Early-Age Properties of Slag-Fly Ash Blended Geopolymer Concrete Reinforced with Glass Fibers – A Preliminary Study
Bibliographic record
Abstract
This research investigates the effect of additional water content, glass fibers addition, glass fiber length, and the handling time on the workability, 1-and 7-day compressive strength, and 7-day splitting tensile strength of slag-fly ash blended geopolymer concrete.The additional water content ranged from 0 to 100 kg/m 3 .Two types of glass fibers were used with lengths of 24 and 43 mm and incorporated by up to 2 and 1.5%, by volume, respectively.Also, the handling time, representing the time from mixing to casting, was varied.The experimental results showed that the additional water content led to a significant increase in the slump and decrease in the 1-and 7-day compressive strengths of plain geopolymer concrete.A value of 75 kg/m 3 was required to attain a slump of 150 mm and 7-day compressive strength of 35 MPa.Furthermore, the addition of 24-mm long glass fibers reduced the slump and increased the compressive and splitting tensile strength by up to 23 and 40%, respectively, compared to the plain control mix.Longer glass fibers (43 mm) resulted in further slump loss and increase in the splitting tensile strength, while the compressive strength was unaffected.Extending the handling time led to lower workability and limited impact on the mechanical properties.
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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".