GENETIC-ALGORITHM-BASED MIX PROPORTION DESIGN METHOD FOR RECYCLED AGGREGATE CONCRETE
Why this work is in the frame
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Bibliographic record
Abstract
Several desirable characteristics of concrete, such as strength, slump, durability and low CO 2 emission, cannot always be obtained by current conventional mix proportion design methods for recycled aggregate concrete (RAC), because Recycled aggregate generally has lower quality than natural aggregate owing to residual cement paste and various impurities. We treat optimal concrete mix proportioning as a multi-criteria problem, and suggest a new method based on genetic algorithms (GAs) to solve the mix proportion design problem for RAC through a simulated biological evolutionary process. In this method, several fitness functions for the desired properties of concrete, i.e., slump, strength, carbonation speed coefficient, price, and emission of CO 2 , were considered based on conventional data or adopted from previous studies. We thus arrived at optimal mix proportions for RAC that meet the desired performance criteria.
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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 | 0.001 |
| 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 it