Optimization of Aggregate Gradation Combinations to Improve Concrete Sustainability
Bibliographic record
Abstract
By optimizing the packing of the combined aggregate gradations, the cement paste content needed to make concrete can be reduced, improving sustainability, cost, performance, durability, and workability. Optimization can be achieved using theoretical and empirical techniques, or waste concrete material as an intermediate size fraction. However, the potential for improvement is currently limited by prescriptive grading specifications that require meeting individual requirements for fine and coarse aggregates.\nFrom this study, using various optimization techniques, it was found that by inclusion of an intermediate sized aggregate material, a reduction in cement paste up to 16% is possible for 35 MPa and 50 MPa mix designs typically used in Ontario bridge decks. The aggregate materials used were a natural sand, and two crushed limestones of 19.0 mm and 6.7 mm maximum size. From these findings, recommendations are made for improving the current Ontario Provincial Standard Specification (OPSS) 1002 used for concrete aggregates.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".