Evaluation of human error contribution to oil tanker collision using fault tree analysis and modified fuzzy Bayesian Network based CREAM

2019 ◽  
Vol 179 ◽  
pp. 159-172 ◽  
Author(s):  
Shuen-Tai Ung
Keyword(s):  
Bayesian Network ◽  
Human Error ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Tree Analysis ◽  
Oil Tanker

A human error mechanism for pilot based on fault tree analysis and Bayesian network

2020 ◽  
Vol 38 (6) ◽  
pp. 6863-6871
Author(s):  
Guo Xinyao ◽  
Meng Bin ◽  
Liu Yawei ◽  
Lu Na ◽  
Fu Shuai ◽  
...  
Keyword(s):  
Bayesian Network ◽  
Human Error ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Tree Analysis

Application of Bayesian Network in Safety Evaluation of Metro Construction

2013 ◽  
Vol 838-841 ◽  
pp. 1463-1468
Author(s):  
Xiang Ke Liu ◽  
Zhi Shen Wang ◽  
Hai Liang Wang ◽  
Jun Tao Wang
Keyword(s):  
Bayesian Networks ◽  
Bayesian Network ◽  
Posterior Probability ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Safety Evaluation ◽  
Tree Analysis ◽  
Tunnel Blasting ◽  
Better Than

The paper introduced the Bayesian networks briefly and discussed the algorithm of transforming fault tree into Bayesian networks at first, then regarded the structures impaired caused by tunnel blasting construction as a example, introduced the built and calculated method of the Bayesian networks by matlab. Then assumed the probabilities of essential events, calculated the probability of top event and the posterior probability of each essential events by the Bayesian networks. After that the paper contrast the characteristics of fault tree analysis and the Bayesian networks, Identified that the Bayesian networks is better than fault tree analysis in safety evaluation in some case, and provided a valid way to assess risk in metro construction.

scholarly journals Human Reliability Using the Fault Tree Analysis. A Case Study of a Military Accident Investigation

2016 ◽  
Vol 22 (1) ◽  
pp. 215-219 ◽  
Author(s):  
Florin Nicolae ◽  
A. Cotorcea ◽  
Marian Ristea ◽  
Dinu Atodiresei
Keyword(s):  
Human Error ◽  
Human Performance ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Human Reliability ◽  
Tree Analysis ◽  
Safety Systems ◽  
The Relationship ◽  
Critical Subsystems

Abstract The work integrates the human error term in the broader concept of human performance analysis. The main issues associated with human error and human reliability are highlighted step by step, resulting from the review of literature, from the perspective of the relationship between risk and safety. To assess the risks arising from human error and to reduce vulnerability of work, methods derived from the probabilistic assessment of the work safety systems are used. To identify the risks caused by the human error, the authors propose the Fault Tree Analysis (FTA) method. The paper reveals the way the method is used for identifying the critical subsystems for the functioning of a given system and analyzes how unwanted events and their causes arise and occur. Also, a case study that is investigated throuhg the FTA method and that consists in the analysis of an accident that occurred in Evangelos Florakis naval logistics base from Cyprus, is presented.

Cause factors in emergency process of fire accident for oil–gas storage and transportation based on fault tree analysis and modified Bayesian network model

2018 ◽  
Vol 29 (5) ◽  
pp. 802-821 ◽  
Author(s):  
Changfeng Yuan ◽  
Hui Cui ◽  
Bin Tao ◽  
Siming Ma
Keyword(s):  
Bayesian Network ◽  
Network Model ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Analysis Method ◽  
Bayesian Network Model ◽  
Tree Analysis ◽  
Oil Gas ◽  
Emergency Process ◽  
Fire Accident

From the perspective of the safety of emergency process, in this paper, we put forward a new analysis method of cause factors based on fault tree analysis and modified Bayesian network in emergency process of fire accident for oil–gas storage and transportation. Nineteen cause factors are found based on the statistical analysis of actual accident cases. We adopt fault tree analysis method and Bayesian network model to analyze cause factors qualitatively and quantitatively. In order to more accurately determine the quantitative influencing degree of each cause factor, the conditional probabilities in Bayesian network are modified by using expert scoring method and modified Bayesian network model is established. Finally, the proposed method is applied to analyze cause factors in emergency process of two practical accident cases. Research results have an important scientific significance to reveal evolution mechanism of secondary accidents in emergency process and ensure system safety in whole life cycle.

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