Interfacial fracture energy: an indicator of the adhesion of bituminous materials
Bibliographic record
Abstract
This paper demonstrates that the pressurized blister test can be an effective method to predict binder-aggregate bonding. Recently, the blister test has been introduced as a reliable approach to predict the bonding between bituminous sealant and aggregate. Since this test measures a geometry-independent parameter that is an inherent property of the interface, the test can be applied to any bituminous material, from the softest bituminous crack sealant to the most brittle binder. With very brittle material, cohesive failure becomes a concern. Such a failure can be easily prevented by an increase in the thickness of the adhesive specimen. However, an increase in specimen thickness also gives rise to shear forces that cannot be neglected in the analysis. Utilizing theoretical and experimental analyses, this paper presents the effect of shear forces on the interfacial fracture energy (IFE) of adhesive bituminous materials. The effect of shear forces on blister deflection is shown as a function of material thickness. In addition, the dependence of IFE of bituminous materials on temperature and rate of loading was investigated through laboratory testing. An optimum temperature and loading rate can be identified for each material where IFE is optimized. This may help select appropriate binder/sealant - aggregate pairs for improved performance under defined environmental conditions
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".