Sarwar, Adnan (2018) Resilience analysis of offshore safety and power system. Masters thesis, Memorial University of Newfoundland.
[English]
PDF
- Accepted Version
Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission. Download (2MB) |
Abstract
Harsh and deep waters create challenging environments for offshore drilling and production facilities, resulting in increased chances of failure. This necessitates improving the resilience of the engineering system, which is the capability of a system to recover its functionality during disturbance and failure. The present work proposes an approach to quantify resilience as a function of vulnerability and maintainability. The approach assesses proactive and reactive defense mechanisms along with operational factors to respond to unwanted disturbances and failures. The proposed approach employs a Bayesian network to build two resilience models. Two developed models are applied to: 1) a hydrocarbon release scenario during an offloading operation in a remote and harsh environment, and 2) the main requirements to improve the resilience of an offshore power management system. This study attempts to relate resilience capacity of a system to the system’s absorptive, adaptive and restorative capacities. These capacities influence pre-disaster and post-disaster strategies that can be mapped to enhance resilience of the system. Furthermore, the technique of an object-oriented framework is adopted to better structure the resilience model as a function of a system’s adaptability, absorptive and restorative capabilities. Sensitivity analysis is also conducted to analyze the impact and interdependencies among different variables to enhance resilience.
Item Type: | Thesis (Masters) |
---|---|
URI: | http://research.library.mun.ca/id/eprint/13147 |
Item ID: | 13147 |
Additional Information: | Includes bibliographical references. |
Keywords: | Risk Management, Hydrocarbon Release, Power System, Integrated Operations, Bayesian Network |
Department(s): | Engineering and Applied Science, Faculty of |
Date: | May 2018 |
Date Type: | Submission |
Library of Congress Subject Heading: | Offshore oil industry -- Risk management -- Mathematical models |
Actions (login required)
View Item |