Use of Polymeric Fibers in the Development of Semilightweight Self-Consolidating Concrete Containing Expanded Slate
Bibliographic record
Abstract
This paper aims to evaluate and optimize a number of semilightweight self-consolidating concrete (SLWSCC) mixtures containing coarse and fine aggregates, lightweight expanded slate, and reinforced with different types of polymeric fiber. The fibers used were 8 and 12 mm polyvinyl alcohol (PVA8 and PVA12), and 19 mm polypropylene (PP19). The developed mixtures included different binder contents (550 and 600 kg/m3), fiber volumes (0.3% and 0.5%), and coarse-to-fine (C/F) aggregate ratios (0.7 and 1.0). Two normal-weight self-consolidating concrete (NWSCC) mixtures made with fine and coarse crushed granite aggregates also were tested in this investigation for comparison. Although the use of polymeric fibers negatively affected the fresh properties of the mixture, it was possible to develop successful SLWSCC mixtures with significantly improved flexural strength using up to 0.5% fibers. SLWSCC mixtures with shorter fibers (PVA8) had better fresh properties and strengths compared to mixtures with longer fibers (PVA12 and PP19). A minimum of 550 kg/m3 binder content was required to develop SLWSCC mixtures with acceptable self-compactability. However, using 600 kg/m3 binder content contributed to improving the fresh properties of the mixture, which allowed using a higher content of lightweight expanded slate aggregate, achieving a further reduction of the mixture density. The results also showed that unlike the lightweight coarse aggregates, the use of lightweight fine aggregates helped to develop mixtures with higher flowability, passing ability, and strengths.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".