Impact of Earthquake Types and Aftershocks on Loss Assessment of Non‐Code‐Conforming Buildings: Case Study with Victoria, British Columbia
Bibliographic record
Abstract
This paper presents a study on the impact of earthquake types (shallow crustal, deep inslab, and megathrust Cascadia interface earthquakes) and aftershocks on loss assessment of non‐code‐conforming reinforced concrete (RC) buildings. The loss assessment is formulated within the performance‐based earthquake engineering framework. The dependency between the maximum and residual inter‐story drift ratios are captured using copulas. Finite‐element models that take into account key hysteretic characteristics of non‐ductile RC frames were adopted and incremental dynamic analysis is utilized to compute collapse risk. The proposed procedure is applied to a set of 2‐, 4‐, 8‐, and 12‐story non‐ductile reinforced concrete frames located in Victoria, British Columbia, Canada. From the results, the aftershock showed marked difference for the 2‐story building. At annual probability of 10 −2 –10 −3 , crustal and inslab events with M w 6.5 to M w 7.5 contributed the most to the loss as these events occur more frequently. At rarer annual probability of 10 −3 –10 −4 , the Cascadia event having M w 8.5 to M w 9.0 is predominant and contributed the most to the loss.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".