 (2019)
41. Wang, T., "Incorporating approximate dynamics into data-driven calibrator : a representative model for ship maneuvering prediction", IEEE Trans. Ind. Inf, 18(3), pp.1781~1789 (2022)
42. Xue, Y., "Hydrodynamic parameter identification for ship manoeuvring mathematical models using a bayesian approach", Ocean Eng, 195 (2020)
43. Yasukawa, H., "Maneuverability and hydrodynamic derivatives of ships traveling in heeled condition", J. Jpn. Soc. Nav. Archit. Ocean Eng, 17, pp.19~29 (2013)
44. Yasukawa, H., "Introduction of MMG standard method for ship maneuvering predictions", J. Mar. Sci. Technol, 20, pp.37~52 (2015)
45. Yasukawa, H., "Practical maneuvering simulation method of ships considering the roll-coupling effect", J. Mar. Sci. Technol, 24, pp.1280~1296 (2019)
46. Yoon, H., "Benchmark CFD validation data for surface combatant 5415 in PMM maneuvers – Part 1: force", moment, Ocean Eng, pp.2015, 109[DOI]
47. Zhang, X., "Identification of abkowitz model for ship manoeuvring motion using ε-support vector regression", J. Hydrodyn, 23(3), pp.353~360 (2011)
48. Zhang, G., "Multi-innovation auto-constructed least squares identification for 4 DOF ship manoeuvring modelling with full-scale trial data", ISA(Instrum. Soc. Am. )Trans, 58, pp.186~195 (2015)
49. Zhu, M., "Identification-based simplified model of large container ships using support vector machines and artificial bee colony algorithm", Appl. Ocean Res, 68, pp.249~261 (2017)

관련 논문AI추천