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Title: Advanced quantitative risk assessment of offshore gas pipeline systems
Author: Lavasani, Seyed Mohammadreza Miri
ISNI:       0000 0004 2689 0371
Awarding Body: Liverpool John Moores University
Current Institution: Liverpool John Moores University
Date of Award: 2010
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This research has reviewed the current status of offshore and marine safety. The major problems identified in the research are associated with risk modelling under circumstances where the lack of data or high level of uncertainty exists. This PhD research adopts an object-oriented approach, a natural and straightforward mechanism of organising information of the real world systems, to represent the Offshore Gas Supply Systems (OGSSs) at both the component and system levels. Then based on the object-oriented approach, frameworks of aggregative risk assessment and fault tree analysis are developed. Aggregative risk assessment is to evaluate the risk levels of components, subsystems, and the overall OGSS. Fault trees are then used to represent the cause-effect relationships for a specific risk in the system. Use of these two assessment frameworks can help decision makers to obtain comprehensive view of risks in the OGSS. In order to quantitatively evaluate the framework of aggregative risk, this thesis uses a fuzzy aggregative risk assessment method to determine the risk levels associated with components, subsystems, and the overall OGSS. The fuzzy aggregative risk assessment method is tailored to quantify the risk levels of components, subsystems, and the OGSS. The proposed method is able to identify the most critical subsystem in the OGSS. As soon as, the most critical subsystem is identified, Fuzzy Fault Tree Analysis (FFTA) is employed to quantitatively evaluate the cause-effect relationships for specific undesired event. These results can help risk analysts to select Risk Control Options (RCOs) for mitigating risks in an OGSS. It is not financially possible to employ all the selected RCOs. Therefore, it is necessary to rank and select the best RCO. A decision making method using the Fuzzy TOPSIS (FTOPSIS) is proposed to demonstrate the selection of the best RCOs to control the existing risks in the system. The developed models and frameworks can be integrated to formulate a platform which enables to facilitate risk assessment and safety management of OGSSs without jeopardising the efficiency of OGSSs operations in various situations where traditional risk assessment and safety management techniques cannot be effectively applied.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
Keywords: HD61 Risk Management ; TC Hydraulic engineering. Ocean engineering