Comparative analysis concerning the structural performance and resilience of concrete materials incorporating glass powder and conventional concrete
Why this work is in the frame
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Bibliographic record
Abstract
The construction industry relies on a variety of structural materials, with concrete being a favored choice due to its outstanding strength and durability. Conventional concrete is typically made up of cement, fine aggregates, and crude aggregates, with its strength designed to meet specific requirements. Enhancing sustainability and minimizing environmental impact can be accomplished through utilizing waste substances in concrete production. One approach involves partially replacing cement and fine aggregates blended with waste glass powder. Additionally, superplasticizers serve as commonly utilized to lower the water-cement ratio (F/C), thereby improving the power properties of concrete. Effective curing remains a crucial factor in augmenting structural durability and concrete's mechanical characteristics in structures. The study examines strength and durability characteristics of concrete from integration using glass powder in place of certain cement and fine aggregate. Cement-based material mixtures are prepared with two different w/c values of 0.4 and 0.5 and replacement concentrations of 10%, 15%, and 20% for both the binder and fine aggregates. Essential parameters include fast chloride permeability and water absorption; comparative analyses are conducted to determine performance differences between conventional concrete and the modified version. The results of assessing the viability of adding leftover glass powder to concrete, this study aims to improve environmentally friendly building techniques.
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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 | 0.001 |
| 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 it