Risk‐targeted seismic evaluation of functional recovery performance in buildings
Bibliographic record
Abstract
Abstract Past earthquakes have highlighted the impact of prolonged downtime on community recovery. The introduction of performance objectives expressed in terms of recovery time has been identified as a key goal for the next generation of building codes. Recent development of downtime estimation frameworks now allows for the discussion of how to use recovery time estimates to (1) establish recovery‐targeted performance and (2) assess the functional recovery performance of buildings designed with modern code provisions. In this paper, we employ methods adapted from life‐safety provisions to evaluate building functional recovery performance using downtime simulation outputs. A scenario‐based, an intensity‐based and a risk‐targeted analysis of functional recovery performance objectives are presented. The functional recovery performance of a series of modern residential reinforced concrete shear wall archetype buildings, ranging from eight to 24 stories in height, at a site in downtown Seattle, Washington, are then assessed. Results of the scenario‐based assessment of an M9 Cascadia Subduction zone earthquake, comparable to an intensity‐based assessment at the 975‐year intensity level, show that the probability of achieving functional recovery within four months is close to zero, while the likelihood of achieving functional recovery by one year is approximately 60%. The results of the risk‐targeted assessment of the archetype buildings show a 50% probability in 50 years of the building downtime to functional recovery exceeding one month, a 43% in 50‐year probability of the downtime exceeding four months and an 8% in 50‐year probability of downtime exceeding one year. Finally, the expected annual downtime is approximately three days for all building heights considered. Disaggregation was used to identify intensity levels that contribute most of the downtime risk. The risk of downtime exceeding one month to one year is dominated by frequent, low‐intensity earthquakes (e.g., 100‐year return period). The risk of exceeding longer recovery times is dominated by less frequent, higher intensity earthquakes (i.e., return periods greater than 975 years). While the results of the analysis are sensitive to assumed damage thresholds and impeding factor delays triggered at low intensity levels, the findings suggest that reinforced concrete shear wall buildings designed following current building codes have a high risk of lengthy downtimes. Ultimately, the proposed methods and results illustrate the importance of introducing recovery‐based provisions into the next generation of building codes.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".