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Record W2086418404 · doi:10.1520/jte20130049

Advanced Testing and Characterization of Shear Modulus and Deformation Characteristics of Oil Sand Materials

2014· article· en· W2086418404 on OpenAlexaboutno aff
Joseph Anochie-Boateng, Erol Tutumluer

Bibliographic record

VenueJournal of Testing and Evaluation · 2014
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsGeotechnical engineeringAsphaltTriaxial shear testOil sandsShear modulusSubgradeDirect shear testShear (geology)Materials scienceLaboratory testCharacterization (materials science)Deformation (meteorology)GeologyComposite materialPetroleum engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Oil sands are natural deposits of sand materials that are rich in bitumen. Limited studies have been conducted to determine the dynamic behavior of oil sand materials. Recent difficulties encountered in oil sand mine fields in Canada substantiated the need to characterize the stress dependent, visco-elastic, and plastic behavior of oil sand materials under dynamic loading of off-road construction and mining equipment. This paper introduces a new cyclic triaxial test procedure for determining shear modulus and deformation characteristics of oil sand materials. The test procedure was used to characterize shear moduli of three oil sand materials with varying bitumen contents. From the test results, nonlinear shear modulus models were successfully developed to characterize temperature and stress dependent behavior of the tested oil sand materials. The research findings indicate that the new laboratory approach is an improvement on conventional tests, especially when oil sand materials need to be evaluated in the field for subgrade construction and equipment mobility.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.702
Threshold uncertainty score0.278

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 integrity0.0000.000
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 head0.016
GPT teacher head0.229
Teacher spread0.213 · 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

Citations2
Published2014
Admission routes1
Has abstractyes

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