Loss and Downtime Assessment of RC Dual Wall–Frame Office Buildings Toward Resilient Seismic Performance
Bibliographic record
Abstract
This study quantitatively assesses the impact of seismic design strategies on the performance of reinforced concrete (RC) dual wall–frame office buildings by comparing direct and indirect economic losses and downtime in life-cycle terms. A high-rise archetype building located in Santiago, Chile, on stiff soil was evaluated as a benchmark case study. Three design strategies to potentially enhance the seismic performance of a building designed conventionally were explored: (i) incorporating fluid viscous dampers (FVDs) in the lateral load-resisting structure; (ii) replacing conventional non-structural components with enhanced ones (ENCs); and (iii) a combination of the previous two strategies. First, probabilistic structural responses were estimated through incremental dynamic analyses using three-dimensional nonlinear models of the archetypes subjected to a set of hazard-consistent Chilean ground motions. Second, FEMA P-58 time-based assessment was conducted to estimate expected annual losses (EALs) for economic loss estimation. Finally, for downtime assessment, a novel probabilistic framework, built on the FEMA P-58 methodology and the REDi guidelines, was employed to estimate the expected annual downtimes (EADs) to achieve specific target recovery states, such as reoccupancy (RO) and functional recovery (FR). Results revealed that seismically enhancing RC dual wall–frame buildings with FVDs significantly improves resilience by reducing loss and downtime. For example, the enhanced building with FVDs achieved an EAL of 0.093% and EAL of 8.6 days for FR, compared to the archetype base building without design improvements, which exhibited an EAL of 0.125% and an EAD of 9.5 days for FR. In contrast, the impact of ENCs alone was minor, compared to the effect of FVDs, with an EAL of 0.106% and an EAD of 9.1 days for FR. With this detailed recovery modeling, probabilistic methods, and a focus on intermediate recovery states, this framework represents a significant advancement in resilience-based seismic design and recovery planning.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".