A 9-Year Evaluation of Field Cracking and Rutting Performance of SPS-9 Superpave Experiment
Bibliographic record
Abstract
Though the first of 26 Specific Pavement Study 9 (SPS-9) experiments was built more than 9 years ago to assess the field performance of the Superpave® asphalt and mix design and analysis system, there has been no definitive report on the experiment's overall field performance. This analysis therefore evaluates the performance of the SPS-9 experiments through the use of the 2001 distress data available from the Long-Term Pavement Performance information management system database. Field distresses evaluated in this study included rutting, fatigue cracking, longitudinal wheelpath and nonwheelpath cracking, and transverse cracking. In addition to the field distress evaluation, a statistical analysis was conducted to determine whether a performance difference exists between the Superpave "correct" performance-graded (PG) binder section and the Superpave alternative PG binder section designed to exhibit early distress at each of the SPS-9 sites. The statistical analysis relates the distresses through means ( t-test) and variances ( F-test). The data analysis indicates that more than 78% of the Superpave sections have no cracking and more than 80% have only nominal rutting. When cracking occurred, fatigue and longitudinal nonwheelpath cracking were the predominant distresses. For the Superpave binder sections, distresses began to appear within 4 years of construction, with overlays outperforming new pavements and agency sections performing as well as or better than Superpave sections. Surprisingly, the results of the t-test and the F-test analysis showed no statistical difference (at the 95% confidence level) in the fatigue cracking, longitudinal wheelpath cracking, longitudinal nonwheelpath cracking, and rutting distresses between the Superpave binder sections and the Superpave alternative binder sections. However, a statistical difference (based on the F-test) existed for transverse cracking performance between the two PG binder sections.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".