Dal Alert!

Receive alerts from Dalhousie by text message.



Title: Risk Based Decision Making for Marine Systems
Abstract: Creating safe and sustainable solutions for ocean development is vital for protecting marine systems and the environment from potential hazards. Risk may arise due to climate change, oil spill, shipping, oil and gas production, transportation, and inspection and maintenance (IM) of the equipment used in marine systems. Due to these risks, making decisions under uncertainty with limited knowledge, scarce data and lack of experience in ocean frontiers is challenging. The first part of the presentation will focus on risk based decision making frameworks for marine systems. Subsequently, the recently developed Risk Based Integrity Modelling (RBIM) will be discussed for the optimization of limited IM resources for marine industries. System deterioration is a stochastic process. RBIM is a newly developed approach that aims at the protection of human and marine life, financial investments and the environment against the consequences of failure. RBIM quantifies the ris! k to which the systems/components are subjected and uses this as a basis for the design of a maintenance strategy. The major time-dependent deteriorations observed from the field include corrosion and cracking, which are modelled using stochastic process to estimate the probability of failure using Bayesian analysis. Bayesian analysis improves the fidelity of the likelihood of future events by relating it with prior and posterior probabilities. Prior modeling is based on judgmental studies and analyzing historic data from similar installations, whereas the likelihood probability is based on field non-destructive test data. The posterior modeling is performed using a simulation based Metropolis-Hastings algorithm and Laplace approximations since the prior-likelihood combinations are non-conjugate pairs. Failure consequences are modelled using engineering economic analysis by estimating the cost of failure, inspection, and maintenance. The cost of failure includes lost commod! ity, loss of shutdown, spill cleanup, loss caused by environme! ntal damage and liability. The equivalent cost of deterioration is combined with the cumulative (posterior) failure probability to produce an operational risk curve. Since the operational risk curve is a convex function of the IM interval, the optimum interval is the global minimum point. The operational risk can thus be reduced to a minimum level through optimal maintenance. Finally, application of the risk based decision making frameworks will be discussed in relation to Arctic shipping, condition monitoring and integrated operations. 


Lectures, Seminars




MA 310, 5269 Morris Street 



Additional Information

Prem Thodi, Ph.D., P.Eng.
Memorial University

Biography: Prem Thodi is currently working as a Postdoctoral Fellow with the Center for Risk, Integrity and Safety Engineering (C-RISE) at Memorial University. He has 10 years of professional experience, of which 8 years he spent in the Oil & Gas industry and 2 years in academia. In industry, most recently he worked as a Senior Engineering Specialist and JIP Manager with INTECSEA Canada, WorleyParsons and prior to his PhD, he worked as a Design Engineer for Structures and Pipelines with McDermott International. He gained his PhD degree in Oil & Gas Engineering from the Faculty of Engineering and Applied Science at Memorial University, where he produced a thesis titled as “Risk based integrity modeling for the optimal maintenance strategies of offshore process components”. He has published more than 30 papers in refereed journals and international conferences. Dr. Thodi is a recipient of the NSERC plus RDC Industrial R&D Fellowship (IRDF) and the David Dunsiger Award! for best thesis from Memorial University. He is a registered professional engineer (P. Eng.) with the association of professional engineers and geoscientists of Newfoundland and Labrador and a member of the society for risk analysis. His research expertise broadly covers dynamic risk assessment, stochastic optimization, decision under uncertainty, Arctic and harsh environment engineering, and marine structures and pipeline engineering.