Bibliographic record
Abstract
Abstract The recently developed Incremental Dynamic Analysis (IDA) requires nonlinear time history analyses at different levels of intensity of an ensemble of ground motions, which is time‐consuming due to the high computational efforts involved. In the current study, a simplified method named as Incremental Modified Pushover (IMP) is developed and evaluated. In this method, the response of the structure is obtained using one pushover analysis at any specified level of ground motion intensity. The associated higher mode effects are explicitly considered when determining target roof displacement and lateral load pattern. In the bilinear idealization of the pushover curves, a new approach has been used. Moment resisting steel frames with 4, 8, 12 and 16 stories, as well as their corresponding soft‐story models are used for verifying the proposed method. The studied frames were subjected to seventeen different scaled earthquake ground motions. The results of the presented method, IMP, are verified in terms of maximum roof displacement, maximum inter‐story drift and maximum plastic hinge rotation at different ground motion intensities. The results show that the IMP method gives higher response values compared with IDA, which can be viewed as being more conservative. 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".