Banner

Overview of the project

Background:

A major safety-related issue for the maritime activities and shipping in the Norwegian Arctic waters is the accumulation of sea spray ice on vessels, threatening the safety of vessel crew, onboard operations, and the performance of safety-critical apparatus (e.g., firefighting and lifesaving apparatus, rescue boats). In some extreme cases, sea spray icing leads to vessel instability, vessel capsizing, and thus loss of life. Loss of “Tradewind” in 2002, “Hunter” in 2007, in Alaska, the loss of the “Destination” fishing vessel in January 2017, and ONEGA vessel in 2020, are examples of such major risks.

To manage the risks associated with sailing in Arctic waters, the shipping industry has developed and implemented winterization measures (i.e., anti-icing and mechanical/electrical de-icing techniques), for vessels to reduce such risks. A more sustainable design and operation of such measures relies on more reliable spray icing models are of crucial importance. Although some researchers have developed models for estimating icing rate, model verification and the dependency of icing on oceanographic and meteorological conditions, vessel characteristics, etc., make any icing modelling complex. In addition, the maritime industry has also focused on developing organisational barriers and improving regulatory frameworks such as DNV-GL winterisation standard and IMO’s Polar Code, which are mainly technical instruments, and their concern is predominantly on establishing requirements for suitable construction for winterised vessels. Hence, the available regulatory frameworks do not adequately meet all the considerations of various safety and environmental factors and how they impact the safety culture, risk perception, risk acceptance criteria, and situational awareness of the seafarers. These will consequently alter our views on risk, and this impacts our decision-making process during emergency situations.

While there have been several cases of vessel capsize due to spray icing, there is no database of near-misses and vessel encounters with icing storms that can be used for performing risk assessments and generating risk-informed decision-making insights.

Nowadays, in the maritime domain professional vessels are equipped with the Automatic Identification System (AIS) that broadcasts the vessel’s status that consists of both vessel information (e.g., identification numbers, a name, dimensions, and a type) and trajectory information (e.g., position, time, velocity, course, destination, navigational status, etc.). Historical AIS data provide insight into historical ship behaviour that can be utilised to generate knowledge on maritime traffic patterns. In this regard, AIS data have been used in ship collision risk assessment studies by employing machine-learning techniques for trajectory prediction. Some dynamic risk models have also been developed by use of Bayesian Networks for ship collision risk assessment. However, there is no research available on the use of AIS data applied to spray icing risk assessment and risk-informed decision making in the Arctic waters.

Project Goal:

The main goal of this project is to propose a modelling framework for making informed decisions with regards to spray icing risks in the Norwegian Arctic waters by leveraging historical AIS data, employing spray icing estimation model, and integrating field knowledge in fishery industry, while considering the uncertainties related to the meteorological and oceanographic conditions.

In particular, the objectives of this project are:

  • Map out the field experience and exiting knowledge on maritime risk perception, risk acceptance criteria, and safety culture among the seafarers.
  • Analyse the historical vessel AIS data by employing machine-learning algorithms to develop statistical models for studying the operational decisions that can be made during icing storms
  • Develop a risk-informed decision-making framework in relation the risk of spray icing in the Norwegian Arctic waters

Work Packages:

WP1– Mapping out the operational experience on navigation in the Norwegian Arctic waters: We analyse and document available field experience about making operational decisions during rough weather conditions and icing storms by conducting individual/focus group interviews with seafarers. We focus on risk perception, safety culture, and their internal/external contributing factors so as to generate a thorough understanding about on-board decision-making mechanisms and situational awareness during icing storms. WP1 activities include:

  • Task 1-1– Analyse and document available field experience and knowledge on sea spray icing related decisions via conducting individual/focus group interviews
  • Task 1-2– Develop knowledge on risk perception, risk understanding, safety culture and their contributing factors in relation to the spray icing risks

WP2– AIS data mining: In this WP, clustering techniques will be applied to historical AIS data to model the historical ship behaviour in certain regions corresponding to certain meteorological and oceanographic conditions. During this process we find anomalies of ship behaviour that will be integrated with meteorological/oceanographic parameters and the climatology of spray icing, and will be further refined by integrating operational and field knowledge on safe navigation in the Arctic waters. By employing this approach, we extract the operational parameters and decision variables for safe navigations in the Arctic waters in view of spray icing risks.

  • Task 2-1– AIS Data collection and cleaning
  • Task 2-2– Ship behaviour anomaly detection
  • Task 2-3– Integration of meteorological and oceanographic data, spray icing models, and seafarers’ field knowledge in anomaly detection models to extract information on operational decisions made in view of spray icing

WP3– Risk-informed decision-making framework: This WP integrates WP1 and WP2 to develop a framework for making risk-informed decisions concerning navigation in the Arctic waters exposed to sea spray icing risks. The framework will be shared with stakeholders during workshops and reference group meetings, to incorporate their feedback. It will also be tested against some pre-established spray icing-related scenarios during tabletop exercises with stakeholders. WP3 activities include

  • Task 3-1– Integrate results from WP1 and WP2 to develop risk-informed decision-making framework
  • Task 3-2– Introduce and test the framework during tabletop exercises
  • Task 3-3– Incorporate stakeholders’ feedback and disseminate the final framework

WP4– Project Management: This WP ensures that the project is carried out as planned with high quality and in relation to the research ethics and open science policies. A reference group consisting of stakeholders will be developed for discussing the project progress during two meetings per year. In addition to the kick-off and project-termination meetings, three workshops will be organised as well to present and discuss the research outputs and to make sure the project continues as planned. WP4 activities include:

  • Task 4-1- Project management and administration
  • Task 4-2- Project communication (internal and external)
  • Task 4-3- Project results dissemination

Funding:

This project is co-funded by the Norway's Troms and Finnmark, and Nordland Counties under Arktis 2030 TFFK-Hovedprosjekt programme, Grant Number: 2021-0462, 4,997,728 NOK, and is run jointly by UiT The Arctic University of Norway as the project owner, SINTEF Nord AS, The Norwegian Meteorological Institute, and The Norwegian Coastal Administration as partners.