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Record W4225708637 · doi:10.31224/osf.io/ea37m

Lateral force-displacement response of buried pipes in slopes

2021· preprint· en· W4225708637 on OpenAlexafffund
Mohammad Katebi, Dharma Wijewickreme, Pooneh Maghoul, Kshama Roy

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of British ColumbiaUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsGeotechnical engineeringDisplacement (psychology)GeologyFinite element methodStructural engineeringEngineering

Abstract

fetched live from OpenAlex

A series of full-scale experiments were conducted to estimate lateral soil constraints on the pipes buried in dense sandy slopes at different burial depths. The experimental data indicated that the soil force on the pipe increases with increasing the slope grade and burial depth ratio. The lateral soil force versus relative pipe displacement response observed from the experiments is presented and compared to those arising from level ground conditions. The study was extended to larger burial depth ratios by simulating pipes under sloping ground conditions using a numerical (finite element) model that was initially calibrated using the results from physical modelling. The findings from the study in terms of the variation of peak lateral soil restraint as a function of the slope grade and burial depth ratio are presented for consideration in pipeline design.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.216
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 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

Citations0
Published2021
Admission routes2
Has abstractyes

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