Probabilistic evaluation of global seismic capacity of degrading structures
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The present study addresses the probabilistic seismic capacity evaluation of the existing non‐ductile reinforced concrete structures that are vulnerable to shear, and thus axial, failures of their columns. The probability of structural collapse at a target lateral displacement imposed by seismic hazard is estimated by reliability analysis. For this purpose, the prevalent nonlinear static procedure is extended with finite element reliability analysis. The global structural model is enhanced by incorporating probabilistic capacity and post‐failure response models of individual columns. The challenges in the detection of collapse and the potential problems and remedies in the reliability analysis due to ‘gradient discontinuities’ are presented. In particular, ‘smoothing’ of the post‐failure response models is implemented to represent realistic member behaviour and to avoid non‐convergence in the reliability analysis. Finally, parameter importance measures are employed to identify the parameters with the highest contribution to the uncertainty in the structural performance. Copyright © 2007 John Wiley & Sons, Ltd.
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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 | 0.001 |
| 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 it