Е-Публикации
Технически университет - София

Abstract: The ice presence significantly complicates shipping in cold regions during winter or even year-round in some polar areas. Climate change contributes to a warmer climate, resulting in more favorable ice conditions for navigation and attracting more vessels in cold regions. Efficient ice navigation requires a systemic approach, allowing for planning and analyzing future navigation under complex and changing circumstances. We developed an agent-based simulation tool for the analysis and design of sustainable winter navigation systems, considering the ice conditions, the technical parameters of ships in the traffic, parameters of ship voyages, established maritime routes in the region, and supporting infrastructure (e.g., availability and technical parameters of icebreakers, icebreaking assistance, and ice routing provided by the authorities). This paper presents an overview of the applications of our decision support tool for different regions of the Baltic Sea (e.g., modeling the Finnish-Swedish winter navigation system in the Gulf of Bothnia and winter navigation in the Estonian waters), supporting sustainable, safe, and cost-efficient shipping in ice.

References

1. Kondratenko AA Kujala P Hirdaris SE Holistic and sustainable design optimization of Arctic ships Ocean Eng. 2023 275 10.1016/j.oceaneng.2023.114095 114095
2. Kondratenko, A.A., Bergström, M., Suominen, M., Kujala, P.: An Artificial Bee Colony optimization-based approach for sizing and composition of Arctic offshore drilling support fleets considering cost-efficiency. Ship Technol. Res. 69(2), Art. no. 2 (2022)
3. Kujala P, et al. Review of risk-based design for ice-class ships Mar. Struct. 2019 63 181 195 10.1016/j.marstruc.2018.09.008
4. Riska K Kämäräinen J A review of ice loading and the evolution of the Finnish-Swedish ice class rules Trans. Soc. Nav. Arch. Mar. Eng. 2011 119 265 298
5. Finnish Transport Infrastructure Agency: Finland’s Winter Navigation. Instructions for winter navigation operators. Helsinki (2023)
6. Topaj, A., Bakharev, A., Tarovik, O.: Comparative analysis of uncertainty factors in the problem of optimal ice routing. In: Proceedings of the 26th International Conference on Port and Ocean Engineering under Arctic Conditions, Moscow (2021)
7. Topaj AG Tarovik OV Bakharev AA Kondratenko AA Optimal ice routing of a ship with icebreaker assistance Appl. Ocean Res. 2019 86 177 187 10.1016/j.apor.2019.02.021
8. Kondratenko AA Kulkarni K Li F Musharraf M Hirdaris S Kujala P Decarbonizing shipping in ice by intelligent icebreaking assistance: a case study of the Finnish-Swedish winter navigation system Ocean Eng. 2023 286 10.1016/j.oceaneng.2023.115652 115652
9. Kulkarni K Li F Kondratenko AA Kujala P A voyage-level ship performance modelling approach for the simulation of the Finnish-Swedish winter navigation system Ocean Eng. 2024 295 10.1016/j.oceaneng.2024.116997 116997
10. Kulkarni, K., Kujala, P., Musharraf, M., Rainio, I.: Simulation tool for winter navigation decision support in the Baltic Sea. Appl. Sci. 12(15), Art. no. 15 (2022). https://doi.org/10.3390/app12157568
11. Lindeberg, M., Kujala, P., Sormunen, O.V., Karjalainen, M., Toivola, J.: Simulation model of the Finnish winter navigation system. In: Proceedings of the IMDC2018—International Marine Design Conference 2018, Espoo, Finland (2018)
12. Lindeberg M Kujala P Toivola J Niemelä H Real-time winter traffic simulation tool—based on a deterministic model Zeszyty Naukowe Akademii Morskiej w Szczecinie 2015 42 114 118 124
13. Lu, L., Kondratenko, A., Kulkarni, K., Li, F., Kujala, P., Musharraf, M.: An investigation of winter navigation and icebreaker needs in the ice-infested water: the Gulf of Finland and the Gulf of Riga. In: Proceedings of the ASME 2024 43rd International Conference on Ocean, Offshore and Arctic Engineering, American Society of Mechanical Engineers Digital Collection (2024). https://doi.org/10.1115/OMAE2024-127955
14. Garifullin, M., Borshchev, A., Popkov, T.: Using AnyLogic and agent-based approach to model consumer market. In: Proceedings of the EUROSIM 2007, Ljubljana, Slovenia (2007)
15. Tarovik O Eremenko D Topaj A A benchmark study on ship speed prediction models in Arctic conditions: machine learning, process-based and hybrid approaches Ocean Eng. 2024 311 10.1016/j.oceaneng.2024.118884 118884
16. Tarovik O Yakimov V Dobrodeev A Li F Influence of seasonal and regional variation of ice properties on ship performance in the Arctic Ocean Eng. 2022 257 10.1016/j.oceaneng.2022.111563 111563
17. FMI, Index of marine-observations, products, ice-charts. https://cdn.fmi.fi/marine-observations/products/ice-charts . Accessed 21 Jan 2025
18. Liu C Musharraf M Li F Kujala P A data mining method for automatic identification and analysis of icebreaker assistance operation in ice-covered waters Ocean Eng. 2022 266 10.1016/j.oceaneng.2022.112914 112914

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