Seismic performance of wood‐frame houses in south‐western British Columbia
Bibliographic record
Abstract
Abstract The seismic performance of conventional wood‐frame structures in south‐western British Columbia is analytically investigated through incremental dynamic analysis by utilizing available UBC‐SAWS models, which were calibrated based on experimental test results. To define an adequate target response spectrum that is consistent with information from national seismic hazard maps, record selection/scaling based on the conditional mean spectrum (CMS) is implemented. Furthermore, to reflect complex seismic hazard contributions from different earthquake sources (i.e. crustal events, interface events, and inslab events), we construct CMS for three earthquake types, and use them to select and scale an adequate set of ground motion records for the seismic performance evaluation. We focus on the impacts of adopting different record selection criteria and of using different shear‐wall types (Houses 1–4; in terms of seismic resistance, House 1>House 2>House 3>House 4) on the nonlinear structural response. The results indicate that the record selection procedures have significant influence on the probabilistic relationship between spectral acceleration at the fundamental vibration period and maximum inter‐story drift ratio, highlighting the importance of taking into account response spectral shapes in selecting and scaling ground motion records. Subjected to ground motions corresponding to the return period of 2500 years, House 1 is expected to experience very limited extent of damage; Houses 2 and 3 may be disturbed by minor damage; whereas House 4 may suffer from major damage occasionally. Finally, we develop statistical models of the maximum inter‐story drift ratio conditioned on a seismic intensity level for wood‐frame houses, which is useful for seismic vulnerability assessment. Copyright © 2010 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".