MétaCan
Menu
Back to cohort
Record W2887552978 · doi:10.1139/cgj-2018-0208

Lateral resistance of “rigid” pipelines and cables on rocky seabeds

2018· article· en· W2887552978 on OpenAlexvenueno aff
Terry Griffiths, David White, Scott Draper, Adam Leighton, Liang Cheng, Hongwei An, Antonino Fogliani

Bibliographic record

VenueCanadian Geotechnical Journal · 2018
Typearticle
Languageen
FieldEngineering
TopicMechanical stress and fatigue analysis
Canadian institutionsnot available
FundersEngineering and Physical Sciences Research CouncilLloyd's RegisterAustralian Government
KeywordsSeabedSubseaGeotechnical engineeringPipeline transportFriction coefficientCoefficient of frictionCoulomb frictionCurrent (fluid)Stress (linguistics)Offshore geotechnical engineeringDeformation (meteorology)GeologyMaterials scienceEnvironmental scienceComposite material

Abstract

fetched live from OpenAlex

Accurate assessment of lateral resistance is critical to ensure the on-bottom stability and integrity of subsea pipelines and cables in the oil–gas and marine renewable energy industries. However, on rocky seabeds recommended practices provide limited recommendations on pipe–seabed interaction, suggesting only a single value for the friction coefficient of 0.6. This paper reports on a programme of physical experiments and theoretical modelling investigating the lateral resistance of pipes on rocky seabeds. It is shown that the peak and mean effective friction can significantly exceed the interface (or Coulomb) friction coefficient when the pipe diameter (D) is similar to the median rock diameter (d n50 ). Only when the pipe diameter becomes large compared to the rock size does the mean effective friction approach the interface friction. The effective friction coefficient was found to vary with variability in rock size and shape, as well as the length of pipe relative to median rock diameter. Each of these findings is reproduced well using the theoretical model. Collectively, the results demonstrate that the effective lateral friction coefficient may be higher than 0.6 for mean friction, and significantly higher for peak friction. This implies that inaccuracy may exist in current design, which may be rectified using the theoretical model.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.010
GPT teacher head0.207
Teacher spread0.197 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations13
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicMechanical stress and fatigue analysisFrench-language works237,207