Offshore pipelines and ice gouge geohazards: Comparative performance assessment of decoupled structural and coupled continuum models1
Offshore pipelines in ice environments may be subjected to unique geohazards such as seabed ice gouging. These events involve nonlinear processes including large deformations and strains, contact mechanics, and failure mechanisms. Current pipeline engineering design practice employs decoupled, struc...
| Published in: | Canadian Geotechnical Journal |
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| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | https://ir.library.carleton.ca/pub/10407 https://doi.org/10.1139/cgj-2016-0090 |
| Summary: | Offshore pipelines in ice environments may be subjected to unique geohazards such as seabed ice gouging. These events involve nonlinear processes including large deformations and strains, contact mechanics, and failure mechanisms. Current pipeline engineering design practice employs decoupled, structural finite element modelling procedures to assess system demand and capacity. The inherent error and uncertainty within this approach drives conservative engineered solutions. Physical modelling and continuum numerical simulation tools complement this engineering framework to improve confidence in predicted outcomes. The relative performance of engineering models, used in current practice, and numerical simulation tools, including structural and continuum finite element modelling procedures, to predict the deformation and strain response of a buried pipeline subjected to an ice gouge event is examined. Refinements to the numerical modeling procedures and establishment of a consistent and compatible reference framework for the performance evaluation differentiate this study from others, which are subsets of the current investigation. For the parameter analysis conducted, within an equivalent reference framework, the outcomes demonstrate key factors, including superposition error and directional load decoupling, that influence model error that may not be as significant as previously considered. The scope and extent of this outcome is not fully understood and requires further investigations to delineate the significance across a wider parameter range. |
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