Application of recycled waste aggregate to lean concrete subbase in highway pavement
Bibliographic record
Abstract
As aggregates recycled from various types of construction waste are continuously being produced, interest has focused on how to apply them for use in highway pavement. This paper considers the application of waste aggregates to lean concrete, based on basic mechanical property tests and environmental toxicity. Compared with natural aggregates, waste aggregates derived mainly from recycled concrete have low specific gravity and high water absorption characteristics. After testing their environmental toxicity, it was found that waste aggregates do not release any metallic ions when introduced to alkaline conditions but do release a small but seemingly harmless amount of metallic ions when introduced to acidic solutions. Concrete made with waste aggregates has significant limitations in strength, particularly flexural strength, which is the main parameter of quality control and design for concrete pavement. It is therefore not practical to use waste aggregates for the surface layer of concrete without using additives or special treatments. It is possible, however, to apply concrete with waste aggregates for lean bases. In testing, lumps of asphalt, cement paste, bricks, and glass were classified as impurities and were observed for changes in strength based on the percentage of impurities used. If the amount of impurities is greater than 25%, the 7-d compressive strength does not meet the strength requirements specified for lean concrete.Key words: recycled waste aggregates, lean concrete, impurity content, concrete pavement.
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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 | 0.000 | 0.000 |
| 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".