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Evaluation of Transit Simulation for Independent Navigation in Ice

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Evaluation of Transit Simulation for Independent Navigation in Ice Proceedings of the Thirty-first (2021) International Ocean and Polar Engineering Conference www.isope.org Rhodes, Greece, June 20 – 25, 2021 Copyright © 2021 by the International Society of Offshore and Polar Engineers (ISOPE) ISBN 978-1-880653-82-1; ISSN 1098-6189 Evaluation of Transit Simulation for Independent Navigation in Ice Sabina Idrissova, Alexey Shtrek, Luigi Portunato, Sami Saarinen, Cayetana Ruiz de Almirón de Andrés Aker Arctic Technology Inc. Helsinki, Finland ABSTRACT R&D – Research and Development This paper presents a transit simulation tool developed by Aker Arctic INTRODUCTION and a comparison of the transit simulation results with the data derived from the Automatic Identification System (AIS). Case study for the Maritime activity in the Arctic is on the increase, driven by the simulation covers a route from Ob bay to the Barents Sea with extraction of Arctic natural resources, trans-Arctic shipping, and Arctic independent navigation of “Yamalmax” LNG carriers. Three types of tourism. To ensure safe and sustainable operations in ice-covered winter severity are considered along with the simulation of level ice waters a complex of studies must be performed. One of the basic and ice ridges. The results are summarized in terms of speed and time studies conducted during the feasibility phase is a transit study. Transit spent in the voyage and compared with corresponding measurements study is needed to assess shipping logistics through ice-covered waters, from the AIS database. As a result, advantages, limitations, and future identifying roundtrip times, defining fleet size, need for icebreaker developments of the transit simulation tool are also discussed. assistance and calculating transportation cost. KEY WORDS: transit simulation; navigation in ice; LNG carrier; The most important part of transit analysis for ice-going vessels is the Arctic; ice conditions; ice resistance; AIS database. calculation of the parameters of the ship's movement (speed, power) in ice conditions. Models for assessing the ship resistance in ice, for ABBREVIATIONS instance, those described by (Lindqvist 1989; Li, et al., 2018; Kuuliala, et al., 2017) are key components to predict those parameters. These LNG – Liquified natural gas models are used for calculations of ship performance, which can be AIS – Automatic Identification System assessed in two general ways (Valtonen & Riska, 2014). First is by M – Mild winter simulating ship transit through the ice using the equivalent ice A – Average winter thickness concept where the ice is converted into level ice of certain S – Severe winter (equivalent) ice thickness (Milaković, et al., 2019). The ship speed is NSR – Northern Sea Route then calculated in this equivalent ice thickness. The second alternative CM – Christophe de Margerie way is to calculate the ship speed in the generated ice profile. In this FL – Fedor Litke case, several assumptions concerning ice conditions must be made, and ET – Eduard Toll the outcome of the simulation is the speed variation of the ship. The NZ – Nikolay Zubov second approach will be presented in this paper as a part of the Aker VR – Vladimir Rusanov Arctic Transit Simulation Tool. RS – Rudolf Samoylovich VZ – Vladimir Vize The outcome of the transit study can cover a variety of solutions as GB – Georgiy Brusilov presented before. However, specific ships characteristics, the BD – Boris Davydov uncertainty of ice and environmental conditions and assumptions NY – Nikolay Yevgenov applied during the transit study can create challenges for such solutions VV – Vladimir Voronin (Li, et al., 2018). Therefore, calibration of transit simulation methods is NU – Nikolay Urvantsev needed. Such calibration can be assessed either based on the experience YG – Yakov Gakkel or based on the available full-scale data. Thus, this paper covers two 1011.
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