Predicting the seismic collapse capacity of adjacent structures prone to pounding
Bibliographic record
Abstract
In crowded cities, many structures are often constructed in a very close vicinity; therefore, during severe earthquakes, pounding phenomenon occurs due to out-of-phase vibrations of adjacent structures. In this study, pounding of adjacent structures is investigated up to the occurrence of total collapse. The novelty of this study is performing incremental dynamic analyses to compute the seismic collapse capacities of both pounding structures in one model and removal of the collapsed structure during analysis, and proposing modification factors for modifying median collapse capacity of single structures to consider the effect of pounding, which cannot be considered before the design process. The results indicate that pounding may significantly affect median collapse capacities of structures compared with those obtained by neglecting the pounding phenomenon. Therefore, different modification factors are required according to structural characteristics. It is noteworthy that the results of this study were obtained using simplifying assumptions and should not be generalized.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".