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Record W2094901896 · doi:10.1061/9780784413272.363

Large-Scale Shear Testing of Tire-Derived Aggregates (TDA)

2014· article· en· W2094901896 on OpenAlexaff
Ming Xiao, Martin Ledezma, Corbin Hartman

Bibliographic record

VenueGeo-Congress 2014 Technical Papers · 2014
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsPetro Geotech (Canada)
FundersCalifornia State University, Fresno
KeywordsShear (geology)Mohr–Coulomb theoryDirect shear testGeotechnical engineeringCohesion (chemistry)Shear stressMaterials scienceShearing (physics)Critical resolved shear stressRepeatabilityTriaxial shear testGeologyPure shearSimple shearShear rateComposite materialStructural engineeringEngineeringMathematicsFinite element methodRheology

Abstract

fetched live from OpenAlex

This paper reports a large-scale direct shear testing of tire-derived aggregates (TDA) of large sizes (25 to 75 mm). TDA are pieces of processed and shredded waste tires that can be used as lightweight and quick fills for embankments, subgrades, and retaining wall backfills. A large-scale direct shear apparatus was built to obtain the shear strength of the large-sized material. The shear box dimensions were 78 cm wide, 80 cm long, and 122 cm tall. The lower shear box was driven by a hydraulic piston, while the upper shear box remained stationary. The horizontal shear forces, shear displacements, and vertical forces were recorded by an automatic data acquisition system. Four normal loads were applied on the TDA to simulate overburden pressures of 24, 48, 96, and 144 kPa (or 500, 1000, 2000, and 3000 lb/ft2). Duplicate tests were performed to verify the repeatability. Under each normal stress, the shear stress vs. deformation curve was plotted, and the maximum shear stress was obtained. Mohr-Coulomb failure criterion was developed, and the cohesion and friction angle were obtained.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.316
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.006
GPT teacher head0.197
Teacher spread0.190 · 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.

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

Citations2
Published2014
Admission routes1
Has abstractyes

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