Shear Behavior of SCC Beams with Different Coarse-to-Fine Aggregate Ratios and Coarse Aggregate Types
Bibliographic record
Abstract
The effect of mixture composition and coarse aggregate density on the shear strength and cracking behavior of self-consolidating concrete (SCC) beams are presented in this study. The experimental test parameters included coarse/fine (C/F) aggregate ratio (ranging from 0.7 to 1.2), coarse aggregate size (10 and 20 mm), coarse aggregate type/density (slag, expanded slate, and crushed stone), and varying compressive strengths (26–72 MPa). The density of the tested mixtures varied from 1,848 to 2,286 kg/m3. The study investigates the fresh properties of all tested mixtures and the shear strength and cracking behavior of 16 full-scale concrete beams. Based on some selected design codes, the ultimate shear strength of the tested beams is also predicted. The results showed that SCC mixtures with a higher C/F ratio or bigger normal-weight aggregate had better flowability and less high range water reducer admixtures (HRWRA) demand. Although all tested beams showed comparable normalized shear strength, beams with a high C/F ratio or bigger normal-weight aggregate had higher postdiagonal cracking resistance. The results also showed that the expanded slate and slag lightweight aggregates were found to be relatively strong (compared to most common lightweight aggregates) as they did not entirely break along the diagonal crack. Increasing the volume of these lightweight aggregates in SCC mixtures not only reduced the mixture density but also enhanced the postdiagonal cracking resistance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".