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Record W2145759549 · doi:10.1139/l2012-063

Estimation of tensile strains at the bottom of asphalt concrete layers under wheel loading using deflection basins from falling weight deflectometer tests

2012· article· en· W2145759549 on OpenAlexafffundvenue
Jean-Pascal Bilodeau, Guy Doré

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2012
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFalling weight deflectometerDeflection (physics)Ultimate tensile strengthStructural engineeringGeotechnical engineeringAsphaltFinite element methodAsphalt concreteModulusGeologyEngineeringMaterials scienceComposite materialSubgrade

Abstract

fetched live from OpenAlex

The falling weight deflectometer is a pavement analysis tool that is now widely used in the pavement engineering field. Using the backcalculation process and the measured deflection basin, the layers moduli can be determined and a mechanistic analysis of the pavement can be made. A new approach is proposed to bypass the necessity of the backcalculation by allowing a direct estimation of the tensile strain at the bottom of asphalt concrete using the deflection basin. A model based on a finite element theoretical pavement analysis is proposed for this purpose. Complementary models have been developed to use the proposed models without having to determine the layers moduli. The proposed model to estimate the tensile strain at the bottom of the asphalt concrete layers is validated and calibrated using data obtained on an instrumented experimental site.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.110
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.027
GPT teacher head0.245
Teacher spread0.218 · 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

Citations16
Published2012
Admission routes3
Has abstractyes

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