Journal of Marine Science and Technology

, Volume 17, Issue 1, pp 59–67 | Cite as

Optimal ship tracking on a navigation route between two ports: a hydrodynamics approach

  • J. K. Panigrahi
  • C. P. Padhy
  • D. Sen
  • J. Swain
  • O. Larsen
Original Article
First Online:
Received:
Accepted:

Abstract

The optimal trajectory from Calcutta port to Mumbai port is charted for a tanker transshipping from the East coast to the West coast of India during rough weather. Rough weather is simulated over Indian seas using the state-of-the-art WAM numerical wave model (WAMDI Group in J Phys Oceanogr 18:1775–1810, 1988), assimilating satellite (IRS-P4) wind fields. These simulated wave fields and two-dimensional (2D) directional wave spectrum are an absolute representation of the irregular seaway. Hence, the same for the monsoon month of August 2000 formed the input basis for this study. Loss of ship speed due to the wave field (i.e., nonlinear motion of the tanker in waves) and associated sea-keeping characteristics in the seaway are estimated (Bhattacharya in Dynamics of marine vehicles, Wiley, New York, 1978). The approach adopted in this paper is unique in that it takes into account both voluntary and involuntary speed reductions of the ship. It helps in ship tracking by the optimum route using inverse velocity as the weight function for the path in an efficient way. Dijkstra’s algorithm [Numer Math 1(3):269–271, 1959] is applied in an iterative manner for determining the optimum track. The optimum track information has broad scope for use in modern shipping industry for obtaining safe and least-time routing by avoiding schedule delays with economic fuel consumption.

Keywords

Ship behavior Surface waves Ship routing WAM model OTSR 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

The authors are thankful to Head, Department of Ocean Engineering and Naval Architecture, IIT, Kharagpur, India and Director, DHI-NTU Water & Environment Research Centre and Education Hub, Singapore, for extending support and encouragement for this work. This study is a collaboration of Ph.D. works of Dr. Chinmaya P. Padhy and Dr. Jitendra K. Panigrahi under the supervision of Prof. D. Sen and Dr. J. Swain, respectively.

