Influence of Clamping Stresses in the Shear Strength of Concrete Slabs Under Uniform Loads
Bibliographic record
Abstract
Experimental results have shown shear capacities of concrete slabs under uniform loads sometimes considerably higher than those predicted by current concrete codes. Vertical compressive stresses transverse to the beam axis, or clamping stresses, are neglected in these analyses. The present study includes results from analytical and experimental research that was conducted to investigate the influence of clamping stresses on the shear strength of concrete slabs under uniform loads. Including clamping stresses in the Modified Compression Field Theory (MCFT) procedures was shown to considerably increase the shear prediction accuracy for members under uniformly distributed loads even for members with short shear spans. In addition, contrary to current sectional methods that give accurate results only in those regions where plane sections remain plane, results suggest that the MCFT with clamping stresses can provide reasonably accurate results in any region of a slab. Shear strength predictions from the MCFT with clamping were verified against 113 experiments from the literature and twelve tests designed and carried out during this work. Additional improvements in predicted shear capacities were achieved when tension stiffening was included in the calculations, an important issue for continuous members in which the shear critical region is close to the inflection point.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".