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Record W1713566447 · doi:10.1139/l2012-031

Comparative study on the impact of wide base tires and dual tires on the strains occurring within flexible pavements asphalt concrete surface course

2012· article· en· W1713566447 on OpenAlexaffvenue
Damien Grellet, Guy Doré, Jean-Pascal Bilodeau

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsWearing courseBase courseAsphaltCourse (navigation)Asphalt concreteEngineeringAsphalt pavementForensic engineeringGeotechnical engineeringCivil engineeringStructural engineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Complex and variable solicitations from climate and traffic greatly impact pavements performance and therefore user’s safety and comfort. As the effect of traffic is related to the strains induced in the pavement structures, this study objective is to determine if changing conventional dual tires to wide base single tires may impact significantly strains in flexible pavements. This paper documents an experimental investigation of strain induced close to the edge of the tire and under the tire. Two pavement structures and two climate conditions have been tested. For each test section, optical fiber strain gauges fixed on asphalt concrete cores are installed within the asphalt concrete pavement layer. This is a retrofit technique that allows measuring strains in the upper and lower part of the asphalt layer. The experiment led to the following observations: wide base single tires cause a 14 to 30% increase of the tensile strains at the bottom of the asphalt concrete layer but cause a 20% decrease of the ten...

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)0.000
metaresearch head score (Gemma)0.000
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.047
GPT teacher head0.289
Teacher spread0.242 · 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

Citations20
Published2012
Admission routes2
Has abstractyes

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Same venueCanadian Journal of Civil EngineeringSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207