The Effect of Using Red Brick Waste on Some Mechanical and Thermal Properties of Recycled Aggregate Concrete in Syria
Bibliographic record
Abstract
In this study, the effect of using crushed red brick waste on some mechanical and thermal properties of recycled aggregate concrete in Syria such as pressure resistance, tensile strength, elastic modulus, thermal conductivity has been studied. Where a portion of coarse aggregate (gravel) and coarse sand up to the diameter of 2.38 mm included in the composition of the reference concrete mixture aggregate (consisting of 30% recycled gravel and 70% natural limestone gravel) has been replaced by crushed red brick aggregate by 20%, 40%, 60%, 100%. After implementing these mixtures, some of the resulted concrete properties such as: density, compressive strength, bending strength, splitting strength, as well as thermal conductivity has been measured. The results showed that compressive, bending, and splitting strength increase with the increase in of red brick replacement ratio to a maximum value, and then decreasing, where the replacement ratios of 45%, 72%, and 70%, respectively correspond with compressive, bending, and splitting maximum strength. concrete mixtures with a thermal conductivity less than 0.3 W / m.K have been obtained, which can be considered as heat insulating according to Syrian Thermal Insulation Code, thus it can be used to insulate walls and ceilings, these mixtures contain crushed red brick aggregate ratio greater than 52% in their coarse aggregate (gravel) and sand up to the diameter of 2.38 mm. The results also showed that thermal conductivity more sharply decrease than the conductivity calculated by relation given by ACI as the replacement ratio increase. A similar new relation has been found for the thermal conductivity of concrete mixes containing red brick aggregate.
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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".