Structural Integrity of Composite Steel Gravity Frame Systems
Bibliographic record
Abstract
An important aspect of progressive collapse evaluation of steel gravity frame structures is to consider the mobilization of composite action between the slab and the steel frame. After initial column failure and experiencing large deformation, catenary action develops in the floor slab and the overall response of the system changes the load transfer mechanism to the connections. As a consequence, shear connections experience extreme rotation and demands that are significantly different from those imposed by an equivalent bare frame system. This research investigates the structural integrity of steel gravity frames in conjunction with the concrete floor slab and the induced demands on the shear connections. A high-fidelity model including the floor slab components is developed to examine the performance and behaviour of the shear connections, in addition to the overall load carrying capacity of the system. Explicit quasi-static analysis is employed to overcome the convergence difficulties related to contact, geometric and material nonlinearities, large deformation, and fracture simulation. Challenges involved in developing numerical simulations of conventional composite floor framing systems when a column has been compromised are discussed. The component finite element model is validated against the results of physical tests in terms of failure mode. It is shown that the finite element analyses give reasonable accuracy and agree well with the experimental results. The research results show that while the presence of the concrete floor slab contributes to the capacity of connections, it also amplifies the demand on the connections and alters the load transfer mechanism as compared to a bare frame.
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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 | 0.001 | 0.001 |
| 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".