Behavior of multi-story steel buildings under dynamic column loss scenarios
Bibliographic record
Abstract
This paper presents a computational study of column loss scenarios for typical multi-story steel buildings with perimeter moment frames and composite steel-concrete floors. Two prototype buildings (three-story and ten-story) were represented using three-dimensional nonlinear finite element models and explicit dynamic analysis was used to simulate instantaneous loss of a first-story column. Twelve individual column loss scenarios were investigated in the three-story building and four in the ten-story building. This study provides insight into: three-dimensional load redistribution patterns; demands on the steel deck, concrete slab, connections and members; and the impact of framing configuration, building height and column loss location. In the dynamic simulations, demands were least severe for perimeter columns within a moment frame, but the structures also exhibited significant load redistribution for interior column loss scenarios that had no moment connectivity. Composite action was observed to be an important load redistribution mechanism following column loss and the concrete slab and steel deck were subjected to high localized stresses as a result of the composite action. In general, the steel buildings that were evaluated in this study demonstrated appreciable robustness.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".