Assessment of the PVC Waste Addition Effect on the Concrete Mechanical Performance
Bibliographic record
Abstract
The purpose of this study is to investigate the possibility of using the polyvinyl chloride (PVC) wastes as a concrete manufacturing material without pre-treatment.The purpose is also to contribute for restricting environmental pollution and exploitation of natural resources, through the stabilization and the solidification of PVC wastes in concrete.The aim of this experimental study is to evaluate experimentally the fresh and cured properties of PVC concrete based in comparison with ordinary concrete (OC).This study consists in collecting PVC waste, especially the used PVC pipes rejected in nature, and incorporate it into concrete by substitution of sand with different volume ratios (5%, 10% and 15%).In this study, two different shapes (Fiber and Fine) of PVC were considered.According to the test results, the addition of PVC waste in concrete as a partial replacement for natural sand conducts to decrease the workability of fresh concrete.It was noticed that, the concrete with PVC fiber shows a lower workability comparatively with fine PVC concrete.It was also observed that the PVC fiber improves the concrete compressive strength.It increases with increasing the replacement ratio of PVC waste.However, the increase in the ratio of fine PVC leads to a decrease in compressive strength.The better mechanical performance factor (MPF) was obtained for concrete mixes with high PVC fiber and moderate PVC fine ratios.The collected outcomes would contribute to helpful information for recycling PVC waste in concrete mixes.
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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 | 0.000 | 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) | 0.001 | 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".