Characterization of the coefficient of thermal expansion and its effect on the performance of Portland cement concrete pavements
Bibliographic record
Abstract
The coefficient of thermal expansion (CTE) of concrete is considered to be an important design parameter to predict Portland cement concrete (PCC) pavement performance in mechanistic-empirical pavement design guide (MEPDG). This study measured CTE values of concrete specimens having various coarse aggregates, and investigated the relationship between the CTE and critical design parameters. It was found that aggregate types, the amount of coarse aggregate, and relative humidity (RH) had a statistically significant impact on the CTE. Expansion CTE had a higher variation compared to contraction CTE, and the maximum value of expansion CTE at 63% RH was 8% higher than the value at 100% RH. Sensitivity analysis showed that inaccurate estimation of concrete CTE can cause serious error in predicting the performance of PCC pavements. A prediction equation of concrete CTE was introduced by modifying Hansen’s model and the predicted CTE value had a good agreement with the measured CTE.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".