Correlations between Fresh Properties of Self-Consolidating Concrete Including Palm Oil Fuel Ash
Bibliographic record
Abstract
Palm oil fuel ash (POFA) has been used successfully as a supplementary cementing material in various types of concrete. In the present study, self-consolidating concrete (SCC) was produced by using POFA as a partial replacement of ordinary portland cement (OPC). In total, sixteen SCC mixes were prepared by varying water to binder (W/B) ratio, POFA content, and high-range water reducer (HRWR). POFA was used by replacing 0–30% of OPC by weight at the W/B ratios ranging from 0.25 to 0.40. The filling ability, passing ability and segregation resistance of various SCC mixes were investigated. The filling ability was determined with respect to slump flow, 50-cm slump flow time, inverted slump cone flow spread and time, and V-funnel flow time. The passing ability was examined with respect to J-ring flow. In addition, the segregation resistance was assessed with regard to sieve segregation index and column segregation factor. Based on the data obtained, the correlations for the fresh properties of SCC were sought. The experimental findings showed strong correlations between most of the fresh properties of SCC.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".