Properties Evaluation of Self Compacting Concrete Made with Industrial By-Products
Bibliographic record
Abstract
Urbanization with advanced technologies should be economic, sooner operational, and sustainable. In addition to reducing construction time, modern technologies should utilize various left-over materials or by-products to save budget and the environment. The present study examines the potential of using Phosphogypsum, an industrial by-product, in concrete as an environment-friendly, sustainable solution. Various percentages (5%, 10%, 15%, and 20%) of Phosphogypsum have been used to replace Portland cement to produce cost-effective SCC with favorable properties and strength. Conplast SP430 G8 superplasticizer has been used at a fixed amount as a chemical admixture. Laboratory tests have been performed to analyze various material properties together with conducting slump flow test, V-funnel test, and L-box test to evaluate the workability of the SCC. Compressive strength test results at 3-, 7-, 14-, and 28-days’ concrete reveals that light replacement of cement with Phosphogypsum may increase the strength, whereas higher replacement would result in a decrease in strength. The present study concludes that a 10% replacement of cement with Phosphogypsum would provide the best result with increased compressive strength. This finding eventually confirms the use of Phosphogypsum, an industrial by-product, in concrete without compromising its strength with a reduction of time and construction cost.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".