BayesiaLab
Risk Assessment of a Liquefied Natural Gas Process Facility Using Bow-Tie and Bayesian Networks

Risk Assessment of a Liquefied Natural Gas Process Facility Using Bow-Tie and Bayesian Networks

Abstract

In the last few decades, chemical and process industries have become more prone to accidents due to their complexity and hazardous installations. These accidents lead to significant economic and, most importantly, human losses. Risk management is one of the appropriate tools to guarantee the safe operations of these plants. Risk analysis is an important part of risk management, and it consists of different methods such as Fault tree, Bow-tie, and Bayesian network (BN). The latter has been widely applied for risk analysis purposes due to its flexible and dynamic structure. In the current presentation, we will expose the different applications of BN in chemical and process industries with examples to explain how BN can be used to conduct a risk assessment, safety, and risk analysis of these industries.

Presentation Video

Not available.

About the Presenter

Hamza Zerrouki, Department of Process Engineering, University Amar Telidji of Laghouat, Laghouat, Algeria

I joined the Department of process engineering in September 2018. Before that, I was with the Institute of Occupational Health and Safety at Batna 2 University as a Ph.D. student from 2013 until 2018.

I have a bachelor's degree in industrial and environmental safety from the University of Laghouat (2011) and a master’s degree in control of industrial risks from the University of Batna 2 (2013). My research is mainly focused on the safety assessment and management of petrochemical facilities regarding technological accidents and Bayesian network applications.


For North America

Bayesia USA

4235 Hillsboro Pike
Suite 300-688
Nashville, TN 37215, USA

+1 888-386-8383
info@bayesia.us

Head Office

Bayesia S.A.S.

Parc Ceres, Batiment N 21
rue Ferdinand Buisson
53810 Change, France

For Asia/Pacific

Bayesia Singapore

1 Fusionopolis Place
#03-20 Galaxis
Singapore 138522


Copyright © 2024 Bayesia S.A.S., Bayesia USA, LLC, and Bayesia Singapore Pte. Ltd. All Rights Reserved.