Improving the Seismic Resilience of Existing Braced-Frame Office Buildings
Bibliographic record
Abstract
The concept of seismic resilience is defined as the capability of a system to maintain a level of functionality or performance in the aftermath of an earthquake event. In the research reported in this paper, a methodology for the seismic resilience assessment of existing braced-frame office buildings was developed. In this context, damage levels were defined as function of performance levels associated to earthquake intensity. Furthermore, fragility curves were derived from incremental dynamic analysis (IDA) curves obtained from time–history analyses using computer software and both aleatoric and epistemic uncertainties were considered. To illustrate the previously mentioned concept, a walkthrough of the methodology is presented in a case study comprising of existing 3-story and 6-story concentrically braced-frame (CBF) office buildings located in eastern Canada (Montreal and Quebec City) and western Canada (Vancouver). These buildings were designed in agreement with Canadian national code requirements. The proposed retrofit strategy is according to a United States standard and the retrofitted office buildings should meet the so-called basic safety rehabilitation objective class. In addition, all studied retrofitted buildings show enhanced earthquake resilience.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".