Three-Dimensional Linear Viscoelastic Properties of Two Bituminous Mixtures Made with the Same Binder
Bibliographic record
Abstract
Eiffage developed a high-performance bituminous mixture known as GB5. It is based on aggregate optimization method. This paper presents the results of a research project checking whether, in the small strain domain, this type of mixture behaves like the more conventional asphalt mixture GB3 currently used as a base layer in French bituminous pavements. Three-dimensional complex modulus tests are performed on GB5 and GB3, two hot mixtures asphalt (HMA) made with the same bitumen but produced with different aggregate skeletons. Tension-compression sinusoidal testing is applied to the specimens over a wide frequency and temperature range. Both axial and radial strains are monitored, thereby allowing the computation of the complex Young's modulus and complex Poisson's ratios. From the experimental results, the time–temperature superposition principle (TTSP) is verified for both complex Young's modulus and complex Poisson's ratios in two directions. The obtained shift factors and normalized complex modulus curves for the two mixtures indicate that the bitumen phase drives the viscoelastic behaviour of the asphalt mixture, regardless of the granular skeleton. The effect of air-void content on the static, glassy, and characteristic time values of modulus and Poisson's ratios, which is obtained from simulation using a linear viscoelastic model with two springs, two parabolic elements, one dashpot, is analyzed. The anisotropic properties of the two mixtures and the reproducibility between the two laboratories is also checked.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".