Push-Over Analysis for Performance-Based Design Using Semi-Rigid Analysis Techniques
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Bibliographic record
Abstract
The paper presents the conceptual details of a new mathematical model for nonlinear static push-over analysis for use in performance-based design of frameworks under earthquake loading. Studies have shown that the behavior of semi-rigid frameworks can be modeled using a `fixity-factor' that measures the degree of connection fixity. Assuming a potential plastic hinge section of a beam-column member is a kind of connection, a similar approach is adopted by this study to monitor the rigidity degradation (plastification) of members of frameworks under push-over loads. Through the use of `rigidity-factors' that measure the degree of plastic hinge formation, the conventional elastic stiffness matrices of frame elements (beams, columns, etc.) are progressively modified to account for nonlinear elastic-plastic behavior under incrementally increasing loads. The concepts are illustrated for first-order analysis of planar frameworks. They are readily extended to second-order analysis and space frameworks.
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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 | 0.001 | 0.003 |
| 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) | 0.004 | 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