Lifetime Resilience Measurement of River-Crossing Bridges with Scour Countermeasures under Multiple Hazards
Bibliographic record
Abstract
River-crossing bridges are often subject to multiple hazards, including foundation scour, seismic attacks, and environmental degradation. When river-crossing bridges are in service, they should be restored rapidly after any disruption over their lifetime. To achieve this resilient quality, it is necessary to assess the system resilience subjected to multihazard impacts and the beneficial effects of any retrofitting or hazard-countermeasure in a lifetime context. To river-crossing bridges, one important intervention is to implement scour countermeasures. This study presents a probabilistic framework to quantify the lifetime system resilience of river-crossing bridges subject to multiple hazards. Notably, the framework is designed to reveal how progressive and abrupt hazards interact and result in resilience degradation and how scour countermeasures contribute to resilience enhancement. Experimental outcomes reveal the positive and distinct effects of implementing scour countermeasures at different times. The proposed framework is expected to assist civil engineers in conducting lifecycle management of river-crossing bridges that are subject to hydraulic scour and demand timely countermeasures.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".