Evaluation of factors affecting tack coat bond strength
Bibliographic record
Abstract
Different types of distress occur in asphalt concrete pavements due to lack of bonding between existing old layer and overlay. Therefore, this paper evaluates the bonding strength between sand asphalt mixture as overlay and roller compacted concrete (RCC) as the existing layer. Four types of tack coat including crumb rubber modified (CRM), grade 60/70 binder, cationic slow-setting (CSS), and cationic rapid-setting (CRS) emulsion were considered, with 200, 400, and 600 g/m 2 dosages. Different RCC surface temperatures including 0, 25, and 60 °C were chosen to evaluate the effect of ambient temperature on the bonding strength. Results showed that CRM and 60/70 binders have higher bonding strength in comparison to emulsions. The bonding strength at 0 °C for all types of tack coat was significantly lower than other temperatures. The optimum application rates of 200 g/m 2 and 400 g/m 2 were selected for the CSS and CRS emulsified binders respectively. The optimum application rate for the 60/70 and CRM binders was selected as 600 g/m 2 .
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".