MATHEMATICAL MODEL OF VESSEL STABILITY ON REGULAR WAVES
https://doi.org/10.33815/2313-4763.2024.1.28.041-056
Abstract
One of the important issues of shipping safety is a significant decrease and even loss of stability of ships in waves, as evidenced by accident statistics. In real operating conditions, the shape of the volume of the underwater part of the ship’s hull changes all the time, which leads to changes in the metacentric height and stability shoulder up to 40%. Research has established that the greatest danger for ships is an encounter with a wave whose length coincides with the length of the ship. Guidelines and Recommendations for safe sailing in adverse weather conditions are provided in IMO documents. However, in order to respond to hazards in accordance with existing guidelines, the hazards must first be identified, which is already a difficult technical task, since, in addition to the specified hazard, there are other hazards that can lead to a capsize of the ship or a collapse of the hull. According to the authors of the article, the most radical way to avoid dangers is to utilize automated systems or automatic control modules in automated systems. Effective functioning of automated and automatic systems is ensured by mathematical models of objects or processes, which must have sufficient speed for the possibility of their use in real time. Therefore, the development of such a model is an urgent scientific and technical task. The work developed an analytical model for calculating the restoring moment of the vessel in the roll channel, which allows to estimate the stability of the vessel on regular waves. The developed analytical model can be used both in laboratory studies on stability on regular waves, and in the on-board computer of the automated ship motion control system, which will allow to constantly, at each step of the on-board computer, assess the stability of the ship, thereby reducing the risks of capsizing, loss of the ship and cargo. The possibility of using the analytical model in the on-board computer is explained by the small requirements for computing power. The obtained results differ from the known solutions in that they allow to automate the stability control processes on regular waves, reduce the influence of the human factor and increase the safety of navigation.
References
2. Recommendation on intact stability for passenger and cargo ships under 100 meters in length, IMCO RESOLUTION A.167 (ES.IV) adopted on 28 November (1968).
3. Guidance to the master for avoiding dangerous situations in following and quartering seas, IMO MSC/Circ.707. Ref. T1/2.04/ (1995).
4. Recommendation on a severe wind and rolling criterion (weather criterion) for the intact stability of passenger and cargo ships of 24 meters in length and over, IMO RESOLUTION A.562(14) adopted on 20 November (1985).
5. Revised guidance to the master for avoiding dangerous situations in adverse weather and sea conditions, IMO MSC.1/Circ.1228 (2007), 8 p.
6. Capt. Takuzo Okada (2019). Marine Weather Ship Handling in Rough Sea, Japan P&I Club. P&I Loss Prevention Bulletin 45, 100 p.
7. Nosov, P, Koretsky, O., Zinchenko, S., Prokopchuk, Yu., Gritsuk, I., Sokol, I., Kyrychenko, K. (2023). Devising an approach to safety management of vessel control through the identification of navigator's state, Eastern-European Journal of Enterprise Technologies, 4(3(124)),19–32. DOI: 10.15587/1720-4061.2023.286156.
8. Zinchenko, S., Kobets, V., Tovstokoryi, O., Kyrychenko, K., Nosov, P., Popovych, I, (2023). Control of the Pivot Point Position of a Conventional Single-Screw Vessel, CEUR-WS.org, Vol.3513, P.130–140, (ICST-2023). https://ceur-ws.org/Vol-3513/paper11.pdf.
9. Zinchenko, S., Kyrychenko, K., Grosheva, O., Nosov, P., Popovych, I., Mamenko, P. (2023). Automatic reset of kinetic energy in case of inevitable collision of ships, IEEE Xplore, p. 496–500, 13th International Conference on Advanced Computer Information Technologies (ACIT), Wrocław, Poland. DOI: 10.1109/ACIT58437.2023.10275545.
10. Zinchenko, S., Kobets, V., Tovstokoryi, O., Nosov, P., Popovych, I. (2023). Intelligent System Control of the Vessel Executive Devices Redundant Structure, CEUR Workshop Proceedings, Vol-3403, pp. 582–594. https://ceur-ws.org/Vol-3403/.
