Design of Alkali-Activated Ladle Slag Mortar Using Taguchi Method
Bibliographic record
Abstract
This study investigates the feasibility of utilizing ladle furnace slag as a sole binder in alkali-activated mortar. The Taguchi method for design of experiments was used to design, analyze, and optimize the mixture proportions of alkali-activated ladle slag mortars. The five factors considered in the design included ladle slag content (LS), alkali-activator solution-to-binder ratio (AAS/B), sodium silicate-to-sodium hydroxide ratio (SS/SH), sodium hydroxide solution molarity (M), and crushed sand-to-dune sand replacement ratio (CSR). With four design levels, a corresponding L16 orthogonal design matrix was developed. The targeted design criteria were the 7-day compressive and tensile strength, workability, and initial setting time. Analysis of variance results showed that mechanical properties were equally impacted by LS, SS/SH, and CSR. Conversely, the LS, AAS/B, and SS/SH contributed the most to the workability and setting time. Using Taguchi method, three mixes were proportioned based on the analyzed data to optimize each of the design criteria. Validation of the optimized mixes provided evidence of the applicability of the Taguchi method to design alkaliactivated ladle slag mortars with a margin of error of less than 9%.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".