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Record W1805557289 · doi:10.1520/stp12530s

Resilient Modulus Testing Using Conventional Geotechnical Triaxial Equipment

2003· book-chapter· en· W1805557289 on OpenAlexaff
JM Konrad, C Robert

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicTunneling and Rock Mechanics
Canadian institutionsMinistry of Transportation of OntarioUniversité Laval
Fundersnot available
KeywordsGeotechnical engineeringTriaxial shear testModulusGeologyMaterials scienceComposite materialPetrologyShear (geology)

Abstract

fetched live from OpenAlex

This paper presents the results of a comprehensive laboratory investigation program on the mechanical properties of an unbound aggregate used in pavement base courses. Repeated load triaxial tests were used to assess the influence of test conditions (specimen size, degree of saturation, pulse loading and loading sequence) on resilient modulus. A conventional triaxial setup, used by most geotechnical laboratories, was adapted for the testing of 100-mm-diameter and 200-mm-high specimens. The material response under a sinusoidal variation of load was compared with the AASHTO procedure on larger samples and different pulse loading. The test program showed that the resilient modulus obtained from the different loading sequences agreed well for given density and moisture content conditions. Conventional triaxial equipment can be used to determine the resilient modulus of unbound aggregates provided accurate displacement gauges are used in the middle-third of the specimen.

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)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.049
GPT teacher head0.236
Teacher spread0.187 · 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

Citations2
Published2003
Admission routes1
Has abstractyes

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