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Record W1963989635 · doi:10.4043/20696-ms

SS: Atlantic Canada

2010· article· en· W1963989635 on OpenAlexaffabout
Ryan Phillips, John Barrett, Aiman Al-Showaiter

Bibliographic record

VenueAll Days · 2010
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsCentre For Cold Ocean Resources Engineering
Fundersnot available
KeywordsKeelSubmarine pipelinePipeline transportSeabedMarine engineeringArcticGeologyFinite element methodSea icePermafrostGeotechnical engineeringEngineeringOceanographyStructural engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Moving ice features impose significant challenges on engineering aspects of offshore oil and gas field development in the Arctic and sub-Arctic regions, particularly related to their interaction through the seabed with submarine installations such as pipelines. This paper compares continuum finite element modelling of ice keel-seabed interaction against physical model data and evaluates the current state-of-the-art. It identifies areas requiring further research and development, and evaluate potential limits on ice gouging in soft to stiff clays. Introduction Environmental conditions impose significant challenges on engineering aspects of oil and gas field development in the offshore Arctic and sub-Arctic regions. One major challenge is the burial depth requirements for marine pipelines against a gouging ice keel. King et al (2009) present a probabilistic burial analysis for pipeline protection against ice gouging of the seabed. The analysis combines a probabilistic characterization of the ice gouge regime with a deterministic analysis of pipeline strain response for a range of ice gouge widths, depths and ice keel/pipeline crown clearances, allowing a pipeline burial depth to be defined that satisfies specified stress/strain limits and target reliability levels. Such analyses require a relatively simple model of the ice - soil - pipe interaction to consider the multitude of different load cases. This simple model must be validated against available physical model test data and complex numerical analyses of a much smaller number of load cases, as recently recognized by DnV (2008). Continuum explicit finite element eulerian-based analyses provide an adequate framework for consideration of the ice - seabed - pipe interaction as demonstrated by Nobahar et al (2007), Liferov et al (2007), Konuk & Yu (2007) and Abdalla et al. (2009). These analyses focused on clay seabeds and can be calibrated using appropriate material parameters, but need to be validated against physical data. Limited validations to date in these papers have included comparisons to lateral subgouge deformation (SGD) profiles on the gouge centreline measured from PRISE centrifuge model tests described by Phillips et al (2005). This paper extends this validation to consider steady state conditions, gouge forces, frontal berm formation, seabed failure mechanisms and both vertical SGD and transverse distributions of lateral SGD below the gouge depth. The pipeline is not considered in this present validation. A validated numerical analysis can be used to extend the understanding of the seabed response to ice gouging and associated parametric influences such as keel geometry and seabed soil properties. Physical Model Test Data Konuk & Yu (2007), Liferov et al (2007) and Abdalla et al. (2009) compared their numerical modelling predictions to the physical model test data produced from PRISE. The Pressure Ridge Ice Scour Experiment (PRISE) joint industry research program was led by C-CORE, Phillips et al (2005). It investigated the stresses and soil deformations during ice gouging events and was a proprietary program designed to develop the engineering framework to allow for pipeline installation in arctic regions with the understanding of soil deformations and ice loads seen during ice gouging events. The program included a series of small scale physical model tests of ice gouging conducted in a geotechnical centrifuge. Centrifuge modeling provides an effective alternative to large scale physical models by stress scaling to study the mechanics of the ice gouging process.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.683
Threshold uncertainty score0.456

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0050.001
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.6830.335

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.164
Teacher spread0.161 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2010
Admission routes2
Has abstractyes

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