Wind hazard on earthquake damaged buildings
Bibliographic record
Abstract
Abstract This study proposes a holistic approach to multihazard performance‐based assessment of a tall steel building, partially damaged by earthquake, and then subjected to wind. The case study is a 16‐storey LD‐CBF building in Montreal, designed in accordance with the Canadian code and steel standard. Advanced numerical models are developed in OpenSees; hence, they account for material nonlinearity including low‐cycle fatigue to simulate brace fracture. Wind histories are generated from wind tunnel data. The sequence of analyses is: (i) design the LD‐CBF building to respond to code‐based earthquake (2475 years return period) and verify the LD‐CBF members to design wind load (1‐in‐500 years), as well as, the interstorey drift under the service wind (1‐in‐10 years); (ii) apply the 60 min. wind load history on earthquake damaged building; (iii) assess the building response in terms of interstorey drift and residual interstorey drift, and (iv) compare the results of the case study under (1) earthquake on intact building, (2) wind on intact building, and (3) wind on earthquake damaged building. The findings are significant and allow the realistic representation of the effects of multiple hazards on steel buildings. In summary, the consequent hazard on building safety has a detrimental effect.
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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".