Seismic resilience of typical code‐conforming RC moment frame buildings in Canada
Bibliographic record
Abstract
This article examines the baseline resilience of reinforced concrete (RC) moment frame buildings conforming to the seismic design standards of Canada. Metrics for robustness, rapidity, and resilience are evaluated to capture the system’s reliability, speed of recovery, and socioeconomic impacts. Buildings of different heights are evaluated using nonlinear time‐history analyses. Six damage states are defined as disjoint branches of an event tree depending on the building’s path to recovery. For a scenario earthquake of magnitude 7.3 magnitude at a distance of 30 km from Vancouver, the housing occupancy recovery trajectory is developed. Monte Carlo simulations are used to propagate uncertainty from seismic hazards to the building response to the lead time required for recovery. Buildings are found to maintain 50%–65% of their pre‐event housing occupancy in the immediate aftermath. The housing occupancy is restored to 90% within 2–4 months, with a shorter recovery period for low‐rise buildings, whereas the system resilience level requires 6 months to 1 year for restoration to 90%. Empirical data from the Loma Prieta (1989) and Northridge (1994) earthquakes are used to compare analytically predicted repair times. The findings from this article will facilitate the shift to resilience‐based design in Canada.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".