Skip to main content
Log in

Identification of ship motion performance of coupled heave and pitch using experimental irregular time-series data

  • Original article
  • Published:
Journal of Marine Science and Technology Aims and scope Submit manuscript

Abstract

We propose to estimate parameters of the system model based on the equation of motion using the time histories of the wave elevation and the ship’s heave and pitch motions to evaluate hydrodynamic force coefficients directly. Two types of mathematical models are formulated considering the frequency dependence of the added mass and damping coefficients. Then, these parameters are estimated from the time-series data by the ensemble Kalman filter. It is possible to evaluate hydrodynamic forces acting on a ship hull and wave-induced ship’s motions using estimated parameters. This paper reports on the verification of the proposed parameter estimation method using the experimental data measured in a tank test.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Tasai F, Takagi M (1969) Theory and calculation of ship’s motion in regular waves, Symposium on Seaworthiness of Ships, The Japan Society of Naval Architects, 1–52 (in Japanese)

  2. Salvesen N, Tuck EO, Faltinsen OM (1970) ship’s motions and sea load. Trans SNAME 78:250–287

    Google Scholar 

  3. Kashiwagi M (1995) Prediction of surge and its effect on added resistance by means of the enhanced unified theory. In Transactions of the West-Japan Society of Naval Architects 89 (pp. 77–89). The Japan Society of Naval Architects And Ocean Engineers

  4. Cummins WE (1962) The impulse response function and ship’s motions. David Taylor Model Basin Washington DC

  5. Kotik J, Mangulis V (1962) On the Kramers–Kroning relations for ship’s motions. Int Shipbuilding Progress 9(97):361–368

    Article  Google Scholar 

  6. Oglivie TF (1964) Recent progress toward the understanding and prediction of ship’s motions, In 5th ONR Symposium on Naval Hydrodynamics

  7. Van Oortmerssen G (1976) The motions of a moored ship in waves, H. Veeman en Zonen nv

  8. Fonseca N, Soares CG (1998) Time-domain analysis of large-amplitude vertical ship’s motions and wave loads. J Ship Res 42(02):139–153

    Article  Google Scholar 

  9. Fonseca N, Soares CG (2002) Comparison of numerical and experimental results of nonlinear wave-induced vertical ship’s motions and loads. J Marine Sci Technol 6(4):193–204

    Article  Google Scholar 

  10. Fonseca N, Soares CG (2005) Comparison between experimental and numerical results of the nonlinear vertical ship’s motions and loads on a containership in regular waves. Int Shipbuilding Progress 52(1):57–89

    Google Scholar 

  11. Vásquez G, Fonseca N, Soares CG (2015) Experimental and numerical study of the vertical motions of a bulk carrier and a Ro Ro ship in extreme waves. J Ocean Eng Marine Energy 1(3):237–253

    Article  Google Scholar 

  12. Ma S, Wang R, Zhang J, Duan WY, Ertekin RC, Chen XB (2016) Consistent formulation of ship’s motions in time-domain simulations by use of the results of the strip theory. Ship Technol Res 63(3):146–158

    Article  Google Scholar 

  13. Yoshida H, Takagi K, Ikebuchi T, Sugimoto K (2004) A Study on Practical Large Amplitude ship’s motion Analysis 24:89–100 ((in Japanese))

  14. Begovic E, Bertorello C, Cakici F, Kahramanoglu E, Rinauro B (2020) Vertical motions prediction in irregular waves using a time domain approach for hard Chine displacement hull. J Mar Sci Eng 8(5):337

    Article  Google Scholar 

  15. Kim Y, Lee J H, Liu Y, Nam Y, Lee JH, Yang H (2021) Application of Digitalization Scheme for Ship Performance Prediction in Waves: Combination of Physics-Based Simulation and Digital Technique, International Workshop on Water Waves and Floating Bodies, http://www.iwwwfb.org/Abstracts/iwwwfb36/IWWWFB36GLOBAL018.pdf

  16. Piscopo V, Scamardella A, Gaglione S (2020) A new wave spectrum resembling procedure based on ship’s motion analysis. Ocean Eng 201:107137

    Article  Google Scholar 

  17. Fossen TI (2002) Marine Control Systems Guidance. Navigation, and Control of Ships, Rigs and Underwater Vehicles, Marine Cybernetics, Trondheim

  18. Kashiwagi M (2004) Transient responses of a VLFS during landing and take-off of an airplane. J Marine Sci Technol 9(1):14–23

