Processing of Recycled Cement Sacks as Cellulose Pulp into Pervious Concrete
Bibliographic record
Abstract
This study proposes and validates a methodology for incorporating cellulose fibres (CF) from recycled cement sacks into pervious concrete.The process involves mechanically converting the sacks into pulp and pre-saturating them to ensure integration into the mix.The CF obtained was evaluated in terms of composition, and its performance was assessed through rheology and the mechanical and permeability properties of pervious concrete at three dosages (3.9, 5.8, and 7.7 kg/m³).A straightforward mechanical procedure was established to produce the CF, requiring a minimum presaturation period of 12 hours to secure adequate mix flowability and paste coating uniformity.XRF and XRD tests confirmed that the treatment reduced cement residues, although traces of chlorine remained.Saturated CF did not compromise matrix fluidity, ensuring an adequate coating.Additionally, CF improved permeability by up to 32.9% without compromising strength, acting as an internal curing agent and enhancing longterm compressive strength up to 10.4%.CF also strengthened matrix-aggregate bonding, improved post-crack integrity, and promoted a more ductile failure mode.In conclusion, processing cement sacks into cellulose fibres provides a practical and sustainable solution for improving cohesion and permeability in pervious concrete while maintaining mechanical performance.This approach supports sustainable construction by valorising packaging waste and offers a method adaptable to industry, depending on local conditions.
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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) | 0.001 | 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".