MétaCan
Menu
Back to cohort
Record W2128794541 · doi:10.1139/cgj-2014-0029

Soil-buried pipeline interaction for vertical downwards relative offset

2014· article· en· W2128794541 on OpenAlexvenueno aff
George Kouretzis, K. Krabbenhøft, Daichao Sheng, Scott W. Sloan

Bibliographic record

VenueCanadian Geotechnical Journal · 2014
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsTrenchOffset (computer science)Pipeline transportGeotechnical engineeringLimit analysisFinite element methodPipeline (software)Structural engineeringSoil structure interactionPileEngineeringGeologyComputer scienceMaterials science

Abstract

fetched live from OpenAlex

A new perspective is presented on the interaction effects for the vertical downwards offset of a pipeline relative to its surrounding soil. Instead of estimating the interaction force via shallow footing bearing capacity theory, as per common pipeline design practice, we assume that the vertical movement of the pipeline in uniform soil is governed by mechanisms similar to the lateral loading of a circular pile up to its limit load. The validity of this assumption is investigated numerically with the finite element limit analysis method, and design expressions are derived for the maximum interaction force on pipelines embedded in cohesive and granular soils. For the common case of buried pipelines built in sand-backfilled trenches, the same numerical method is employed to determine the necessary trench dimensions so as to avoid interaction with the possibly much stiffer native soil that results in a significant increase in the force applied on the pipeline during ground movement. The described approach can be employed in project-specific analyses to optimize trench dimensions, and thus avoid unnecessary excavation costs or mitigation measures.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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 designBench or experimental
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

Citations44
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Geotechnical JournalSame topicGeotechnical Engineering and Underground StructuresFrench-language works237,207