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Safety of Pipelines Subjected to Deterioration Processes Modelled Through Dynamic Bayesian Networks

[+] Author Affiliations
O. G. Palencia, A. P. Teixeira, C. Guedes Soares

Universidade de Lisboa, Lisboa, Portugal

Paper No. OMAE2017-61969, pp. V03AT02A058; 9 pages
doi:10.1115/OMAE2017-61969
From:
  • ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering
  • Volume 3A: Structures, Safety and Reliability
  • Trondheim, Norway, June 25–30, 2017
  • Conference Sponsors: Ocean, Offshore and Arctic Engineering Division
  • ISBN: 978-0-7918-5765-6
  • Copyright © 2017 by ASME

abstract

The paper studies the application of Dynamic Bayesian Networks for modelling degradation processes in oil and gas pipelines. A DBN tool consisting of a Matlab code has been developed for performing inference on models. The tool is then applied for probabilistic modelling of the burst pressure of a pipe subjected to corrosion degradation and for safety assessment. The burst pressure is evaluated using the ASME B31G design method and other empirical formulas. A model for corrosion prediction in pipelines and its governing parameters are explicitly included into the probabilistic framework. Different sets of simulated corrosion measurements are used to increase the accuracy of the model predictions. Several parametric studies are conducted to investigate how changes in the observed corrosion (depth and length) and in the frequency of inspections affect the pipe reliability.

Copyright © 2017 by ASME
Topics: Safety , Pipelines

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