Probabilistic Lateral Buckling Assessment
- Carlos Sicilia (INTECSEA) | Philip A. Cooper (INTECSEA) | Emilien Bonnet (INTECSEA)
- Document ID
- International Society of Offshore and Polar Engineers
- International Journal of Offshore and Polar Engineering
- Publication Date
- December 2015
- Document Type
- Journal Paper
- 241 - 246
- 2015. The International Society of Offshore and Polar Engineers
- Monte Carlo (MC), probabilistic, lateral buckling, reliability, Safebuck, Pipeline, neural network
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- 188 since 2007
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This paper presents a probabilistic method to assess the lateral buckling response of a pipeline. The method is based on a Monte Carlo (MC) simulation in which the lateral buckling response is predicted through the use of a surrogate model that employs artificial neural networks (ANNs) calibrated from nonlinear finite element (FE) analyses. The method presented intends to improve on current industry best practice by directly considering the limit states relevant to global buckling to produce designs with consistent levels of reliability.
In the design of offshore pipelines, it is often convenient and sometimes necessary to allow the formation of lateral buckles. This relieves the axial compression but can potentially lead to severely localized bending deformations. In such designs, the lateral buckles are often subjected to the most onerous loading conditions and govern the mechanical design of the pipeline.
The response of a pipeline at a lateral buckle can be modeled in great detail through the use of sophisticated nonlinear finite element analysis (FEA). However, such models require information that is not available at the design stage. This information includes the pipe-soil interaction response, which can be quantified at the design stage but is subjected to significant uncertainty, and the as-laid geometry of the pipe in the vertical and horizontal planes, which cannot be determined until the pipeline has been laid. The uncertainty in these two parameters leads to additional uncertainty regarding where the buckles form and, more importantly, how far apart the buckles are from one another, as this governs the level of load (axial feed-in or expansion) that goes into each buckle location.
The uncertainty in design is normally accounted for by the use of safety (load and resistance) factors calibrated to achieve a certain probability of failure. In the case of the lateral buckling response of a pipeline, this would seem impractical given the very high level of uncertainty and the interdependence between the global response of the pipeline, i.e., where the buckles form, and the local response at each lateral buckle. Under these circumstances, a pipeline-specific probabilistic assessment appears to be a suitable approach.
This type of approach was proposed by the Safebuck Joint Industry Project (JIP) (Bruton and Carr, 2011), which developed the Buckfast software available to the participants of the JIP. This approach, however, is based on the concept of the characteristic virtual anchor spacing (VAS), which requires a calibration implicit in the Safebuck methodology/guidelines to obtain the required probabilities of failure.
The purpose of this paper is to present a probabilistic assessment of the lateral buckling response of a pipeline that is based on the actual limit states and therefore requires no calibration. The proposed strategy is intended to achieve probabilities of failure in line with those required for the rest of the design of the system and therefore to produce a design that is better optimized.
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