Prediction of Post-Earthquake Damage of Reinforced Concrete Highway Bridges
Bibliographic record
Abstract
<p>The prediction of earthquake damage to highway bridges is essential for informed decision on the post-earthquake bridge functionality. This paper presents a simplified method based on the development of fragility functions of typical reinforced concrete highway bridges and its validation. The concept of fragility functions represents a probabilistic relationship between the seismic intensity measure IM (e.g. spectral acceleration) and the degree of bridge damage. Median IMs of the fragility functions for the assumed damage states are developed using closed-form relationships based on the capacity spectrum method for seismic demand assessment. For each damage state, these relationships correlate the displacement threshold to the corresponding median IMs in terms of the input spectral acceleration at 1.0 sec. The simplified fragility assessment method was validated with dynamic analyses of an existing three span continuous girder reinforced concrete bridge in Quebec. The method revealed particularly useful for rapid vulnerability evaluation of a portfolio of bridges.</p>
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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 | 0.000 |
| 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 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".