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Record W2103307654 · doi:10.1139/t07-037

Large-scale modelling of soil–pipe interaction during large amplitude cyclic movements of partially embedded pipelines

2007· article· en· W2103307654 on OpenAlexvenueno aff
C.Y. Cheuk, David White, M. D. Bolton

Bibliographic record

VenueCanadian Geotechnical Journal · 2007
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsBermGeotechnical engineeringPipeline transportSubmarine pipelineDisplacement (psychology)GeologySeabedLateral movementEngineeringStructural engineeringMechanical engineering

Abstract

fetched live from OpenAlex

As the development of offshore hydrocarbons moves into deeper water, pipelines form an increasingly significant part of the required infrastructure. High-temperature high-pressure pipelines must be designed to accommodate thermal expansion and potential lateral buckling. A novel design approach is to control the formation of pre-engineered lateral buckles to relieve the expansion. The amplitude of these buckles is typically several pipe diameters. Assessment of the force–displacement interaction between the on-bottom pipeline and the seabed is crucial for design. A series of large-scale plane strain model tests has been conducted to measure the response of a pipe segment partially embedded in soft clay, during large amplitude cyclic movements, mimicking consecutive thermal expansion and contraction at a bend in a pipeline. Four key stages in the force–displacement response have been identified: (i) breakout, (ii) suction release, (iii) resistance against a steadily growing active berm, and (iv) additional resistance during collection of a pre-existing dormant berm. A simple upper bound solution is proposed to model the observed response. This solution captures the experimental trends including growth of the active berm and collection of dormant berms. This approach is the first attempt to quantitatively model the mechanisms underlying the response during large-displacement lateral sweeps of an on-bottom pipeline, accounting for the growth of soil berms.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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

Citations51
Published2007
Admission routes1
Has abstractyes

Explore more

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