Seismic Fragility Assessment of an Existing Multi-Span RC Bridge Equipped with Risk Mitigation Systems
Bibliographic record
Abstract
The vulnerability of bridges and the effectiveness of suitable mitigation techniques in regions exposed to different seismic scenarios, while lacking reliable fragility assessment studies for existing bridge inventory, need focused attention. Further, while several retrofit techniques were proposed for improving the seismic performance of existing bridges, the limitations of such approaches need further investigation. Thus, this study assesses the seismic vulnerability of a benchmark structure representing pre-seismic code multi-span bridges in an earthquake-prone region before and after the retrofit to mitigate earthquake-related losses. The numerical modeling approaches of the selected bridge and retrofit systems were verified using the results of previous experimental studies. Detailed three-dimensional fiber-based (3DFB) simulation models were then developed to assess the seismic response of the benchmark bridge under the effects of diverse earthquake records representing far-field and near-source seismic scenarios in both longitudinal and transverse directions. The obtained results from several inelastic pushover analyses (IPAs) and incremental dynamic analyses (IDAs) confirmed the vulnerability of the benchmark bridge and the pressing need for mitigation actions to reduce the expected seismic losses under different seismic scenarios. Higher damage probabilities were observed under the effects of far-source events and at lower intensities than their near-field counterparts. Based on the probabilistic assessment study, it is concluded that retrofitting the bridge with buckling restrained braces (BRBs) is an effective mitigation measure to increase the lateral strength and overcome the high curvature ductility (CD) demands observed in bents, particularly under the most critical seismic scenario. The study provides insight into the impacts of contemporary retrofit techniques on improving the seismic performance of substandard bridges and presents a range of fragility functions for the assessment and mitigation of earthquake risks.
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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 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.001 | 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".