Early-Age Stiffening of Cold Recycled Bituminous Materials Using Shear Wave Velocity
Bibliographic record
Abstract
ABSTRACT The characterization of cold recycled bituminous materials (CRMs) at a very young age, shortly after compaction, is inherently challenging due to the nature of the material. The granular aspect of CRM at this stage and its high-water content render the use of conventional mechanical techniques impractical. Following previous work, the use of a nondestructive technique based on the frequency analysis of mechanical elastic shear waves, piezoelectric ring actuator technique (P-RAT), has enabled assessment of the behavior of cold in-place recycled material treated with bitumen emulsion from 10 min after compaction to 30 days of curing. Emphasis on shear wave velocity (Vs) measurements during the early age confirmed the rapid stiffening of the mix along with the departure of water present in the mix. A 6 °C drop of the surface temperature is observed along with this rapid increase of Vs and water loss. The initial and final Vs values range from 287 to 330 m s−1 and from 461 to 578 m s−1, respectively. To assess the capabilities of P-RAT, specimens with different void contents were tested, mainly 12, 15, and 17 %. It was observed that in each tested specimens, a similar behavior was exhibited during the first few hours of curing. Based on these observations, hypotheses are put forth regarding the phenomena governing the increase in stiffness during this period. Finally, the influence of the compaction of the specimens on the Vs values is consistent and comparable with the information available in the literature for such CRM.
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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) | 0.001 | 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".