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Record W4404797014 · doi:10.1139/cjce-2024-0100

Numerical modelling of complex modulus tests on asphalt concrete using the 2D discrete element method

2024· article· en· W4404797014 on OpenAlexvenueno aff
Léo Coulon, Georg Koval, Cyrille Chazallon, Jean-Noël Roux

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsDiscrete element methodAsphaltStructural engineeringAsphalt concreteModulusFinite element methodGeotechnical engineeringDynamic modulusEngineeringMaterials scienceComposite materialMechanics

Abstract

fetched live from OpenAlex

The VENoL analytical model was developed to reproduce the nonlinear viscoelastic behaviour of asphalt concrete in dynamic analysis. In this paper, it is integrated as a contact law in a 2D model using the discrete element method (DEM). The asphalt concrete is modelled on a macroscopic scale. The VENoL model is applied in the numerical code without any recalibration of its analytical parameters. Particular attention is paid to modelling variations in the Poisson’s ratio as a function of test conditions. This integration is checked by comparing the results of the numerical model with those extracted from the literature for complex modulus tests in direct tension–compression. Despite the use of a macroscopic scale, it appears that the model can reproduce porosity effects through the mechanisms of DEM. Using the same set of parameters, two-point bending tests are also conducted to ensure their compliance in the characterisation of bituminous mixes.

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: none
Teacher disagreement score0.957
Threshold uncertainty score0.692

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 communication0.0000.000
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 head0.048
GPT teacher head0.280
Teacher spread0.232 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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