Seismic loss comparison for buildings designed with ductile steel seismic force‐resisting systems and with controlled rocking braced frames
Bibliographic record
Abstract
Observations from past earthquakes have highlighted the structural damage and significant residual deformations experienced by ductile steel seismic force‐resisting systems (SFRSs), such as special moment resisting frames (SMRFs), special concentrically braced frames (SCBFs), and buckling‐restrained braced frames (BRBFs). To mitigate these challenges, controlled rocking braced frames (CRBFs) have emerged as a promising low‐damage alternative SFRS. However, concerns have been raised about whether the reduction in structural damage with CRBFs may come at the cost of increased acceleration demands and associated nonstructural damage. This study offers a comprehensive investigation of such trade‐offs by analyzing three buildings of different heights, each designed with the three ductile SFRSs identified above and with CRBFs. After examining the structural response at different earthquake intensities, the focus of the paper is on earthquake‐induced economic losses. Among the considered SFRSs, greater total expected annual losses (EAL) are observed in the SMRF and SCBF buildings, primarily due to demolition losses and repairable losses, including repairs of structural and nonstructural components. The total EAL is lower for the BRBFs and lowest for the CRBFs, with the losses in the BRBF buildings primarily attributed to demolition loss, considered as irreparable loss, while the losses in the CRBF buildings are mainly due to acceleration‐sensitive nonstructural components, considered as reparable loss. To provide a more detailed comparison, cost‐effectiveness analyses are also performed, indicating that a modest cost premium for CRBFs is justified to reduce earthquake economic costs over the building lifetime.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".