Strategies to Reduce Seismic Losses and Improve Seismic Loss Assessments
Bibliographic record
Abstract
While seismic design provisions have improved building safety and reduced collapse incidents, the socio-economic impact of earthquakes persists as a significant concern. Excessive residual drifts and damage to structural and non-structural components may lead to building demolition or costly repairs, resulting in business interruptions, economic losses, and protracted disaster recovery for cities. This thesis commences by exploring approaches to mitigate seismic losses by comparing controlled rocking braced frames (CRBFs) to more conventional ductile steel seismic force-resisting systems (SFRSs). Three widely used ductile SFRS types in the seismic design of buildings are special moment resisting frames (SMRFs), special concentrically braced frames (SCBFs), and buckling-restrained braced frames (BRBFs). However, these ductile SFRSs have been associated with prominent structural damage and substantial residual deformations in past observed earthquakes. CRBFs offer an alternative SFRS with less structural damage, but concerns exist about potential trade-offs, such as increased acceleration and displacement demands, and associated nonstructural damage. This thesis explores these trade-offs in buildings of varying heights with both ductile SFRSs and CRBFs, assessing the structural response under varying earthquakes and focusing on expected annual losses (EALs). The results show that CRBF-equipped buildings still have lower total EALs even when considering these factors. CRBFs offer designers a high degree of control during the design process, with previous research demonstrating low collapse risk across a broad spectrum of design options. However, some studies have also highlighted the increased demands on nonstructural components in CRBF buildings. Therefore, while CRBFs have shown satisfactory collapse performance for various design options, assessing these options in terms of nonstructural component performance is essential. This thesis examines how two design parameters, namely the response modification factor (R) for rocking joint design and the amplification factor for considering higher-mode forces in steel member capacity design, influence earthquake-induced losses in CRBFs. The results indicate that although total EALs do not differ significantly across various design options, the distribution of losses between repairable and irreparable losses varies. In the above-mentioned portions of the thesis, the seismic loss assessments follow the FEMA P-58 methodology, which involves two essential steps: first, evaluating damage using damage fragility curves, and then assessing the effects of this damage through consequence models. Both of these steps are critically evaluated in the second half of this thesis. Fragility curves, including those in the FEMA P58 library, typically use peak floor accelerations (PFAs) to estimate losses in acceleration-sensitive nonstructural components. However, PFAs, like peak ground accelerations (PGAs) for buildings, have limitations as engineering demand parameters (EDPs) because they do not reflect the period of these components. In search of suitable options for creating seismic damage fragility curves, this thesis evaluates fifteen other EDPs proposed in the literature. This thesis also addresses an ambiguity in FEMA P-58's consequence modeling. The modeling of economies of scale is an integral part of consequence modeling. However, the lack of a clear definition for aggregate damage, which is a factor that significantly influences component modeling of economies of scale, can substantially impact simulated repair costs, repair times, and performance assessment. Overall, this thesis provides insights into reducing seismic losses by designing CRBFs as an alternative to commonly used SFRSs, and into improving seismic loss assessments by enhancing the damage fragility curves and consequence models within the widely-used FEMA P58 methodology.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".