Journal
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
Volume 162, Issue -, Pages 357-372Publisher
ELSEVIER
DOI: 10.1016/j.psep.2022.03.089
Keywords
Risk performance reasoning; Dempster-Shafer evidence theory; Dynamic Bayesian network; Cloud model; Arctic waters
Categories
Funding
- National Key Research and Development Program of China [2021YFC2801000]
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This paper proposes a risk performance reasoning strategy for LNG ships navigating in Arctic waters and develops a risk performance reasoning technique for LNG tanker collision accidents in Arctic waters. The study reveals that the main risk in Arctic summer waters is posed by obstacles in the channel that are difficult to detect.
Risk performance reasoning strategy for LNG ships navigating in Arctic waters is proposed in this paper. Many uncertainties exist in the reasoning of ship navigation risk in Arctic waters, which are influenced by multi-source risk causing events. As a result of the aforementioned concerns, the dynamic Bayesian network (DBN) structure is offered as a solution for an uncertain risk assessment model. The DBN network can benefit from a strategy for solving ambiguous data information based on Dempster-Shafer (D-S) evidence theory and a cloud model. Additionally, a risk performance reasoning technique for LNG tanker collision accidents in Arctic waters is developed. Besides, the marine meteorological reanalysis data, data from ship borne sensor monitoring, and expert knowledge in the suggested risk performance reasoning method are incorporated. A case study confirmed that the risk performance reasoning of accidents was needed revealed that the main risk in Arctic summer waters is posed by obstacles in the channel that are difficult to detect, such as icebergs and reefs. (c) 2022 Institution of Chemical Engineers. Published by Elsevier Ltd. All rights reserved.
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