Approximate Method for Performance-Based Seismic Assessment of Steel Moment-Resisting Frames
Bibliographic record
Abstract
bstract A wide range of approximate methods has been historically proposed for performance-based assessment of frame buildings in the aftermath of an earthquake. Most of these methods typically require a detailed analytical model representation of the respective building in order to assess its seismic vulnerability and post-earthquake functionality. This paper proposes an approximate method for estimating story-based engineering demand parameters (EDPs) such as peak story drift ratios, peak floor absolute accelerations, and residual story drift ratios in steel frame buildings with steel moment-resisting frames (MRFs). The proposed method is based on concepts from structural health monitoring, which does not require the use of detailed analytical models for structural and non-structural damage diagnosis. The proposed method is able to compute story-based EDPs in steel frame buildings with MRFs with reasonable accuracy. Such EDPs can facilitate damage assessment/control as well as building-specific seismic loss assessment. The proposed method is utilized to assess the extent of structural damage in an instrumented steel frame building that experienced the 1994 Northridge earthquake.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".