Assessment of Anisotropy in Cold In-Place Recycled Materials Using Shear Wave Velocity and Computed Tomography Analysis
Bibliographic record
Abstract
Pavement materials like hot mix asphalt (HMA) and cold recycled mixes (CRMs) are typically considered isotropic. This study evaluates the anisotropy of a cold in-place recycled (CIR) material using the shear wave velocity (Vs) parameter. The piezoelectric ring actuator technique (P-RAT) is utilized to assess the Vs parameter in three directions in CIR slabs. Similarly, the ultrasonic pulse velocity (UPV) technique is employed to measure P-wave velocities. Both methods evaluate mechanical properties in multiple directions. Complex modulus tests are conducted to link velocities results to |E*| modulus. Finally, computed tomography (CT) scans are performed on the specimens in order to evaluate anisotropy resulting from aggregate alignment. The Vs obtained using P-RAT and the Vp from UPV indicate anisotropy, as the wave velocities differ across the three directions. Differences range from 0.6 to 11.6% in Vs, influenced by measurement location. UPV results are analysed in relation to the |E*| modulus master curves, demonstrating that the first peak arrival time for the P-wave corresponds with the master curve. CT scan analysis reveals that the aggregates tend to be more aligned in the direction of the compacting wheel’s displacement, which also highlights anisotropy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".