Drift‐ and energy‐based seismic performance assessment of retrofitted wood frame shear wall buildings: Shake table tests
Bibliographic record
Abstract
Abstract In 2004, the Province of British Columbia (BC) announced a multi‐year $1.5 billion seismic retrofit program for the province's 750 at‐risk public schools. The purpose of this program was to quantify the seismic risk of the province's public‐school buildings and to expedite the seismic upgrading of the most at‐risk schools. In order to provide a safe and cost‐effective implementation of this program, the Engineers and Geoscientists BC, in collaboration with the University of British Columbia, has developed a performance‐based probabilistic method and guidelines for the seismic risk assessment and retrofit of low‐rise buildings. As part of this initiative, a number of laboratory experiments have been conducted to provide data that would support the recommendations provided in the guidelines. The laboratory experiments included several full‐scale shake table tests of wood frame systems. The specimens were subjected to sequences of earthquake motions to simulate their performance under main shock‐aftershocks. This paper presents details of seven of the experiment and wood‐frame buildings considered. A detailed discussion of the results of the analyses of the shake table tests data, and performance assessment using drift‐ and energy‐based damage indices is presented. This study highlights the importance of considering the effects of subduction earthquake and mainshock‐aftershock sequences for design and retrofit of wood frame structures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".