Khan, Bushra (2020) Operational risk assessment for shipping in Arctic waters. Doctoral (PhD) thesis, Memorial University of Newfoundland.
[English]
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Abstract
Arctic navigation has many complexities due to its particular features such as ice, severe weather conditions, remoteness, low temperatures, lack of crew experience, and extended period of darkness or daylight. For these reasons, vessels, such as oil tankers, dry cargo ships, offshore supply vessels, research vessels, and passenger ships operating in the Arctic waters may pose a high risk of collision with ice and other ships causing human casualties, environmental pollution and the loss of assets. This thesis presents a conceptual framework that is focused on collision modelling. In order to understand the process of risk escalation and to attempt a proactive approach in constituting the collision models for Arctic navigation, the present thesis identifies various risk factors that are involved in a collision. Furthermore, the thesis proposes the probabilistic framework tools that are based on the identified risk factors to estimate the risks of collision in the Arctic. The proposed frameworks are used to model the collision based risk scenarios in the region. They are developed with the use of Bayesian Networks, the Nagel-Schreckenberg (NaSch), and Human Factor Analysis and Classification (HFACS) models. In the present thesis, the proposed models are theoretical in nature, but they can be useful in developing a collision monitoring system that provides a real time-estimate of collision probability that could help avoid collisions in the Arctic. Further, the estimated probabilities are also useful in decision making concerning safe independent and convoy operations in the region. The proposed frameworks simplifies maritime accident modeling by developing a practical understanding of the role of physical environment, navigational and operational related aspects of ships, and human errors, such as individual lapses, management failures, organizational failures, and economic factors in the collision related accidents in the Arctic. This research also identifies the macroscopic properties of maritime traffic flow and demonstrates how these properties influence collision properties. The thesis also presents an innovative accident model for ice-covered waters that estimates the collision probability and establishes the relationship between the macroscopic properties of the traffic flow with the contributory accidental risk factors in the region. The main focus of the present thesis is, to better understand, communicate, and incorporate specific risk factors into the maritime risk assessment processes, involve shipping organizations to agree on best practice methodologies and make the data sources easily available, and modify the Arctic risk management processes by implementing effective risk assessment techniques and appropriate risk treatment.
Item Type: | Thesis (Doctoral (PhD)) |
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URI: | http://research.library.mun.ca/id/eprint/14461 |
Item ID: | 14461 |
Additional Information: | Includes bibliographical references. |
Keywords: | Risk Assessment, Arctic Ocean, Bayesian Networks, Northern Sea Route, Safe navigation at sea |
Department(s): | Engineering and Applied Science, Faculty of |
Date: | May 2020 |
Date Type: | Submission |
Digital Object Identifier (DOI): | https://doi.org/10.48336/0m1b-f450 |
Library of Congress Subject Heading: | Collisions at sea--Simulation methods; Collisions at sea--Risk assessment. |
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