STR-942: PUNCHING SHEAR OF SELF-CONSOLIDATING TWO WAY SLABS
Bibliographic record
Abstract
This paper presents an experimental program conducted to investigate the punching shear behaviour of self-consolidating (SCC) two-way slabs, and the influence of using different sizes of coarse aggregate and slab thickness on this behaviour. For this purpose, a total of six slabs were tested. Two groups of labs with targeted compressive strength of 30 MPa were used; for group A, 10 mm coarse aggregate size was used, and 20 mm coarse aggregate size was used for the slabs in group B. Each group consisted of three slabs with different thicknesses of 150, 200, and 250 mm. The results revealed a significant effect of slab thickness and size of coarse aggregate. The failure criterion proposed by (Muttoni 2008) based on the slab rotation was used to predict the tested slabs capacities. In addition, comparison with other codes of practice (CSA A23.3-04, ACI 318-11, BS8110-97, and EC2) was carried out. These codes except the EC2 can be safely used to check the punching shear capacity of SCC slabs without the need of any modification to the equations used.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".