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Record W2902318854 · doi:10.1680/jgeot.17.p.116

Axial force–displacement behaviour of a buried pipeline in saturated and unsaturated sand

2018· article· en· W2902318854 on OpenAlexaff
Mohammed Al-Khazaali, Sai K. Vanapalli

Bibliographic record

VenueGéotechnique · 2018
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of Ottawa
FundersMinistère de l'Education Nationale, de l'Enseignement Superieur et de la Recherche
KeywordsPipeline transportGeotechnical engineeringPipeline (software)Water tablePetroleum engineeringGeologyGroundwaterEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Several pipeline projects have been proposed in the world in recent years owing to the rapid growth of the petroleum industry. Onshore pipeline systems are usually buried above the natural groundwater table, where the soil is typically in an unsaturated condition. Rational interpretation of these pipelines is possible by extending the mechanics of unsaturated soils. In this paper, the axial force exerted by way of the relative movement on a prototype steel pipeline in sand under both saturated and unsaturated conditions is determined from laboratory investigations using specially designed equipment. The test results under the unsaturated condition showed significantly higher axial force on the pipeline compared to the saturated condition, attributable to the contribution from matrix suction. Two analytical models proposed in this study, which take into account the influence of matrix suction and dilation, successfully predicted the peak and residual skin friction along the pipe surface. The framework developed, based on experimental studies and analysis of the results and the proposed models that use saturated shear strength parameters and the soil-water characteristic curve, is promising for generating simple tools for the design of pipeline infrastructure buried in sands to ensure their stability and safety, and at the same time provide economical solutions.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.145
Threshold uncertainty score0.682

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 head0.005
GPT teacher head0.215
Teacher spread0.209 · 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 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

Citations20
Published2018
Admission routes1
Has abstractyes

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