EVALUATION OF PHASE ANGLE AS A PRACTICAL PARAMETER FOR LOW TEMPERATURE SPECIFICATION GRADING OF ASPHALT BINDERS
Bibliographic record
Abstract
The importance of road and highway systems in the development of a nation’s economy cannot be overemphasized. Over the years, concerted efforts have been made by researchers to develop and design test methods with high accuracy, repeatability, and reproducibility. The goal is to reduce pavement failures and the high cost of road construction and rehabilitation. Current low temperature performance tests such as the bending beam rheometer (BBR) and extended BBR (EBBR) tests are not without limitations. They could be time-consuming and require more sample quantity even though they are rigorous and accurate. Hence, this study aims to examine the viability of limiting phase angle measurement as a credible alternative to the laborious extended BBR (EBBR) procedure. In this study, a total of 239 samples were tested from various agencies and are grouped into tank samples, core samples and loose mix samples. Agency A and Agency B were carefully examined to ensure climatic and traffic requirements are met. High temperature performance grade (HTPG), intermediate temperature performance grade (ITPG), regular bending beam rheometer (BBR), extended bending beam rheometer (EBBR) tests were carried out on the samples. In addition to this, the data obtained from each test were correlated with limiting phase angle temperature [T(30°), T(45°)]. From the study, Agency B largely met the climatic and traffic requirements when compared with Agency A, due to a much more effective approach adopted by the agency. Furthermore, correlation studies involving ITPG, BBR, and EBBR with limiting phase angle temperature showed that core samples have the highest correlation followed by loose mix samples and tank samples. From the large data set used in this study, it is more evident that the limiting phase angle measurement is a viable alternative to evaluate the thermal cracking performance of binders because of its higher sensitivity, easier experimental procedure, and smaller sample quantity requirement.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.002 | 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".