Defining Design Parameters for Controlled Rocking Braced Frames to Control Seismic Losses
Bibliographic record
Abstract
Controlled rocking braced frames (CRBFs) are a self-centering lateral force-resisting system aimed at reducing structural damage potential. Previous research has shown that relatively low design forces for rocking and for structural elements in CRBFs would be acceptable based on collapse fragility analysis. However, past studies have also highlighted the potential for significant story drifts and for increased demands on acceleration-sensitive nonstructural components installed in buildings with CRBFs. Therefore, while CRBFs have demonstrated acceptable performance in terms of collapse across a wide range of design options, these design options must be evaluated considering the performance of nonstructural components if the intended low-damage potential of CRBFs is to be fully realized. To address this need, this paper investigates the influence of two key design parameters on seismic losses of buildings with CRBFs, namely the response modification factor (R) for the rocking joint design and the amplification factor (γ) used to incorporate higher-mode forces into the capacity design of frame members. Three different heights of CRBF buildings are designed using different design options, with values of R ranging from 5 to 12 and with higher-mode forces considered based on two seismic intensity levels: the design earthquake (DE) and the maximum considered earthquake (MCE). Then, following an assessment of structural responses, the paper’s primary emphasis is on earthquake-induced economic losses. While the computed total expected annual losses (EALs) using various design options are remarkably similar, the distribution of losses attributed to collapse or to nonstructural components varies. The CRBFs with lower resistance to rocking exhibit greater losses attributed to collapse and to drift-sensitive nonstructural components, but this is counterbalanced by a simultaneous reduction in losses related to acceleration-sensitive nonstructural components. Furthermore, in taller CRBF buildings, using amplified higher-mode forces based on the MCE level slightly decreases total EALs compared to those using the DE level, primarily due to a reduction in collapse losses.
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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 | 0.001 | 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".