Development of a Viscosity Specification for Hot-Poured Bituminous Sealants
Bibliographic record
Abstract
Abstract Current crack sealant specifications focus on using simple empirical tests such as penetration, resilience, flow, and bonding to cement concrete briquettes (ASTM D 6690) [1] to measure the ability of the material to resist cohesive and adhesive failures. There is, however, no indication of the pertinence of these standard tests to predict the success of field installation and sealant performance. In an effort to bridge the gap between sealant fundamental properties and field performance, performance-based guidelines for the selection of hot-poured crack sealants are currently being developed. This paper proposes a new viscosity test procedure to help assess the propensity of sealants to wet the crack surface during installation. The proposed procedure calls for the use of a Brookfield rotational viscometer equipped with a modified spindle rod and an SC4-27 spindle at a speed of 60 r/min. Sealants are heated 20 min at the recommended installation temperature and the viscosity is measured after 30 s of spindle rotation in the hot sealant. These experimental conditions provide viscosities representative of sealant viscosity at shear rates during field application. The repeatability for within laboratory and between laboratories was found to be 5.4 and 17 %, respectively. This repeatability is comparable with the corresponding variability of the SuperPave viscosity test for asphalt binders.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".