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Record W2089134388 · doi:10.1139/t06-079

The use of tangent stiffness to characterize the resilient response of unbound crushed aggregates

2006· article· en· W2089134388 on OpenAlexvenueno aff
J.‐M. Konrad

Bibliographic record

VenueCanadian Geotechnical Journal · 2006
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsnot available
Fundersnot available
KeywordsStress pathStiffnessTangentTangent stiffness matrixTangent modulusGeotechnical engineeringOverburden pressureStress (linguistics)Materials scienceStructural engineeringModulusDissipation factorCompactionMathematicsShear (geology)GeologyEngineeringComposite materialGeometryStiffness matrix

Abstract

fetched live from OpenAlex

Repeated-load triaxial tests were conducted on crushed granitic base-course material to study the resilient response under different stress paths and compaction states. It has been established that the resilient response of this prestrained unbound granular material is best defined in terms of tangent stiffness (Et) and vertical stress (σv). The data also revealed the existence of a threshold value of tangent stiffness that is essentially dependent on initial confining stress for a given compaction state. When the tangent modulus exceeds this threshold value, a unique relationship between tangent stiffness and vertical stress exists for mobilized shear resistance ratios less than 0.4. This Et–σv relationship is independent of stress path. A simple power law model can be used to predict the resilient response of unbound base-course material and an approximate value of resilient modulus for any desired stress path and initial stress condition. The use of the tangent stiffness – vertical stress model for pavement design appears to be very promising.Key words: granular, material, resilient modulus, triaxial, stress path.

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)0.002
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 score0.997
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.197
Teacher spread0.183 · 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

Citations4
Published2006
Admission routes1
Has abstractyes

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