Seismic behavior of soft storey mid-rise steel frames with randomly distributed masonry infill
Bibliographic record
Abstract
In this study, the effect of presence and distribution of masonry infill walls on the mid-rise steel frame structures having soft ground storey was evaluated by implementing finite element (FE) methods. Masonry infill walls were distributed randomly in the upper storey keeping the ground storey open without any infill walls, thus generating the worst case scenario for seismic events. It was observed from the analysis that there was an increase in the seismic design forces, moments and base shear in presence of randomly distributed masonry infill walls which underlines that these design values need to be amplified when designing a mid-rise soft ground storey steel frame with randomly distributed masonry infill. In addition, it was found that the overstrength related force modification factor increased and the ductility related force modification factor decreased with the increase in the amount of masonry infilled bays and panels. These must be accounted for in the design of mid-rise steel frames. Based on the FE analysis results on two mid-rise steel frames, design equations were proposed for determining the over strength and the ductility related force modification factors. However, it was recommended that these equations to be generalized for other steel frame structure systems based on an extensive 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".