Finite element studies of reinforced concrete slab - edge column connections with openings
Bibliographic record
Abstract
An extended nonlinear layered finite element method (LFEM) is used to investigate the influence of openings and shear stud reinforcement (SSR) on the behaviour of reinforced concrete slab – edge column connections. In all, ten large-scale slab – edge column connections tested previously are analyzed. The laboratory test variables were the size and location of the openings in the vicinity of an edge column and the existence of SSR. The numerical results of the load–deflection response, the ultimate strength, and the crack patterns are compared with the experimental findings and good agreement is achieved. A numerical study on two connections is also carried out to determine the influence of the locations of opening in slab – edge column connections with SSR. Discussion on code provisions for slabs with openings is provided. The comparative and numerical studies confirm the accuracy, reliability, and effectiveness of the LFEM in the analysis of slab – edge column connections with both openings and SSR.Key words:slab–column connection, punching shear, opening, shear stud reinforcement, finite element analysis.
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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".