    Article  Google Scholar 

  19. Taghipour R, Perez T, Moan T (2008) Hybrid frequency-time domain models for dynamic response analysis of marine structures. Ocean Eng 35(7):685–705

    Article  Google Scholar 

  20. Falnes J (1995) On non-causal impulse response functions related to propagating water waves. Appl Ocean Res 17(6):379–389

    Article  Google Scholar 

  21. Yu Z, Falnes J (1995) State-space modelling of a vertical cylinder in heave. Appl Ocean Res 17(5):265–275

    Article  Google Scholar 

  22. Kristiansen E, Egeland O (2003) Frequency-dependent added mass in models for controller design for wave motion damping. IFAC Proc 36(21):67–72

    Google Scholar 

  23. Kristiansen E, Hjulstad Å, Egeland O (2005) State-space representation of radiation forces in time-domain vessel models. Ocean Eng 32(17–18):2195–2216

    Article  Google Scholar 

  24. Perez T, Smogeli O, Fossen T, Sorensen AJ (2006) An overview of the marine systems simulator (MSS): a simulink toolbox for marine control systems. Model Identification Control 27(4):259–275

    Article  Google Scholar 

  25. Kitagawa G (1998) A self-organizing state-space model. J Am Stat Assoc 1203–1215

  26. Evensen G (1994) Sequential data assimilation with a nonlinear quasi geostrophic model using Monte Carlo methods to forecast error statistics. J Geophys Res 99(C5):10143–10162

    Article  Google Scholar 

  27. Evensen G (2003) The ensemble Kalman filter: Theoretical formulation and practical implementation. Ocean Dyn 53(4):343–367

    Article  Google Scholar 

  28. King BK, Beck RF, Magee AR (1988) Seakeeping calculations with forward speed using time domain analysis. In Proc. 17th Symp. on Naval Hydrodynamics, 577–596

  29. Kalman RE (1960) A new approach to linear filtering and prediction problems. J Fluids Eng 82(1):35–45

    MathSciNet  Google Scholar 

  30. Weahausen JV (1967) Initial-value problem for the motion in an undulating sea of a body with fixed equilibrium position. J Eng Math 1(1):1–17

    Article  Google Scholar 

  31. Takagi M, Saito K (1981) On the description of non-harmonic wave problems in the frequency domain (1st Report)—memory effect function of a two-dimensional body -. J Kansai Soc Naval Architects 182:39–48 ((in Japanese))

    Google Scholar 

  32. Saito K, Higashi H (1992) Time domain analysis of ship responses in waves—heave and pitch motions in longitudinal waves-. J Soc Naval Architects Jpn 172:9–16 ((in Japanese))

    Article  Google Scholar 

  33. Kashiwagi M (2000) A time-domain mode-expansion method for calculating transient elastic responses of a pontoon -type VLFS. J Mar Sci Technol 5(2):89–100

    Article  Google Scholar 

  34. The Research Initiative on Oceangoing Ships (http://www.rios.eng.osaka-u.ac.jp/)

  35. Stansberg CT, Contento G, Hong SW, Irani M, Ishida S, Mercier R, ... Kriebel D (2002) The specialist committee on waves final report and recommendations to the 23rd ITTC. Proceedings of the 23rd ITTC, 2, 505–551

  36. Nakano S, Ueno G, Nakamura K, Higuchi T (2008) Marginal particle filter and its properties. Stat Math 56(2):225–234 ((in Japanese))

    Google Scholar 

  37. Nakano S, Ueno G, Higuchi T (2007) Merging particle filter for sequential data assimilation. Nonlinear Process Geophys 14(4):395–408

    Article  Google Scholar 

  38. Iwashita H, Kashiwagi M, Ito Y, Seki Y (2016) Calculation of Ship Seakeeping in Low-Speed/Low-Frequency Range by Frequency-Doamin Rankine Panel Methods. J Soc Naval Architects Jpn 24:129–146 ((in Japanese))

    Google Scholar 

  39. Akaike H (1971) Autoregressive model fitting for control. Ann Inst Stat Math 23:163–180

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Takaaki Hanaki.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hanaki, T., Minoura, M. Identification of ship motion performance of coupled heave and pitch using experimental irregular time-series data. J Mar Sci Technol 27, 971–988 (2022). https://doi.org/10.1007/s00773-022-00887-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00773-022-00887-5

Keywords

Navigation