Comparative studies on assessment of corrosion rates in pipelines as semi-probabilistic and fully stochastic values

Opeyemi, David A. and Patelli, Edoardo and Beer, Michael and Timashev, Sviatoslav A.; (2015) Comparative studies on assessment of corrosion rates in pipelines as semi-probabilistic and fully stochastic values. In: 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015. 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015 . University of British Columbia, CAN. ISBN 9780888652454

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    Abstract

    Reduction of pipeline carrying capacity and safety are often caused by corrosion and its potential damaging effects. Simple techniques which can be used to evaluate both current and the timedependent change in the pipeline's reliability are needed since reliability analysis is recognized as a powerful decision-making tool for risk-based design and maintenance. The prediction of future sizes of growing defects and the pipeline remaining life time are obtained by using consistent assessments of their Corrosion Rates (CRs); and these CRs may be considered as deterministic, semi-probabilistic or fully stochastic values. The idea of predicting future sizes of growing defects and corrosion rates as semi-probabilistic and fully stochastic values is considered with a comparison of the results conducted and implemented on a real life pipeline. In this contribution, a probabilistic method based on the imprecise probability approach is presented to predict the remaining life time and the failure probability of pipelines with corrosion defects by using the Monte Carlo simulation (MCS) method implemented in OpenCossan; the open source engine of COSSAN software for uncertainty quantification and risk management. The results obtained from deterministic, semi-probabilistic and probabilistic methods are compared using B31G, Modified B31G and DNV-101 pressure failure models. The proposed probabilistic method of assessment can be applied for the design of new systems as well as assessing of existing pipelines in operation.