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Record W2516143570 · doi:10.1139/cgj-2016-0059

Multi-directional force–displacement response of underground pipe in sand

2016· article· en· W2516143570 on OpenAlexvenueno aff
Jai K. Jung, Thomas D. O’Rourke, Christina Argyrou

Bibliographic record

VenueCanadian Geotechnical Journal · 2016
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
FundersDivision of Civil, Mechanical and Manufacturing InnovationNational Science Foundation
KeywordsGeotechnical engineeringGeologyDimensionless quantityDisplacement (psychology)Pipeline transportSlip (aerodynamics)MechanicsEngineering

Abstract

fetched live from OpenAlex

A methodology is presented to evaluate multi-directional force–displacement relationships for soil–pipeline interaction analysis and design. Large-scale tests of soil reaction to pipe lateral and uplift movement in dry and partially saturated sand are used to validate plane strain, finite element (FE) soil, and pipe continuum models. The FE models are then used to characterize force versus displacement performance for lateral, vertical upward, vertical downward, and oblique orientations of pipeline movement in soil. Using the force versus displacement relationships, the analytical results for pipeline response to strike-slip fault rupture are shown to compare favorably with the results of large-scale tests in which strike-slip fault movement was imposed on 250 and 400 mm diameter high-density polyethylene pipelines in partially saturated sand. Analytical results normalized with respect to maximum lateral force are provided on 360° plots to predict maximum pipe loads for any movement direction. The resulting methodology and dimensionless plots are applicable for underground pipelines and conduits at any depth, subjected to relative soil movement in any direction in dry or saturated and partially saturated medium to very dense sands.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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

Citations89
Published2016
Admission routes1
Has abstractyes

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