Abstract

This paper presents a transit simulation tool developed by Aker Arctic and a comparison of the transit simulation results with the data derived from the Automatic Identification System (AIS). Case study for the simulation covers a route from Ob bay to the Barents Sea with independent navigation of "Yamalmax" LNG carriers. Three types of winter severity are considered along with the simulation of level ice and ice ridges. The results are summarized in terms of speed and time spent in the voyage and compared with corresponding measurements from the AIS database. As a result, advantages, limitations, and future developments of the transit simulation tool are also discussed.

Introduction

Maritime activity in the Arctic is on the increase, driven by the extraction of Arctic natural resources, trans-Arctic shipping, and Arctic tourism. To ensure safe and sustainable operations in ice-covered waters a complex of studies must be performed. One of the basic studies conducted during the feasibility phase is a transit study. Transit study is needed to assess shipping logistics through ice-covered waters, identifying roundtrip times, defining fleet size, need for icebreaker assistance and calculating transportation cost.

The most important part of transit analysis for ice-going vessels is the calculation of the parameters of the ship's movement (speed, power) in ice conditions. Models for assessing the ship resistance in ice, for instance, those described by (Lindqvist 1989; Li, et al., 2018; Kuuliala, et al., 2017) are key components to predict those parameters. These models are used for calculations of ship performance, which can be assessed in two general ways (Valtonen & Riska, 2014). First is by simulating ship transit through the ice using the equivalent ice thickness concept where the ice is converted into level ice of certain (equivalent) ice thickness (Milaković, et al., 2019). The ship speed is then calculated in this equivalent ice thickness. The second alternative way is to calculate the ship speed in the generated ice profile. In this case, several assumptions concerning ice conditions must be made, and the outcome of the simulation is the speed variation of the ship. The second approach will be presented in this paper as a part of the Aker Arctic Transit Simulation Tool.

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