Review of seismic evaluation frameworks for highway bridges based on life cycle concepts
Bibliographic record
Abstract
In recent years the construction industry has extensively relied upon life cycle concepts embedded in service life evaluation methodologies for decision-making processes. In the present paper, these concepts are considered in the context of seismic evaluation of bridges taking into account the significant economic, social, and environmental impacts of seismic-induced damages to bridge networks. Considering the long service life of bridges and the possibility of multiple earthquakes occurring throughout their existence, it is crucial to conduct a comprehensive multi-faceted life cycle analysis of the effects of seismic events on the performance of bridges. There is still a lack of thorough and methodological examination of frameworks and methodologies for bridge infrastructure life cycle costing in seismic regions, but the field is constantly progressing. A comprehensive review is conducted in this paper on life cycle assessment of bridge infrastructure, specifically focusing in seismic regions, so as to assemble the advancements in the field and identify areas that require further research. The review focuses on the objectives, approach, methodology, integration with life cycle assessment, cost components, and uncertainty aspects of methods that have been proposed in the literature.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".