Seismic Design Criteria for Steel Moment Resisting Frames for Collapse Risk Mitigation
Bibliographic record
Abstract
This paper quantifies the lateral overstrength and the collapse risk of steel buildings with perimeter special moment frames (SMFs) designed in highly seismic regions in North America. State-of-the-art analytical models that consider the contributions of the composite concrete slab and the interior gravity framing to the lateral resistance and strength of steel frame buildings are employed. The findings demonstrate that the quantification of system overstrength based on dynamic analysis is more appropriate to nonlinear static analysis, since dynamic amplification of story shear forces due to higher mode effects is considered. Collapse risk is quantified using the mean annual frequency of collapse. It is found that low to mid-rise SMFs designed with a strong column weak-beam (SCWB) ratio larger than 1.0, achieve a probability of collapse larger than 1 percent in 50 years. A tolerable probability of collapse is achieved when a SCWB > 1.5 is implemented into the seismic design of steel SMFs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".