Arctic: ecology and economy
ISSN 2223-4594 | ISSN 2949-110X
Home Archive of journals Volume 11, No. 3, 2021 Models to predict the parameters of ship voyages in the Arctic: existing approaches and possible ways of development


JOURNAL: Volume 11, No. 3, 2021, p. 422-435

HEADING: Shipbuilding for the Arctic

AUTHORS: Tarovik, O.V.

ORGANIZATIONS: Krylov State Research Centre

DOI: 10.25283/2223-4594-2021-3-422-435

UDC: 629.5.016

The article was received on: 01.04.2021

Keywords: Arctic shipping, ice conditions, numerical methods., ice resistance, ship transit model

Bibliographic description: Tarovik, O.V. Models to predict the parameters of ship voyages in the Arctic: existing approaches and possible ways of development. Arktika: ekologiya i ekonomika. [Arctic: Ecology and Economy], 2021, vol. 11, no. 3, pp. 422-435. DOI: 10.25283/2223-4594-2021-3-422-435. (In Russian).


Any information support system for Arctic shipping requires a ship transit model as one of the key elements that allows for strategic analysis, operational planning of vessel voyages, and ice routing of a ship. At the same time, there is no single recognized approach to develop such a model, due to the complexity of ice cover in terms of its impact on shipping.

In this article, we have identified and analyzed three principal approaches to predict the parameters of vessel voyages in the Arctic. They are (1) semi-empirical models to estimate the vessel resistance in ice and then calculate propulsion performance, (2) numerical methods to model ship-ice interaction and calculate ice resistance, (3) statistical models to assess the ship speed based on regression equations or neural networks. Analysis of the strengths and weaknesses of each approach allowed us to propose a concept to develop the ship transit model for practical application.

We suggest combining the elements of different approaches, while in general the model should be based on semi-empirical methods. This is due to their computational simplicity, which is important in ice routing tasks, as well as the need for considering ice resistance along with other types of resistance. To compensate for limitations of a semi-empirical approach, we suggest several directions for further research: (1) scaling the ice resistance to obtain a strict correspondence between the calculated and field values of icebreaking capability, (2) development of a methodology to consider the influence of the season and the region of ship operation, (3) methods to estimate resistance in broken ice of different concentration and arbitrary horizontal size, (4) taking into account the direction of compression relative to the ship course, (5) development of methods to assess ice resistance during icebreaker escort operations. The area of application of statistical approaches in a joint model is to model the influence of ice melting stage, hummocking and the differences in ice conditions along the ship route and in the whole region. The article also highlights several additional issues of combining different approaches.

Finance info: The study was supported by a grant from the Russian Science Foundation entitled Technology for tactical and operational control of icebreakers and ice-class vessels under the conditions of year-round navigation along the Northern Sea Route (project No. 17-79-20162-P).


1. Timofeev O. Ya., Tarovik O. V., Topazh A. G., Mironov E. U., Frolov S. V., Buyanov A. S., Gorbachev M. A., Bengert A. A. The concept of an integrated information system for planning of fleet operation in the Arctic. Arktika: ekologiya i ekonomika. [Arctic: Ecology and Economy], 2019, no. 1 (33), pp. 129—143. DOI: 10.25283/2223-4594-2019-1-129-143. (In Russian).

2. Ionov B. P., Gramuzov E. M. Ice performance of ships. St. Petersburg, Sudostroyeniye, 2001, 512 p. (In Russian).

3. Lindqvist G. A straightforward method for calculation of ice resistance of ships. Proceedings of POAC-1989, 1989, pp. 722—735.

4. Riska K., Wilhelmson M., Englund K., Leiviska T. Performance of merchant vessels in ice in the Baltic. Research Report No 52; Helsinki Univ. of Technology. Espoo, 1997.

5. Kashtelyan V. I., Pozdnyak I. I., Ryvlin A. Ya. Ice resistance to ship movement. Leningrad, Sudostroyeniye, 1968, 238 p. (In Russian).

6. Riska K. The background of the powering requirements in the Finnish-Swedish ice class rules. Maritime Research Seminar’99, VVT Symposium 199. 2000, pp. 91—106.

7. Mellor M. Ship Resistance in Thick Brash Ice. Cold Regions Science and Technology, 1980, no. 3, pp. 305—321.

8. Valkonen J., Riska K. Assessment of the Feasibility of the Arctic Sea Transportation by using Ship Ice transit Simulation. Proceedings of OMAE-2014, 2014, Paper no. 24188.

