Risk-based integrity assessment and failure probabilities of a residential single wall steel aboveground fuel oil storage tanks
Nazir, M and Khan, FI and Mangalam, S and Sumabat, R, Risk-based integrity assessment and failure probabilities of a residential single wall steel aboveground fuel oil storage tanks, Proceedings of the 11th International Probabilistic Safety Assessment and Management Conference and the Annual European Safety and Reliability Conference 2012, PSAM11 ESREL 2012, 25-29 June 2012, Helsinki, Finland, pp. 1716-1725. ISBN 9781622764365 (2012) [Refereed Conference Paper]
Integrity assessment of residential engineering equipments such as fuel oil storage tanks is not done during its service life. In the absence of the incremental deterioration data over the service life, the deterioration rates can only be characterized using failure data. This is quite opposite to the process industry practice of inservice inspections and integrity assessment. In process facility inspections are done to assess the on going deterioration processes and to ensure safe operations during the service life of equipments. Limited work is reported on the estimation of the corrosion rates based on the component failure durations as compared to the work based on in-life inspection data. The current work develops a methodology that can establish corrosion rate estimates based on the failure data (data collected at the realization of the failure). A Bayesian approach to model the corrosion rate for a residential single wall aboveground fuel oil storage tank, is proposed here. The corrosion failure data utilized in this study are obtained from the database of Technical Standard and Safety Authority, Ontario. The posterior density function is used to quantify epistemic uncertainty in the corrosion rate parameter. A probabilistic model is, then, employed to account for the overall uncertainty associated with the corrosion rate variable. The corrosion rate estimate is utilized as an input to a stochastic deterioration process to assess the failure probabilities of the equipment.