DYNAMIC PROBABILITY FAILURE USING BAYESIAN NETWORK FOR HYDROGEN INFRASTRUCTURE MODELING

To produce large scale hydrogen production, it requires adequate and efficient risk control. For decades, fault tree analysis was the most widely used tool for risk assessment for industrial sector generally and hydrogen infrastructure particularly in terms of risk and consequences associated to...

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Bibliographic Details
Main Author: Nurdin, Mohamad Faizal
Format: Final Year Project
Language:English
Published: Universiti Teknologi PETRONAS 2012
Subjects:
Online Access:http://utpedia.utp.edu.my/9653/1/2012%20-%20Dynamic%20Probability%20Failure%20using%20Bayesian%20Network%20for%20Hydrogen%20Infastructure%20Modeling.pdf
http://utpedia.utp.edu.my/9653/
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Summary:To produce large scale hydrogen production, it requires adequate and efficient risk control. For decades, fault tree analysis was the most widely used tool for risk assessment for industrial sector generally and hydrogen infrastructure particularly in terms of risk and consequences associated to it. The limitation to this tool is it tends to be static and do not develop over time which can give unreliable estimation of risk. The purpose of this project is to study the suitability and efficiency of dynamic Bayesian Networks in terms of projecting the risk probability failure that develop over time for hydrogen infrastructure as the alternative of the fault tree analysis. In this study, only the risk probability failure is covered without further exploration on the consequences of the risk. The process involved by the conversion of fault tree to Bayesian Networks model by using appropriate framework. Then, the conditional probability table is assigned to each node where the numbers of CPT depend on the numbers of relationship between nodes. Finally the temporal reasoning is done to show the time-invariant between each node and the beliefs is updated to get the results. The ways of inference use for this study are filtering and smoothing. The results show that generally, the OR gates contribute to higher risk probability compare to AND gates. Besides that, the probability for hydrogen activities increase from year to year with the assumption the accident did not happen the previous year. In addition, the instantaneous release incident is relatively low and unlikely to happen compare to the continuous release.