Optical Fiber Waste Used as Reinforcement for Concrete with Recycled Marble Aggregate
Bibliographic record
Abstract
Sustainable development in the 21st century depends on the reuse of materials and products, as well as on economic and environmental incentives for recycling. Several studies have sought to improve the quality of concrete, as well as its durability and strength, by adding fibers (metallic, polypropylene, carbon, vegetables) or by replacing the aggregate. The use of optical fiber waste in concrete is still incipient and few studies address the use of marble aggregate to be used in concrete. This research assesses the behavior of the mixture composed of: Portland cement + fine aggregate (sand from crushed marble waste) + coarse aggregate (gneiss) + optical fiber waste and water. The compressive strength, the tensile strength and the modulus of elasticity of concrete and the durability of optical fiber waste in alkaline composite were tested through microstructural evaluation. The results present an increase of about 20% in the mechanical properties and a reduction in the rigidity of the mixture, making the material more ductile. The superficial protection of the fibers made them more resistant to the alkaline attack of the cement. The knowledge acquired would allow the creation of sustainable concrete reinforced with optical fiber in a much more efficient way.
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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 | 0.001 | 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".