11. Krugliy, D. G., Appazov, Е. S., Zinchenko, S. М., and Nosov, P. S. (2021). Choice of the Fractal Method For Visualization of Input Data While Designing Support Systems for Decision-Making by Navigator. Sci. in nov. 2021. V. 17, no. 5. P. 63–72. DOI: 10.15407/scine17.05.063.
12. Zeng, K., Lu, J., Gu, M., Chen, Y. (2023). A Comparative Analysis of CFD and the Potential Flow Method for the Pure Loss of Stability in Following Waves. Journal of Marine Science and Engineering, 11(11), November 2135. DOI: 10.3390/jmse11112135.
13. Lu, J., Gu, M. Evangelos Boulougouris. (2023). Further Study on One of the Numerical Methods for Pure Loss of Stability in Stern Quartering Waves. Journal of Marine Science and Engineering, 11(2), 394. DOI: 10.3390/jmse11020394.
14. Liu, L., Yao, Ch., Feng, D., Wang, X., Yu, J., Chen, M. (2022). Numerical study of the interaction between the pure loss of stability, surf-riding, and broaching on ship capsizing. Ocean Engineering, 266(4), 112868. DOI: 10.1016/j.oceaneng.2022.112868.
15. Liu, L., Feng, D., Wang, X., Zhang, Zh., Yu, J., Chen, M. (2022). Study on extreme roll event with capsizing induced by pure loss of stability for the free-running ONR Tumblehome. Ocean Engineering, 257(4), 111656. DOI: 10.1016/j.oceaneng.2022.111656.
16. Lu, J., Gu, M. (2023). A Unified Numerical Method for Broaching and Loss of Stability in Astern Seas. Journal of Marine Science and Engineering 11(8):1555 DOI: 10.3390/jmse11081555.
17. Park, M., Kim, Y. (2024). Probabilistic estimation of directional wave spectrum using onboard measurement data. Journal of Marine Science and Technology. Vol. 29, p. 200–220 DOI: 10.1007/s00773-023-00984-z.
18. Bowker, J. (2018). Coupled dynamics of a flapping foil wave powered vessel. A thesis submitted for the degree of Doctor of Philosophy, 251 p.
19. Dirdal, J.A., Skjetne, R., Rohac, J., Fossen, T.I. (2022). Online wave direction and wave number estimation from surface vessel motions using distributed inertial measurement arrays and phase-time-path-differences. Ocean Engineering, 249(3). DOI: 10.1016/j.oceaneng.2022.110760.
20. Im, N., Lee, S. (2021). A Study on Motion Response of Small Fishing Vessels According to Various Tonnage in Regular Waves. Journal of the Korean Society of Marine Environment and Safety. 27(6):832-838. DOI: 10.7837/kosomes.2021.27.6.832.
21. Xie, Zh., Falzarano, J., Wang. H. (2020). A Framework of Numerically Evaluating a Maneuvering Vessel in Waves. Journal of Marine Science and Engineering, 8(392):392. DOI: 10.3390/jmse8060392.
22. Wang, Y., Perera, L., Batalden, B. (2023). Kinematic motion models based vessel state estimation to support advanced ship predictors. Ocean Engineering. Volume 286, Part 1, 15, 115503. DOI: 10.1016/j.oceaneng.2023.115503.
23. Araki, M., Sadat, H., Sanada, Yu., Umeda, N., Stern, F. (2019). Improved Maneuvering-Based Mathematical Model for Free-Running Ship Motions in Following Waves Using High-Fidelity CFD Results and System-Identification Technique: Risk of Capsizing. Fluid Mechanics and its Applications. DOI: 10.1007/978-3-030-00516-0_6.
24. Pipchenko, O. D. (2010). Optimization of vessel movement control in stormy conditions, PhD Thesis, Odesa National Maritime Academy.
25. Pipchenko, O. D. (2009). On the method of calculation of ship's transverse stability in regular waves, Ships and Offshore Structures, Vol.4, Issue 1, doi: 10.1080/17445300802402579.
