In this study, a methodology has been proposed for risk analysis of dust explosion scenarios based on Bayesian network. Our methodology also benefits from a bow-tie diagram to better represent the logical relationships existing among contributing factors and consequences of dust explosions. In this study, the risks of dust explosion scenarios are evaluated, taking into account common cause failures and dependencies among root events and possible consequences. Using a diagnostic analysis, dust particle properties, oxygen concentration, and safety training of staff are identified as the most critical root events leading to dust explosions. The probability adaptation concept is also used for sequential updating and thus learning from past dust explosion accidents, which is of great importance in dynamic risk assessment and management. We also apply the proposed methodology to a case study to model dust explosion scenarios, to estimate the envisaged risks, and to identify the vulnerable parts of the system that need additional safety measures.

Item Type:	Refereed Article
Keywords:	Bayesian network, bow-tie model, dust explosion, risk analysis, Bayesian networks, dust, personnel training, risk analysis, risk assessment, risk perception, risks, safety engineering, bow tie, common cause failure, contributing factor, explosions
Research Division:	Engineering
Research Group:	Engineering practice and education
Research Field:	Risk engineering
Objective Division:	Expanding Knowledge
Objective Group:	Expanding knowledge
Objective Field:	Expanding knowledge in engineering
UTAS Author:	Khan, FI (Professor Faisal Khan)
ID Code:	120634
Year Published:	2015
Web of Science® Times Cited:	73
Deposited By:	NC Maritime Engineering and Hydrodynamics
Deposited On:	2017-08-29
Last Modified:	2017-10-30
Downloads:	0