Accident scenario analysis for maritime operations

• Main Author: Baksh, MA
• Format: Thesis
• Language: English
• Published: 2018
• Subjects: Arctic transportation risk; Bayesian network; consequence assessment; forward collision avoidance; scenario-based modeling; object-oriented Bayesian network; Arctic; Northern Sea Route
• Online Access: https://eprints.utas.edu.au/28680/; https://eprints.utas.edu.au/28680/1/Baksh_whole_thesis.pdf

Over the years, there has been a significant increase in both size and complexity of processes in marine and offshore operations. One example of maritime operations is that of large-scale Floating Liquefied Natural Gas (FLNG) processing facilities. Accidents in such facilities can be very complex and would be best characterised by evolving scenarios. This thesis reports on the development of a new methodology to incorporate evolving scenarios in a single model and predicts the likelihood of an accident. The methodology comprises; (a) evolving scenario identification, (b) accident consequence framework development, (c) accident scenario likelihood estimation, and (d) ranking of the scenarios. Resulting events in the present work are modelled using a Bayesian Network (BN) approach, which represents accident scenarios as cause-consequences networks. The methodology developed in this thesis is compared with case studies of ammonia and Liquefied Natural Gas (LNG) from chemical and offshore process facility, respectively. The proposed method can differentiate the consequence of specific events and predict probabilities for such events along with continual updating of the consequence probabilities of fire and explosion scenarios being taken into account. The developed methodology can be used to envisage evolving scenarios that occur in the offshore oil and gas processing industry. However, with further modification, it can be applied to different sections of marine industry to predict the likelihood of such accidents. Maritime transportation poses risks regarding possible accidents resulting in damage to vessels, crew members and to the ecosystem. The safe navigation of ships, especially in Arctic waters, is a growing concern to maritime authorities. This study proposes a new risk model to investigate the possibility of marine accidents such as collision, foundering and grounding. The model is developed using the BN. The proposed risk model has considered different operational and environmental factors that affect shipping operations. The application of the model is demonstrated through a case study of an oil-tanker navigating the Northern Sea Route (NSR). By running uncertainty and sensitivity analyses of the model, a significant change in the likelihood of the occurrence of accidental events is identified. The model suggests ice effect as a dominant factor in accident causation. The case study illustrates the priority of the model in investigating the operational risk of accidents. The developed methodology can be used to investigate the possibility of preventing and mitigating ship accidents in harsh and cold environments. Collision avoidance in narrow channel is critical if no early warning is provided. In this thesis, a dynamic risk management system is proposed for the marine vessel so that it can be useful by warning the operator of a vessel of a potential collision threat while travelling along narrow trafficway. This model estimates the level of risk by taking into consideration vessel kinematics, different operational and environmental factors as well as human factors in a confined area and provides early warning. Five decision-making skills viz. general skills, management training, technical knowledge, emergency skills and sailing experience are employed as requirements in an emergency. The applicability of the proposed methodology has been demonstrated through two case scenarios in a narrow channel. The probability obtained through the proposed methodology can be used to make a real-time decision, such as situation assessment, appropriate and immediate action followed by the evasive action. The simulated result shows the increasing level of risk as the probability of warning level increases. Similarly, lower risk decreases as the situation crosses that threshold. The estimated risk allows early warning to take appropriate preventive and mitigative measures to avoid a collision and thus enhance the overall safety of shipping operations.