Synergistic Effects of Fly Ash and Silica-Based Materials on Concrete Properties
Bibliographic record
Abstract
The demand for construction materials is rapidly increasing due to ongoing urbanization and modernization.These materials are primarily sourced from natural resources, leading to significant environmental concerns such as resource depletion and pollution.Recycling construction waste [1] is a sustainable solution to mitigate these issues.Among the various waste materials, glass is one of the most abundant.If not properly managed through collection, cleaning, and recycling waste glass can severely impact the environment and public health.In many developed countries, glass recycling systems are well-established, effectively reducing landfill use and environmental damage.However, in Oman and several other developing nations, glass recycling remains underutilized.Most waste glass ends up in landfills, representing both an environmental hazard and a missed economic opportunity.Not all types of waste glass are suitable for traditional recycling, but they can be repurposed in construction, particularly in concrete production.This research explores the potential of using crushed waste glass as a partial or full replacement for natural sand in concrete.Eight concrete mixes were prepared, incorporating waste glass at 20%, 50%, and 100% replacement levels.Additionally, Class C fly ash [2] was used to replace 30% of Portland cement in all mixes.These modified concretes were tested in both fresh and hardened states to evaluate their performance.The results showed that incorporating waste glass [3] had minimal negative effects on the physical and mechanical properties of concrete.Moreover, the combination of fly ash and glass improved certain concrete characteristics.This study demonstrates that using waste glass in concrete not only maintains acceptable performance standards but also contributes to environmental sustainability by reducing landfill waste and conserving natural resources.Thus, integrating waste glass into construction materials presents a viable strategy for sustainable development in Oman and similar regions.
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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) | 0.001 | 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".