References

  1. 1.
    WAMDI Group (1988) The WAM model—a third generation ocean wave prediction model. J Phys Oceanogr 18:1775–1810CrossRefGoogle Scholar
  2. 2.
    Bhattacharya R (1978) Dynamics of marine vehicles. Wiley, New York, p 508Google Scholar
  3. 3.
    Dijkstra EW (1959) Note on two problems in connection with graphs (spanning tree, shortest path). Numer Math 1(3):269–271MathSciNetMATHCrossRefGoogle Scholar
  4. 4.
    Marks W, Goodman TR, Pierson WJ, Tick LJ, Vassilopoulos LA (1968) An automated system for optimum ship routing. Trans Soc Nav Archit Mar Eng 76:22–55Google Scholar
  5. 5.
    Swain J (1997) Simulation of wave climate for Indian seas. Ph.D. thesis, Cochin University of Science and Technology, IndiaGoogle Scholar
  6. 6.
    Hanssen GL, James RW (1960) Optimum ship routing. J Inst Navig 10(3):253–272Google Scholar
  7. 7.
    Haltiner GJ, Hamilton HD, Arnason G (1962) Minimal time ship routing. J Appl Meteorol 1:1–7CrossRefGoogle Scholar
  8. 8.
    Faulkner FD (1963) Numerical methods for determining optimum ship routes. J Inst Navig 10(4):351–367MathSciNetGoogle Scholar
  9. 9.
    Zoppoli R (1972) Minimum-time routing as an N-stage decision process. J Appl Meteorol 11:429–435CrossRefGoogle Scholar
  10. 10.
    Mitchell JSB, Papadimitriou CH (1991) The weighted region problem: finding shortest paths through a weighted planar subdivision. J Assoc Comput Math 38(1):18–73MathSciNetMATHCrossRefGoogle Scholar
  11. 11.
    Panigrahi JK, Umesh PA (2008) Minimal time ship routing using IRS-P4 (MSMR) analysed wind fields. Mar Geod 31:39–48CrossRefGoogle Scholar
  12. 12.
    Anel AM (2005) Network shortest path application for optimum track ship routing. M.S. thesis, Naval Postgraduate School, Monterey, CA. Report No. A106534, p 93Google Scholar
  13. 13.
    Bekker JF, Schmid JP (2006) Planning the safe transit of a ship through a mapped minefield. J Oper Res Soc S Afr 22(1):1–18Google Scholar
  14. 14.
    Bhatia RC (2001) Validation of water vapour and wind speed products derived from MSMR payload onboard IRS-P4 Satellite and meteorological applications of data products. In: Proceedings of Megha-Tropiques 2nd scientific workshop. Directeur de la Publication, Remy Roca, 2–6 July 2001, pp 1–6Google Scholar
  15. 15.
    Lorenc AC (1986) Analysis methods for numerical weather prediction. Q J R Meteorol Soc 112:1177–1194CrossRefGoogle Scholar
  16. 16.
    Kamineni R, Rizvi SRH, Kar SC, Mohanty UC, Paliwal RK (2002) Assimilation of IRS-P4 (MSMR) meteorological data in the NCMRWF global data assimilation system. In: Proceedings of Indian Academy of Science (Earth and Planetary Science). 111(3):351–364Google Scholar
  17. 17.
    Arrow KJ (1949) On the use of winds in flight planning. J Meteorol 6:150–159CrossRefGoogle Scholar
  18. 18.
    Komen GJ, Cavaleri L, Donelan M, Hasselmann K, Hasselmann S, Janssen PAEM (1994) Dynamics and modelling of ocean waves. Cambridge University Press, UKMATHCrossRefGoogle Scholar
  19. 19.
    Swain J, Panigrahi JK, Vijayakumar D, Venkitachalam NRV (2003) Performance of 3g-WAM using IRS-P4 winds for its operational implementation in the Indian Ocean. In: Proceedings of the symposium on microwave remote sensing applications. CSRE IITB, India, p 1Google Scholar
  20. 20.
    Hasselmann K, Barnett TP, Bouws E, Carlson H, Cartwright DE, Enke K, Ewing JA, Gienapp H, Hasselmann DE, Kruseman P, Meerburg A, Muller P, Olbers DJ, Riehter K, Sell W, Walden H (1973) Measurement of wind-wave growth and swell decay during the joint North Sea Wave Project (JONSWAP). Deutsche Hydrographische Zeitschrift A8(12)Google Scholar
  21. 21.
    Panigrahi JK (2007) Wind induced surface gravity waves in the north Indian Ocean and their potential applications. Ph.D. thesis, Berhampur University, India, p 91Google Scholar
  22. 22.
    Panigrahi JK, Swain J (2010) Numerical simulation and validation of deepwater spectral wind-waves. Mar Geod 33:39–52CrossRefGoogle Scholar
  23. 23.
    Bhatt V, Sarkar A, Kumar R, Basu S, Agarwal VK (2004) Impact of Oceansat-I MSMR data on analyzed oceanic winds and wave predictions. Ocean Eng 31(17):2283–2294CrossRefGoogle Scholar
  24. 24.
    Clarkson Registrar (2006) Bharat Book Bureau CD. Standard editionGoogle Scholar
  25. 25.
    (1970) Admiralty charts and publications. Routing chart Indian Ocean. UK Hydrographic Office, TauntonGoogle Scholar
  26. 26.
    Taha H (2002) Operations research: an introduction, 7th edn. Prentice Hall, New Jersey, p 222Google Scholar
  27. 27.
    Hastenrath S, Lamb PJ (1979) Surface climate and atmospheric circulation. Climatic atlas of the Indian Ocean. Part-I. The University of Wisconsin Press, USAGoogle Scholar
  28. 28.
    Young IR, Holland GJ (1996) Atlas of the oceans: wind and wave climate. Pergamon/Elsevier Science, USA, p 1Google Scholar

Copyright information

© JASNAOE 2011

Authors and Affiliations

  • J. K. Panigrahi
    • 1
  • C. P. Padhy
    • 2
  • D. Sen
    • 2
  • J. Swain
    • 3
  • O. Larsen
    • 1
  1. 1.DHI-NTU Research Centre, DHI Water and EnvironmentSingaporeSingapore
  2. 2.Department of Ocean Engineering and Naval ArchitectureIndian Institute of TechnologyKharagpurIndia
  3. 3.Naval Physical and Oceanographic LaboratoryKochiIndia

Personalised recommendations