SIZE EFFECT ON SHEAR BEHAVIOR OF HIGH STRENGTH RC SLENDER BEAMS
Bibliographic record
Abstract
Nine high strength reinforced concrete beams with minimum shear reinforcement and heavier than minimum as per ACI code, were tested to investigate their size effects on shear strength for medium depth beams (d ranges from 305 to 560 mm), ultimate shear capacity and failure modes. Test variables were shear reinforcement percentage (ρv varying from 0.2682 to 0.3351), longitudinal steel percentage (ρl varying from 2.78 to 3.43) and effective depth (varying from 400 to 500 mm) with constant compressive strength (fck =70 MPa) and shear span to effective depth (av/d) =2.6. This study investigated the influence of beam depth with varying longitudinal reinforcement and minimum shear reinforcement. Test results were compared with the strengths predicted by ACI code, CEB-FIP Model, Zsutty’s equation, Okumaro’s equation and also with Bazant’s method. ACI code and Okumaro’s equation can predict the shear strength trend reasonably well for slender beams. The Bazant’s method is underestimating the ultimate strength. The accuracy of the Zsutty’s equation is relatively better than ACI approaches and but it does not take in to account the size effect. Canadian code provisions correlates well with the experimental results taking in to account the size effect.
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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 | 0.001 |
| 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".