Estimating economic losses of midrise reinforced concrete shear wall buildings in sedimentary basins by combining empirical and simulated seismic hazard characterizations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Summary Studies of recorded ground motions and simulations have shown that deep sedimentary basins can greatly increase the intensity of earthquake ground motions within a period range of approximately 1–4 s, but the economic impacts of basin effects are uncertain. This paper estimates key economic indicators of seismic performance, expressed in terms of earthquake‐induced repair costs, using empirical and simulated seismic hazard characterizations that account for the effects of basins. The methodology used is general, but the estimates are made for a series of eight‐ to 24‐story residential reinforced concrete shear wall archetype buildings in Seattle, WA, whose design neglects basin effects. All buildings are designed to comply with code‐minimum requirements (i.e., reference archetypes), as well as a series of design enhancements, which include (a) increasing design forces, (b) decreasing drift limits, and (c) a combination of these strategies. As an additional reference point, a performance‐based design is also assessed. The performance of the archetype buildings is evaluated for the seismic hazard level in Seattle according to the 2018 National Seismic Hazard Model (2018 NSHM), which explicitly considers basin effects. Inclusion of basin effects results in an average threefold increase in annualized losses for all archetypes. Incorporating physics‐based ground motion simulations to represent the large‐magnitude Cascadia subduction interface earthquake contribution to the hazard results in a further increase of 22% relative to the 2018 NSHM. The most effective of the design strategies considered combines a 25% increase in strength with a reduction in drift limits to 1.5%.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 it