9. Riska K., Patey M., Kishi S., Kamesaki K. Influence of ice conditions on ship transit times in ice. Proceedings of POAC-2001, 2001, p. 17.

10. Kanevskij G. I., Klubnichkin A. M., Sazonov K. E. Forecasting of propulsion performance of multi-shaft ships. St. Petersburg, Krylov State Research Centre, 2019, 160 p. (In Russian).

11. Ryvlin A. Ya., Hejsin D. E. Ice trials of ships. Leningrad, Sudostroyeniye, 1980, 208 p. (In Russian).

12. Sigrid-3: A vector archive format for sea ice charts. JCOMM Technical Report No. 23. WMO/TD-No. 1214. 24 p.

13. Erceg S., Ehlers S. Semi-empirical level ice resistance prediction methods. Ship Technology Research, 2017, 64 (1), pp. 1—14. DOI: 10.1080/09377255.2016.1277839.

14. Hu J., Zhou L. Further study on level ice resistance and channel resistance for an icebreaking vessel. Intern. J. of Naval Architecture and Ocean Engineering, 2016, 8 (2), pp. 169—176. DOI: 10.1016/j.ijnaoe.2016.01.004.

15. Kotovirta V., Jalonen R., Axell L., Riska K., Berlund R. A system for route optimization in ice-covered waters. Cold Regions Science and Technology, 2009, no. 55, pp. 52—62.

16. Tuhkuri J., Polojarvi A. A review of discrete element simulation of ice–structure interaction. Philosophical Transactions of The Royal Society. A Mathematical Physical and Engineering Sciences, 2018, n. 376. DOI: 10.1098/rsta.2017.0335.

17. Lu W., Lubbad R., Loset S., Hoyland K. Cohesive Zone Method Based Simulations of Ice Wedge Bending: a Comparative Study of Element Erosion, CEM, DEM and XFEM. Proceedings of the 21st IAHR International Symposium on Ice. [S. l.], 2012, pp. 920—938.

18. Yu B., Wu W., Xu N., Yue Q., Liu S. Numerical simulation of dynamic ice force on conical structure. Proceedings of POAC-07, 2007, pp. 277—285.

19. Di S., Ji S., Yue Q., Liu S. Ice Loads on Conical Offshore Structures Based on Discrete Element Simulation. Proceedings of the 21st IAHR International Symposium on Ice, 2012, p. 853—863.

20. Su B., Riska K., Moan T. A numerical method for the prediction of ship performance in level ice. Cold Regions Science and Technology, 2010, no. 60, pp. 177—188. DOI: 10.1016/j.coldregions.2009.11.006.

21. Lubbad R., Loset S. A Numerical Model for Real-Time Simulation of Ship–Ice Interaction. Cold Regions Science and Technology, 2011, 65 (2), pp. 111—127. DOI: 10.1016/j.coldregions.2010.09.004.

22. Li F., Kotilainen M., Goerlandt F., Kujala P. An extended ice failure model to improve the fidelity of icebreaking pattern in numerical simulation of ship performance in level ice. Ocean Engineering, 2019, no. 176, pp. 169—183. DOI: 10.1016/j.oceaneng.2019.02.051.

23. Valanto P. The resistance of ships in level ice. Transactions of the Society of Naval Architects and Marine Engineers, 2001, no. 109, pp. 53—83.

24. Sazonov K. E. Theoretical foundations of ship navigation in ice. St. Petersburg, Krylov State Research Centre, 2010, 273 p. (In Russian).

25. Li F., Goerlandt F., Kujala P. Numerical simulation of ship performance in level ice: A framework and a model. Applied Ocean Research, 2020, no. 102. DOI: 10.1016/j.apor.2020.102288.

26. Huang L., Li M., Igrec B., Cardiff P., Stagonas D., Thomas G. Simulation of a ship advancing in floating ice floes. Proceedings of POAC-2019, 2019, 13 p.

27. Su B., Riska K., Moan T., Berg T. E. Full-scale and model-scale simulations of a double acting intervention vessel operating in level ice. Proceedings of 21st IAHR International Symposium on Ice. [S. l.], 2012, pp. 1058—1068.

