Numerical study on the punching shear strength of edge steel-reinforced concrete slab-column connections
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Bibliographic record
Abstract
• Increasing slab thickness cuts deflection by 95% and reduces strength by 40%. • Column aspect ratio of 2 boosts strength by 21%, but ratio of 5 reduces it by 36%. • Larger column stubs lower strength by 43% due to stress redistribution. • Reducing span-to-depth ratio improves strength by 25% and reduces deflection by 93%. Punching shear failure in steel-reinforced concrete (RC) edge slab-column connections poses a critical challenge in structural engineering, with safety and design efficiency implications. This study investigates the influence of key geometric parameters—slab thickness, column aspect ratio, square column stub size, and span-to-depth ratio—on punching shear strength, a topic underexplored in existing research. A unique feature of this research is the ability to examine the effects of slab thickness, column aspect ratio, and square column stub size independently, without any interference from changes in the span-to-depth ratio, by keeping it constant. This approach has never been achieved before and is impractical in experimental studies. Using finite element modeling, over 20 connection configurations were analyzed to assess their structural behavior. Results showed that increasing slab thickness reduced deflection by up to 95% but decreased punching shear strength by 40% due to stress redistribution. Higher column aspect ratios and larger square column stubs caused strength reductions of 36% and 43%, respectively, while reducing the span-to-depth ratio enhanced stiffness and punching shear strength by 25%. The study also evaluated the accuracy of three design standards—American (ACI 318-19 (22)), Canadian (CSA-A23.3:24), and Japanese (JSCE-2007)—revealing deviations of up to 144% from actual performance. To address these discrepancies, four new equations were proposed, tailored to specific geometric parameters, and validated against available literature, demonstrating superior accuracy compared to existing standards. These findings underscore the limitations of current methodologies and emphasize the importance of incorporating geometric factors to improve slab-column connection designs in modern construction.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it