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Extreme Response Prediction of Steel Risers Using a Four Parameter Distribution

[+] Author Affiliations
Miguel Alfonso Calderon Ibarra, Fernando Jorge Mendes de Sousa, Luís Volnei Sudati Sagrilo

Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

Ying Min Low

National University of Singapore, Singapore, Singapore

Paper No. OMAE2017-61481, pp. V03BT02A001; 8 pages
doi:10.1115/OMAE2017-61481
From:
  • ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering
  • Volume 3B: Structures, Safety and Reliability
  • Trondheim, Norway, June 25–30, 2017
  • Conference Sponsors: Ocean, Offshore and Arctic Engineering Division
  • ISBN: 978-0-7918-5766-3
  • Copyright © 2017 by ASME

abstract

Recently, a four-parameter distribution known as the shifted generalized lognormal distribution (SGLD) has been presented in the literature. One of its main advantages is that it covers regions of skewness-kurtosis not covered by other distributions of common use in engineering. In this paper, the performance of this distribution is evaluated in the extreme values’ estimation of the utilization ratios of steel riser sections. Three alternatives for using SGLD are investigated in two case studies of different dynamic behavior. The first one is a SLWR (steel-lazy wave riser) connected to a turret-moored FPSO in 914m water depth, and the second is a SLWR connected to a spread-mooring FPSO in a water depth of 1400m. The results obtained by the SGLD-based analysis, which considered several simulation lengths, are compared to those obtained by means of an extreme value distribution fitted to episodical extremes obtained from many distinct realizations. The results of a traditional Weibull-fitting approach to the response peaks and those obtained with and Hermite transformation-based model are also presented for comparison.

Copyright © 2017 by ASME

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