Investigation on the Performance of High-Volume Fly Ash Concrete Reinforced with Fibers for Rigid Pavement
Bibliographic record
Abstract
Abstract - Fly ash has significant potential in high-volume fly ash concrete (HVFAC) due to its favorable physico-chemical properties. Extensive research in India and abroad has examined its strength and performance characteristics. In India, most ready-mixed concrete plants in the private sector commonly use 20–30% fly ash as part of the cementitious material, whereas several government agencies remain cautious. At construction sites with batching plants, typical fly ash replacement levels are around 25–30%. In contrast, site-mixed concrete using tilting drum mixers rarely uses fly ash directly, though blended cements containing 22–32% fly ash are widely used; in fact, nearly 60–70% of cement produced in India is blended. HVFAC generally replaces more than 50% of cement with fly ash and requires very low water content. To maintain workability, high-range water reducers or superplasticizers are used. Although HVFAC exhibits lower early compressive strength than conventional concrete, it develops excellent long-term strength along with improved elastic modulus, flexural, tensile, and abrasion performance. Research at CANMET-MTL in Canada initiated the development of HVFAC in 1985, with an emphasis on low cement content, a low water-to-binder ratio, and fly ash contents of up to 55%. HVFAC offers reduced CO₂ emissions, lower environmental impact, and improved durability, making it suitable for mass and structural concrete applications. Key Words: High-Volume Fly Ash Concrete (HVFAC), Blended Cement, Fly Ash Utilization, Sustainable Construction, Cement Replacement, and Mechanical and Durability 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".