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Record W1977774015 · doi:10.1520/gtj100511

A Large Diameter Triaxial Apparatus to Measure Pore Pressure and Displacements on a Pre-existing Shear Zone/Plane

2007· article· en· W1977774015 on OpenAlexaff
Xueqing Su, Dwayne D. Tannant, C. Derek Martin, Norbert R. Morgenstern, Gerry Cyre

Bibliographic record

VenueGeotechnical Testing Journal · 2007
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsUniversity of AlbertaGeological Survey of Canada
Fundersnot available
KeywordsShear (geology)Geotechnical engineeringPore water pressureGeologyTransducerTriaxial shear testPressure sensorShear rateSimple shearDirect shear testPermeability (electromagnetism)Displacement (psychology)Materials scienceComposite materialEngineeringRheologyPetrologyChemistry

Abstract

fetched live from OpenAlex

Abstract The development of an apparatus to measure pore pressure and displacements on a pre-existing shear zone/plane during triaxial testing is presented. The apparatus includes a newly developed 405-mm diameter triaxial cell, a miniature pore pressure transducer for monitoring shear-induced pore pressures, and a displacement transducer for measuring shear displacements. Tests were performed by mounting the pore pressure transducer onto the face of a pre-existing shear plane in the specimen and installing the displacement transducer inside the triaxial cell to monitor local deformations. The results reveal that pore pressures measured on the shear plane and the base of specimens of Athabasca clay, Highvale mudstone, and Fort McMurray highly weathered limestone are identical at a shear displacement rate equal or less than approximately 18 mm/day. This implies that when the shear displacement rate is less than about 18 mm/day for rocks/soils that have a permeability greater than 10−8∼10−9cm/s, the pore pressure obtained from in situinstrumentation, which may not be set exactly on the shear plane, can be used as the shear zone pore pressure.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.498
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.001
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 head0.030
GPT teacher head0.268
Teacher spread0.238 · 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 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
Published2007
Admission routes1
Has abstractyes

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