Bayesian network modelling of an offshore electrical generation system for applications within an asset integrity case for normally unattended offshore installations

Abstract

This research focuses on the development of an Initial Bayesian Network (BN) model for modelling system and component failures on a large offshore installation. The intention of the presented research is to model a sequence of events following a specific component failure, under certain conditions and assumptions. This sequence of events is then applied to a BN

Utilising Bayesian networks to demonstrate the potential consequences of a fuel gas release from an offshore gas-driven turbine

“…This research does not set to outline the fundamentals of BN theory or give the BN methodology in detail. The methodology presented in the research by Loughney and Wang 5 is applied to construct this BN model. The model representing the potential for fuel gas release from an offshore gas turbine, along with the further consequences of fire and explosion, begins at the point of several initiating events.…”

“…The Asset Integrity Case is, in principle, an extended safety case. 5 From the initial research conducted by Loughney and Wang, 5 a sequence of events and a BN were produced to demonstrate the cause and effect relationships between the safety critical elements of the generator. The BN demonstrated a number of potential consequences, such as gas import riser failure, high pressure gas flare drum failure, and fuel gas release and fire.…”

“…3,4,6,7 The model to be presented here is an expansion of the previous model, focused on the consequence, fuel gas release and fire. In Loughney and Wang, 5 fuel gas release and its consequences were represented as one node in the network. This research expands on this by constructing a new network to demonstrate the consequence of a gas turbine fuel gas release in much more detail.…”

“…This research expands on this by constructing a new network to demonstrate the consequence of a gas turbine fuel gas release in much more detail. 5,8…”

“…A key part of the study is that it is the development of a logical and consistent risk assessment model, by applying Bayesian network techniques to a sequence of events based upon several initiating failures within a gas turbine. Furthermore, there is also the possibility of expanding the methodology and BN applications in Loughney and Wang 5 and this study to other areas and industries, as well as in conjunction with other techniques. For example, Yan et al 9 apply Bayesian network-bow-tie (BN-bow-tie) analysis, proposed by mapping bow-tie analysis into BN for analysis of gas leaks during biomass gasification.…”