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Record W2568884189 · doi:10.1115/ipc2016-64100

Some Observations on Soil-Pipe Interface Shear Strength in Direct Shear Under Low Effective Normal Stresses and Large Displacements

2016· article· en· W2568884189 on OpenAlexaff
Ruslan S. Amarasinghe, Dharma Wijewickreme, Hisham T. Eid

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of British Columbia
FundersQatar National Research Fund
KeywordsDirect shear testShear (geology)Materials scienceSoil waterShear stressGeotechnical engineeringGeologyComposite materialSoil science

Abstract

fetched live from OpenAlex

Experimental work is undertaken at the University of British Columbia (UBC) to study the soil-pipe interface shear strength at levels of shear displacements and effective normal stresses typically encountered in offshore soil-pipe interaction problems. A macro-scale interface direct shear apparatus having a test specimen footprint of 1.72 m × 1.75 m was designed and built for this purpose. The apparatus is capable of testing various soil-pipe interfaces under effective normal stresses in the range of 3 kPa to 6 kPa. A maximum shear displacement of 1.2 m is achievable at rates ranging from 0.1 μm/s to 1 mm/s. Sensors mounted at the interface enable the accurate determination of the effective normal stress at the interface when fully saturated fine-grained soils are tested. This paper presents some observations arising from a series of interface direct shear tests involving fine-grained soils of different plasticity against bare and epoxy coated steel surfaces.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 science0.0000.000
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 head0.006
GPT teacher head0.216
Teacher spread0.210 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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