EXPLORING THE MASTER CURVE PARAMETERS FOR EFFICIENT PERFORMANCE GRADING OF ASPHALT BINDERS FROM THE UNITED STATES OF AMERICA
Bibliographic record
Abstract
The importance of road infrastructure for national economic development is undeniable. However, countries like the United States of America (USA), with cold climates, face challenges in achieving long-term performance with asphalt pavements. Therefore, attention should be paid to the asphalt binder acceptance criteria used, and concerted efforts are required to develop and design test methods with high accuracy, sensitivity, repeatability, and reproducibility. Testing 39 asphalt binders from nine USA states across three different regions was representative of a wide range of binders. This study utilized Dynamic Shear Rheometer (DSR) testing to obtain rheological indicators such as Tδ=30°, Tδ=45°, Intermediate Temperature Performance Grade (ITPG), and master curve parameters under slow and fast cooling rates. Significant correlations between DSR indicators at different cooling rates were observed. Considering efficiency in time consumption, fast cooling emerges as the preferred method for DSR testing. The Extended Bending Beam Rheometer (EBBR) test is used to determine low-temperature cracking performance, and the Double-Edge-Notched Tension (DENT) test is used to measure the ductile strain tolerance. These tests are time consuming and require a larger sample quantity, even though they are rigorous and accurate. Hence, the study also evaluated the feasibility of using DSR indicators at different cooling rates as an alternative to the laborious EBBR and DENT tests. For this set of USA binders, Tδ=30°, Tδ=45°, and ITPG serve as viable alternatives for EBBR Limiting Low-Temperature Performance Grade (LLTPG). Grade loss from EBBR indicates thermo-reversible aging due to oil exudation in asphalt, surpassing DSR's capabilities, thus, DSR indicators cannot replace grade loss. The Tδ=30°, Tδ=45°, and ITPG demonstrated a reasonable correlation with the critical Crack Tip Opening Displacement (CTOD) obtained from the DENT test. Due to the wide variety of asphalt binders in the USA, the correlations for this set of USA binders deviated from those of previously tested Ontario binders, primarily because USA binders are harder while Ontario binders are softer. None of the master curve parameters proved sufficient substitutes for the EBBR or DENT test indicators. Black space diagrams were used to classify binders as thermo-rheologically simple or complex. The chemical characterization of asphalt binders was done using X-Ray Fluorescence (XRF), Nuclear Magnetic Resonance (NMR), and Fourier Transform Infrared (FTIR) spectroscopies. XRF detects recycled engine oil addition, NMR correlates low-temperature performance grade from the bending beam rheometer with the relative average length of the paraffinic internal methylene chain, and FTIR shows changes in quantity of functional groups with binder aging.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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 | 0.001 |
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".