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Loading Combination Screening Using Probabilistic Determination of Load-Case Matrices

[+] Author Affiliations
Neill C. Renton

Genesis, Aberdeen, UK

Paul Sicsic

TechnipFMC, Rueil Malmaison, France

Joao Falcao Alegrias

TechnipFMC, Aberdeen, UK

Paper No. OMAE2017-61384, pp. V05AT04A013; 8 pages
  • ASME 2017 36th International Conference on Ocean, Offshore and Arctic Engineering
  • Volume 5A: Pipelines, Risers, and Subsea Systems
  • Trondheim, Norway, June 25–30, 2017
  • Conference Sponsors: Ocean, Offshore and Arctic Engineering Division
  • ISBN: 978-0-7918-5769-4
  • Copyright © 2017 by ASME


The application of probabilistic methods to determine the design of offshore systems such as jackets, ship hulls and pipelines is well developed and has a long and successful track record. While flexible risers are subjected to the same random environmental loads, probabilistic methods have yet to be applied in any meaningful way to the common limit states examined by the design community.

Flexible riser systems offer operators a robust method of producing oil and gas fields in harsh environments. Systems are currently designed using a mixture of local and international standards such that they can withstand conditions with a sufficient margin of safety. Extreme dynamic analyses using proprietary finite element analysis (FEA) codes are performed using a deterministic load case matrix to define the extreme loading on the riser system. The loads are used to iterate the riser configuration / cross-section design to a fit-for-purpose solution and to define ancillary equipment, such as bend stiffeners, bend stiffener connectors, buoyancy modules and riser clamps.

Individual load cases (LC) are defined by combining a number of parameters in order to represent different weather events and associated vessel responses in certain operating and accidental conditions, known as engineering events. LC matrices are then defined based on all combinations of weather and engineering events. However, the likelihood of the weather event or the engineering event occurring is currently not assessed.

In the existing deterministic approach, all cases are run through the FEA model to validate the design criteria. However, increases in computing power have allowed load case matrices to expand by orders of magnitude as more variables and environmental conditions are considered. This has resulted in a large increase in engineering costs and capital expenditure through potentially over-designed solutions.

This paper will demonstrate a new probabilistic screening assessment for developing a LC matrix for the dynamic analysis of flexible risers. Specifically, the combined wave and current loads on the flexible riser system in service are examined to determine the probability of occurrence of the weather event. ISO 13628-2 [1] currently states that load cases with a frequency of 1 in 10,000 years are non-credible for design purpose and can be ignored. The field metocean data including directional sea-states and likelihoods are used to confirm which weather events meet this criteria, screening out those which are non-credible. This screening reduces significantly the number of load combinations while validating a fit for purpose design. The correlation of environmental loads generated by wind, wave and currents is a complex topic, nevertheless, it is incorporated conservatively in the screening method developed in this study.

An example is shown for the West-of-Shetland quadrant, where the methodology is applied to a designed riser system. The screening methodology shows 70% of the load cases have non-credible probabilities of occurrence of less than 2.0E−03 over 20 years (lower than one in 10,000 year annual frequency). The example also shows that the load cases which governed the design present a lower probability of occurrence than specified by the industry standards. The methodology removes complexity from the engineering system which could be directly converted into manufacturing and installation cost-savings.

Copyright © 2017 by ASME
Topics: Stress



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