Finite-Element Analysis of Reinforced Concrete Slabs with Punching Shear Reinforcement
Bibliographic record
Abstract
Finite-element analyses (FEA) of reinforced concrete slab-column connections with shear reinforcement are presented and discussed. Ultimate loads and crack patterns are shown and compared to the experimental findings. The damaged plasticity model in ABAQUS, previously calibrated and validated on tested slabs without shear reinforcement, is adopted to properly simulate the behavior of slab-column connections with shear reinforcement. Four interior slab-column specimens were tested under vertical loading applied through the column. One slab specimen was without shear reinforcement, while the other three differed in the amount of the shear bolts. The objective of this paper is to propose a novel numerical modeling strategy for simulating and analyzing shear reinforced slabs with shear bolts. For that purpose, in the numerical analyses, four different approaches for modeling the shear bolt are introduced and described. Discussion and comparison on the predicted failure loads from the design codes and models in conjunction with the experimental and numerical data, are presented. Finally, a parametric numerical study is conducted, where the rectangular and the radial shear reinforcement arrangements are compared.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".