A comprehensive collapse fragility assessment of moment resisting steel frames considering various sources of uncertainties
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Bibliographic record
Abstract
Different sources of uncertainties contribute to the collapse and safety assessment of structures. In this paper, impact of construction quality (CQ) is considered in developing analytical collapse fragility curves for moment resisting steel frames. Furthermore, the interaction of this source of uncertainty with epistemic uncertainty inherent in modeling parameters, due to lack of knowledge and inaccuracy of predictor equations, is investigated. Beam strength, column strength, beam ductility, and column ductility meta-variables are defined as modeling parameters which are being suffered by informal uncertainty. Quadratic equations for the mean and the standard deviation of collapse fragility curves are derived by utilizing response surfaces, which are interpolated to analytically-derived values considering realizations for modeling variables and for various levels of construction quality. To the best of the authors’ knowledge, interaction of modeling and CQ uncertainty in analytical collapse fragility curve has not been considered in previous investigations. A fuzzy rule-based method is applied to employ the effects of uncertainty due to CQ. Using Monte Carlo simulation for the modeling variables and the construction quality index, and subsequently computing response surface coefficients via a fuzzy inference system, and finally deriving collapse fragility curve parameters through response surfaces, result in collapse fragility curves of structures. In developing these curves, different sources of uncertainties are involved, ranging from lexical to informal and stochastic types. It is concluded that neglecting the effects of these sources leads to the underestimation of collapse fragility probability. This shows the importance of considering modeling and construction quality uncertainty effects on collapse fragility curves. It is shown that for a sample moment resisting steel frame collapse probability is increased 53% and 60% for 10% and 2% probability of exceedance in 50 years seismic hazard levels, respectively, while interaction of CQ and modeling uncertainties are considered in comparison with neglecting them. Otherwise, if only modeling uncertainty is involved, this increment is evaluated at 42% and 16%, respectively for the aforementioned probabilities of exceedance.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it