Determination of the effectiveness of porcelain fine waste to enhance the performance of geopolymer concrete with recycled waste using central composite design and Taguchi method
Bibliographic record
Abstract
This study aims to evaluate the effectiveness of incorporating bone china fine aggregate (BCA) in geopolymer concrete (GPC) with recycled coarse aggregate (RCA). A total of 25 experiments were conducted to optimize the mix design of GPC with coarse RCA and fine BCA. The suitability of a response surface model using the central composite design approach and the Taguchi method with an L25 orthogonal array was assessed. Both methods provide valuable insights and recommendations for achieving ideal mix proportions to enhance strength. The resulting model, with a higher coefficient of determination, successfully predicted the mechanical properties of GPC in fresh and hardened states. The findings suggest that GPC with up to 50% RCA and up to 100% BCA demonstrates optimal performance in terms of hardened mechanical properties. Furthermore, a strong correlation was observed between the predicted and actual values, indicating the reliability of the model.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".