Event-tree analysis by fuzzy probability

1992 ◽  
Vol 32 (1-2) ◽  
pp. 291
2017 ◽  
pp. 141-154
Author(s):  
Sasho Andonov

2017 ◽  
Author(s):  
Timothy A. Wheeler ◽  
Matthew R. Denman ◽  
R. A. Williams ◽  
Nevin Martin ◽  
Zachary Kyle Jankovsky

2011 ◽  
Vol 6 (7) ◽  
pp. 340-348 ◽  
Author(s):  
Zhongbao Zhou ◽  
Xuan Zeng ◽  
Haitao Li ◽  
Siya Lui ◽  
Chaoqun Ma

Author(s):  
Danilo Taverna Martins Pereira de Abreu ◽  
Marcos Coelho Maturana ◽  
Marcelo Ramos Martins

Abstract The navigation in restricted waters imposes several challenges when compared to open sea navigation. Smaller dimensions, higher traffic density and the dynamics of obstacles such as sandbanks are examples of contributors to the difficulty. Due to these aspects, local experienced maritime pilots go onboard in order to support the ship’s crew with their skills and specific regional knowledge. Despite these efforts, several accidents still occur around the world. In order to contribute to a better understanding of the events composing accidental sequences, this paper presents a hybrid modelling specific for restricted waters. The main techniques used are the fault tree analysis and event tree analysis. The former provides a framework to investigate the causes, while the latter allows modelling the sequence of actions necessary to avoid an accident. The models are quantified using statistical data available in the literature and a prospective human performance model developed by the Technique for Early Consideration of Human Reliability (TECHR). The results include combined estimates of human error probabilities and technical failure probabilities, which can be used to inform the causation factor for a waterway risk analysis model. In other words, given that the ship encounters a potential accidental scenario while navigating, the proposed models allow computing the failure probability that of the evasive actions sequence. The novelty of this work resides on the possibility of explicitly considering dynamicity and recovery actions when computing the causation factor, what is not a typical feature of similar works. The results obtained were compared with several results available in the literature and have been shown to be compatible.


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