Dynamic collapse analysis for a reinforced concrete frame sustaining shear and axial failures
Bibliographic record
Abstract
Abstract Shaking table test results from a one‐story, two‐bay reinforced concrete frame sustaining shear and axial failures are compared with nonlinear dynamic analyses using models developed for the collapse assessment of older reinforced concrete buildings. The models provided reasonable estimates of the overall frame response and lateral strength degradation; however, the measured drifts were underestimated by the models. Selected model parameters were varied to investigate the sensitivity of the calculated response to changes in the drift at shear failure, rate of shear strength degradation, and drift at axial failure. For the selected ground motion, the drift at shear failure and rate of shear strength degradation did not have a significant impact on the calculated peak drift. By incorporating shear and axial‐load failure models, the analytical model is shown to be capable of predicting the axial‐load failure for a hypothetical frame with three nonductile columns. Improvements are needed in drift demand estimates from nonlinear dynamic analysis if such analyses are to be used in displacement‐based performance assessments. Copyright © 2008 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.000 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".