Flexural Assessment of Existing Slab Bridges in The Pacific Northwest Region Under Long-Duration Earthquake Effects
Bibliographic record
Abstract
Previous research has been conducted on the vulnerability of bridges, but there is a gap in assessing the vulnerability of existing bridges, such as slab bridges, when subjected to long-duration earthquakes in regions with high seismic activity.This study provides a unique quantification and assessment of the impacts of an anticipated moment magnitude (MW) 9.0 earthquake event characterized by its long-duration on the incipient collapse risk of slab bridges in the Pacific Northwest (PNW) region.The assessment encompasses the potential for flexural failures in the columns of slab bridges and the risk of collapse.A slab bridge is modeled in OpenSees as case studies to quantify the vulnerability and risk of incipient collapse using fragility analyses and risk-targeted approach per the 2023 AASHTO Guide Specifications for LRFD Seismic Bridge Design.This study highlights the consequences of the lack of strict seismic design standards in older design codes, especially for slab bridges built before the 1990s.In addition, the findings of this research have shown the impact of long-duration earthquakes on their potential to drastically increase collapse risks of aging slab bridges built before the 1990s.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".