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Record W568764585

Rutting Behaviour of Flexible Pavements Aggregate Bases Measured with Small-Scale Laboratory Heavy Vehicle Simulator

2012· article· en· W568764585 on OpenAlexaboutno aff
Jean-Pascal Bilodeau, Guy Doré, Jonas Depatie, Joannie Poupart

Bibliographic record

Venue2012 CONFERENCE AND EXHIBITION OF THE TRANSPORTATION ASSOCIATION OF CANADA - TRANSPORTATION: INNOVATIONS AND OPPORTUNITIES · 2012
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Soil Stabilization
Canadian institutionsnot available
Fundersnot available
KeywordsRutGeogridAggregate (composite)Geotechnical engineeringReinforcementEngineeringDeformation (meteorology)Frost (temperature)GeotextileEnvironmental scienceStructural engineeringMaterials scienceAsphaltComposite material
DOInot available

Abstract

fetched live from OpenAlex

Rutting of flexible pavement structures when submitted to repeated heavy-vehicle loading is a complex phenomenon. In northern environment where thick granular layers are included in flexible pavement structures to reduce frost action, most of surface rutting occurs in unbound granular materials. This long-term permanent deformation damage can be studied with heavy vehicle simulator. A small-scale laboratory heavy vehicle simulator was developed at Laval University over the last few years and this paper presents the first results obtained for the characterization of the rutting behavior of flexible pavement bases. Standard aggregate bases, as well as base layers containing 70 percent RAP and geogrid were tested. The results obtained are in good agreement with literature on permanent deformation and geogrid reinforcement. The rutting sensitivity of RAP bases is compared to standard aggregate base layer and the structure behavior improvement caused by the geogrid is also quantified. (A) For the covering abstract of this conference see ITRD record number 201211RT334E.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.023
GPT teacher head0.194
Teacher spread0.171 · 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 designObservational
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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venue2012 CONFERENCE AND EXHIBITION OF THE TRANSPORTATION ASSOCIATION OF CANADA - TRANSPORTATION: INNOVATIONS AND OPPORTUNITIESSame topicGeotechnical Engineering and Soil StabilizationFrench-language works237,207