Performance of Cement Mortar Composites Reinforced with Polyvinyl Alcohol Fibers
Bibliographic record
Abstract
Abstract This research studied the hybridization influence of polyvinyl alcohol (PVA), in the first stage as solution and the second added fibers with PVA solution. Performance under flexural loads of cement mortar composite was studied on this basis, PVA concentration in solution used was 1% of cement weight with three PVA fiber volume fraction (1%, 2% and 3%)which were considered as the variables for constant PVA solution to cement ratio (P/C) and w/c ratio as1.6% and 30% respectively. This paper is specially concentrating on the impact of fiber volume fraction contents and their metis to deform composite. The specimens were tested under one-point load test next two days wet curing and 26daysdry curing. The testes exhibited both ductility and flexural strength of cement matrix increased when the fiber volume fraction content increased. Combination only PVA fibers with the cement mortar composite showed softening in strain behaviors, whereas its performance is brittle for PVA solution-containing specimens, but mixture of PVA fiber with PVA solution to the cement mortar composites showed strain hardening performance. PVA fibers and solution in both surface properties (hydrophilic and / or hydrophobic nature) and chemical composition improved area under the curve of the reinforced cement mortar composites at 2% volume friction of PVA fiber with PVA solution about 197%, 29% and 9.6% compare with 1%, 3% volume friction of PVA with PVA solution and 2% without solution respectively. The addition 2% of PVA fibers increased about 44% flexural strength compare to the control specimens at flow diameter 190mm and 63% compare with 3% at flow diameter130 mm. It is given away that a uniform spreading of fibers through the bulk of the composite material is vital to its outstanding workability. Finally, it was observed fraction of PVA fibers plays as a result a significant role for refining ductility of cement mortar composites.
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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".