Strength Properties of Pervious Concrete Made with Locally Produced Recycled Coarse Aggregate
Bibliographic record
Abstract
Pervious concrete is a special type of concrete that addresses critical environmental issues and supports green, sustainable construction.In such concrete, little or no sand is employed in the mix in order to allow the formation of considerable void content leading to high permeability.In this study, seven pervious concrete mixes made with recycled coarse aggregate and containing different amount of natural fine aggregate are tested in the laboratory for their strength.The source of the coarse aggregate is demolished old concrete buildings in the United Arab Emirates.One of the mixes contains 100% natural coarse aggregate without natural sand, another 100% recycled coarse aggregate without natural sand, and the remaining 5 mixes include both recycled coarse aggregate and fine natural aggregate such that the amount of fine-to-coarse aggregate is 1.5-11.7%.Results of the study revealed that that the use of recycled coarse aggregate in pervious concrete without fine aggregate reduced the compressive strength by 36% and tensile strength by 57%.Replacing 4.7% of the recycled coarse aggregate with natural sand in such concrete helped in restoring the compressive strength to the level of the control mix that contained natural coarse aggregate.Likewise, replacing 11.7% of the recycled coarse aggregate with natural sand in concrete mix aided in restoring the split cylinder tensile strength to the level of the control mix that contained natural coarse aggregate.There is a relationship between compressive and tensile strengths, of which a lower bound can be reasonably predicted by models proposed for pervious concrete in the literature.The study confirms the feasibility of using recycled aggregate in pervious concrete mixes if about 10% natural fine aggregate is utilized in the mix as replacement of the recycled coarse aggregate.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".