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On Probabilistic Fracture Assessment of Defective Pipeline Based on Target Failure Probabilities

[+] Author Affiliations
Jae-Bin Lee, Ki-Seok Kim, Woo-Yeon Cho, Sang-Hoon Shim

POSCO, Incheon, Korea

Nam-Su Huh

Seoul National University of Science and Technology, Seoul, Korea

Paper No. OMAE2015-41190, pp. V05BT04A009; 9 pages
doi:10.1115/OMAE2015-41190
From:
  • ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering
  • Volume 5B: Pipeline and Riser Technology
  • St. John’s, Newfoundland, Canada, May 31–June 5, 2015
  • Conference Sponsors: Ocean, Offshore and Arctic Engineering Division
  • ISBN: 978-0-7918-5652-9
  • Copyright © 2015 by ASME

abstract

This paper investigates the priorities as well as the safety factors of each assessment variable for a defective pipeline based on a partial safety factor concept considering the target failure probabilities during operating period of components of interest.

For this, firstly wall-thinned pipeline under internal pressure is considered, which is important in fitness-for-service assessment of corroded pipeline. For the analysis, scatters in the applied pressure, mechanical properties and geometries of wall-thinned pipeline are considered using normal and log-normal distributions. In addition, partial safety factors of a circumferential through-wall cracked pipeline subjected to global bending moment are also evaluated based on the elastic-plastic fracture mechanics. In this case, scatters in the applied bending moment, mechanical and fracture properties are considered based on normal and log-normal distributions.

More importantly, two different deterministic integrity assessment methods are applied to wall-thinned pipeline and two different estimation methods of elastic-plastic J-integral are applied to circumferential through-wall cracked pipeline to evaluate the partial safety factors. Resulting values of partial safety factors are calculated using both the advanced first-order second moment method (AFOSM) and the second-order reliability method (SORM). Moreover, the effects of statistical distributions and variations of standard deviations of assessment variables on the partial safety factors are also demonstrated.

Copyright © 2015 by ASME

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