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Record W2031496089 · doi:10.1520/jte20120338

Computer-Automated Triaxial Testing System for Assessing and Mitigating Sample Disturbance in a Natural Clay in the Laboratory

2013· article· en· W2031496089 on OpenAlexaboutno aff
Tanay Karademir

Bibliographic record

VenueJournal of Testing and Evaluation · 2013
Typearticle
Languageen
FieldEngineering
TopicSoil and Unsaturated Flow
Canadian institutionsnot available
Fundersnot available
KeywordsDisturbance (geology)Geotechnical engineeringSample (material)Triaxial shear testEnvironmental scienceEngineeringGeologyMaterials scienceComposite materialChemistryChromatography

Abstract

fetched live from OpenAlex

Abstract A computer automation for a manual triaxial cell involved in designing new test instrumentation components and connections and in developing new controller software and supportive hardware for accurate functioning of the system during long test durations was undertaken to run high-quality, sophisticated triaxial tests for measuring the stress-strain properties of clays. For validation and further evaluation of the developed computer-automated triaxial testing system, a laboratory testing program was performed to investigate the effects of sample disturbance on laboratory-measured clay soil behavior and the mitigation of disturbance effects in the laboratory using two reconsolidation methods, the stress history and normalized soil properties (SHANSEP) method and the recompression method. Computer-automated triaxial tests were performed on specimens of Boston blue clay (BBC) from a test site (Newbury, MA) sampled using a Sherbrooke-type block sampler. The test results from the laboratory testing program are presented, including for (i) one-dimensionally consolidated undrained compression (CKoUC) tests on both normally consolidated (NC) and mechanically overconsolidated (OC) specimens using the SHANSEP method and (ii) anisotropically consolidated undrained compression (CAUC) tests using the recompression method. The CKoUC(NC) tests were performed to provide baseline SHANSEP data, and results were compared between CKoUC(OC) SHANSEP and CAUC recompression tests.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.589
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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 head0.037
GPT teacher head0.284
Teacher spread0.247 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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