Pilot Experimental Tests on Punching Shear Strength of Flat Plates Reinforced with Stirrups Punching Shear Reinforcement
Bibliographic record
Abstract
Flat plates are favor structure systems usually used in parking garages and high-rise buildings due to its simplicity for construction. However, flat plates have some inherent structural problems, due to high shear stress surrounding the supporting columns which cause a catastrophic brittle type of failure called "Punching Shear Failure". Several solutions are used to avoid punching shear failure, including the use of drop panels or punching shear reinforcement. The latter is being a more sophisticated solution from the structural ductility, the architectural and the economical point of view. This study aims at investigating the effect of stirrups as shear reinforcement in enhancing the punching strength of interior slab-column connections. A total of four full-scale interior slab-column connections were tested up to failure. All slabs had a side length of 1700 mm and 160 mm thickness with 200 mm x 200 mm square column. The test parameters were the presence of shear reinforcement and stirrups concentration around the supporting column. The test results showed that the distribution of stirrups over the critical punching shear zone was an efficient solution to enhance not only the punching shear capacity but also the ductility of the connection. Furthermore, the concentrating of stirrups shear reinforcement in the vicinity of the column for the tested slabs increases the punching shear capacity by 13 % compared to the uniform distribution at same amount of shear reinforcement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".