Punching shear tests of normal- and high-strength concrete flat plates
Bibliographic record
Abstract
Experimental research was conducted to investigate the punching shear performance of flat plates. A large number of slab specimens of normal- and high-strength concrete were tested under concentric and eccentric loads. The effects of flexural reinforcement and the use of steel fiber reinforcement were investigated. Experimental expressions were developed for the computation of residual slab strength. Experimentally observed punching shear capacities were compared with those from the provisions of Canadian Standards Association (CSA) standard CSA-A23.3-04. The results indicate that concrete strength plays an important role in punching capacity and slab rigidity. Slabs with a higher percentage of flexural reinforcement show an increase in punching capacity. The use of steel fibers results in improved strength and stiffness while also enhancing the postpeak deformability and residual strength. The empirical expressions developed provide reasonably good predictions of residual slab capacities. CSA-A23.3-04 expressions result in conservative punching shear capacity predictions for concentrically loaded slabs and provide good agreement with the experimentally observed punching shear capacities for eccentrically loaded slabs.Key words: reinforced concrete, flat plate, punching shear, strength, high-strength concrete, eccentric loading, slab re inforcement ratio, steel fiber reinforced concrete.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".