Collapse of a nonductile concrete frame: Evaluation of analytical models
Bibliographic record
Abstract
Abstract The current paper presents nonlinear dynamic analyses that simulate shaking table tests performed on a four‐column reinforced concrete frame described in a companion paper. The frame consists of two ductile and two nonductile columns interconnected by a stiff beam. In order to validate existing analytical models for nonductile concrete columns, a blind comparison of the test data and results of the analysis is performed. The analysis adequately captures the drift response and correctly detects collapse of the structure; however, strength degradation due to cover spalling is exaggerated in the analytical model. Refinement of the analysis by changing the concrete cover model results in an excellent agreement between the test data and analysis results at the initiation of shear failure and collapse of the frame. The experimental data are further compared with lumped‐plasticity nonlinear models used in engineering practice. The results suggest that the sudden strength degradation used in ASCE/SEI 41‐06 results in an exaggerated estimate of the displacement demands. It is also observed that ignoring the strength degradation, using an elastic‐perfectly‐plastic model, provides a good estimate of the displacement demands when strength degradation is not severe. 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".