28. Buzuev A. Ya., Fedyakov V. E. Variability of ice conditions on ship way. Meteorologiya i gidrologiya, 1981, no. 2, pp. 69—76. (In Russian).

29. Gordienko P. A., Buzuev A. Ya., Sergeev G. N. Study of sea ice cover as a shipping environment. Problemy Arktiki i Antarktiki, 1967, no. 27, pp. 93—104. (In Russian).

30. Brovin A. I., Klyachkin S. V., Bhat S. U. Application of an empirical-statistical model of ship motion in ice to new types of icebreakers and ships. Proceedings of OMAE-1997, 1997, vol. IV, pp. 43—49.

31. Sergeev G. N. Using data on ice thickness to assess the passability of ice routes by ships. Problemy Arktiki i Antarktiki, 1978, no. 54, pp. 52—56. (In Russian).

32. Sergeev G. N., Khromov Yu. N. Hummocking and ice resistance to vessel movement. Meteorologi i gidrologiya, 1980, no. 10, pp. 100—104. (In Russian).

33. Buzuev A. Ya., Fedyakov V. E. Comprehensive accounting of the characteristics of ice state when developing recommendations for shipping. Issues of increasing the strength and reliability of sea and port facilities. Collection of scientific papers. Moscow, Transport, 1983, pp. 89—97. (In Russian).

34. Frolov S. V. Orientation of the leads and cracks in the ice cover relatively to direction of the ship movement is the most important characteristic of ice navigation in the Arctic basin. Problemy Arktiki i Antarktiki, 2013, no. 3 (97), pp. 35—45. (In Russian).

35. Tretyakov V. Yu., Sarafanov M. I., Fedyakov V. E., Frolov S. V. From Sabetta to the Kara Gates: Methodology for calculating the speed of a vessel in ice cover as an integral indicator of ice navigation conditions. Neftegaz.ru, 2020, no. 8 (104), pp. 46—50. (In Russian).

36. Buzuev A. Ya., Brovin A. I., Kolbatov P. V., Fedyakov V. E. The current state of foreign and domestic research on ice cover as a shipping environment. Obninsk, Inform. tsentr VNIIGMI-MTSD, 1982, 53 p. (In Russian).

37. Lensu M., Goerlandt F. Big maritime data for the Baltic Sea with a focus on the winter navigation system. Marine Policy, 2019, no. 104, pp. 53—65. DOI: 10.1016/j.marpol.2019.02.038.

38. Kim E., Smestad B. B., Asbjornslett B. E. Predicting ship speeds in the Arctic using deep learning on historical AIS data. Proceedings of ISOPE-2020, 2020, pp. 622—626.

39. Montewka J., Goerlandt F., Kujala P., Lensu M. Towards probabilistic models for the prediction of a ship performance in dynamic ice. Cold Regions Science and Technology, 2015, no. 112, pp. 14—28. DOI: 10.1016/j.coldregions.2014.12.009.

40. Li F., Montewka J., Goerlandt F., Kujala P. A probabilistic model of ship performance in ice based on full-scale data. Proceedings of ICTIS-2017, 2017. DOI: 10.1109/ICTIS.2017.8047852.

41. Fu Sh., Zhang D., Montewka J., Yan X., Zio E. Towards a probabilistic model for predicting ship besetting in ice in Arctic waters. Reliability Engineering and System Safety, 2016, no. 155, pp. 124—136. DOI: 10.1016/j.ress.2016.06.010.

42. Vilde O. Captain of the Arctic oil. Sibirskaya neft’, 2019, no. 159, pp. 30—35. (In Russian).

43. Topaj A. G., Tarovik O. V., Bakharev A. A., Kondratenko A. A. Optimal ice routing of a ship with icebreaker assistance. Applied Ocean Research, 2019, vol. 86, pp. 177—187. DOI: 10.1016/j.apor.2019.02.021.

44. Babich N. G. Choosing a navigation route in ice and evaluating the effectiveness of using ice navigational information. Zemlya iz kosmosa: naiboleye effektivnyye resheniya, 2011, no. 10, pp. 28—33. (In Russian).

45. Sazonov K. E., Dobrodeev A. A. Ice performance of high-tonnage vessels. Monograph. St. Petersburg, Krylov. gos. nauch. tsentr, 2017, 122 p. (In Russian).

Download »

© 2011-2023 Arctic: ecology and economy
DOI 10.25283/2223-4594