Survival Analysis of Thin Overlay and Chip Seal Treatments Using the Long-Term Pavement Performance Data
Bibliographic record
Abstract
Pavement preservation treatments are widely used to retard future deterioration, and maintain and improve the functional condition of the system, without substantially increasing pavement structural capacity. This paper provides an empirical assessment of the longevity of two commonly used preservation treatments for hot-mix asphalt (HMA) pavements: thin overlay (0.5 in. to 2 in. in thickness) and chip seal. The data used in this study were extracted from the Long-Term Pavement Performance (LTPP) database and covered 40 States and eight Canadian Provinces. Failure curves (also called survival curves) and mathematical models were developed for these treatment types to estimate their life expectancies and probability of failure at any given age or carried cumulative traffic loading. To account for the effect of climate on treatment performance, separate failure curves were developed for four climatic zones--dry freeze, dry non-freeze, wet freeze, and wet non-freeze. The median life expectancy is 7 to 9.5 years for thin overlays and 3.5 to 10 years for chip seals, depending on which climatic zone the treatment is located in. In terms of traffic loading, the median life expectancy is 1,500 to 8,000 cumulative KESALs for thin overlays and 500 to 2,000 cumulative KESALs for chip seals, depending on the climatic zone of the treatment [1 KESALs = 1,000 equivalent single-axle load (ESAL)]. The wide range in treatment life expectancy among the four climatic zones signifies the effect of climate on the performance of thin overlays and chip seals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".