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Applying a Bayesian Network methodology to an offshore gas turbine driven power generator to demonstrate the cause and effect relationship of the turbine running over-speed and the associated switchboard failures.

Loughney, S, Wang, J and Matellini, DB (2019) Applying a Bayesian Network methodology to an offshore gas turbine driven power generator to demonstrate the cause and effect relationship of the turbine running over-speed and the associated switchboard failures. In: Proceedings of the 29th EUROPEAN SAFETY AND RELIABILITY CONFERENCE (ESREL 2019) . (29th EUROPEAN SAFETY AND RELIABILITY CONFERENCE (ESREL 2019)?, 22 September 2019 - 26 September 2019, Hanover, Germany).

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Abstract

This paper investigates the benefits of applying a Bayesian Network in quantitative risk assessment of the integrity of an offshore gas turbine driven generator. The focus of the research is based on the potential failures and incidents associated with an offshore gas turbine running overspeed and failures within the switchboard. The potential consequences that follow said failures, such as fire, explosion and damage to mechanical equipment are also factored into the analysis. A methodology is outlined in order to construct a coherent BN model. This methodology consists of several steps, starting with identifying variables, to then constructing a qualitative BN model from these variables. The methodology culminates in validation of the BN model. A case study, regarding individual and combined component failures is also applied to demonstrate and validate the methodology. The Bayesian network allows the cause-effect relationships to be modelled through clear graphical representation. Similarly, the model can accommodate for continual updating of failure data. Partial validity of the model is demonstrated against some benchmark axioms. It is vital to maintain that the model must remain practical and close to reality from the perspective of gathering data and generating results.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Bayesian Networks; offshore; gas turbine; overspeed; hydrocarbon release; ignition
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TC Hydraulic engineering. Ocean engineering
Divisions: Maritime & Mechanical Engineering (merged with Engineering 10 Aug 20)
Publisher: Research Publishing Services
Date Deposited: 26 May 2020 08:43
Last Modified: 26 May 2020 08:43
Editors: Beer, M and Zio, E
URI: https://researchonline.ljmu.ac.uk/id/eprint/12988

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