Numerical modelling of complex modulus tests on asphalt concrete using the 2D discrete element method
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".