Evaluation of the Characteristics of Recycled Aggregates Produced in Campinas-SP/Brazil
Bibliographic record
Abstract
To use the aggregate generated by recycling plants in the production of concrete, it is essential to know its characteristics. This paper aims to evaluate samples of recycled aggregates, both small and large, produced at two recycling plants located in the city of Campinas, SP, Brazil, comparing the results with parameters established by NBR 15116:2004 and with the characteristics of the natural aggregates used in the production of concrete. For the development of the study, samples of aggregates, small and large, both natural and recycled were collected, which had their characteristics determined and evaluated according to the specifications of NBRs 7211:2009 and 15116:2004. The results indicate that even the recycled aggregates showing some variability throughout the tests and unfulfilled with some normative specifications, it is concluded that their use in concrete is close to becoming feasible. It was verified that simple corrections in the recycling plants or additions of a certain amount of natural aggregate, would probably already be enough for the total standardization of the recycled aggregate. Comparing the recycled aggregates with the natural ones it was verified that the recycled ones present a higher index of fines and mainly greater absorption of water, which reflects in smaller values of specific mass, apparent specific mass and crushing resistance. However, these are not limiting factors in the use of recycled materials in concretes without structural function, since they will not be so mechanically required.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".