Enhancement of Mechanical Properties of Concrete Using Industrial Waste
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In response to the evolving global landscape, there is a growing inclination towards embracing sustainable and environmentally conscious construction practices to meet the demand for more eco-friendly and climate-resilient built environments.In recent time several SCM (Supplementary Cementitious Material) had been employed in concrete for its property enhancement as well as reducing negative impact of waste on environment.Taking a step in the similar direction the present study employs Rice husk ash (RHA) and Waste marble powder (WMP) for strength enhancement of concrete.Varying percentage of Rice Husk Ash (0%, 2.5%, 5%, 10%, 12.5%, 15%&20%) and Waste Marble Powder (0%,2.5%,5%,10%, 12.5%, 15% & 20%) were used as a replacement of cement in binder.Further a combined replacement of RHA and WMP was used to prepare data cases for replacement of cement in concrete.Five different cases were designed with keeping RHA percentage constant for single case while varying the WMP percentage for same.Case 0 with no replacement, Case 1 with 2.5% RHA along with varying percentage of WMP, Case 2 with 5% RHA along with varying percentage of WMP similarly Case 3 with 10% RHA along with varying percentage of WMP and Case 4 with 12.5% RHA along with varying percentage of WMP.The varied percentage of WMP were 5%, 10%, 15% and 20% for each case.This resulted in identification of combined effect of both materials on concrete strength
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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 | 0.000 | 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) | 0.000 | 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