Special Issue on Recent Advances in Seismic Design, Analysis, and Protection of Highway Bridges
Bibliographic record
Abstract
Analysis and design of protection systems for highway bridges have witnessed extensive research activities in the last two decades.Researchers worldwide have studied highway bridges both analytically and experimentally and have documented the performances of highway bridges during recent earthquake events.Several damage mechanisms in both structural and geotechnical aspects of highway bridges have been recorded and analyzed in detail.Retrofit methods such as strengthening, base isolation, and other energy dissipative devices have been proposed, tested, and implemented in full-scale bridges.This special issue presents a spectrum of work from leading researchers highlighting the state of the art in the analysis, design, and protection of highway bridges.Estimation of seismic risk is a central element in earthquake engineering.Integral to this aspect are fragility curves, which relate the conditional probability of reaching or exceeding any damage state as a function of the hazard [e.g., peak ground acceleration (PGA)].Estimation of seismic risk is then undertaken by combining the seismic hazard and fragility curves using the total probability theorem.Papers in this special issue range from the estimation of fragilities using incremental dynamic analysis to using fragility curves as a measure to evaluate the performance of seismic protection systems and soil-structure interaction effects.Tehrani and Mitchell, in the paper "Seismic Risk Assessment of Four-Span Bridges in Montreal Designed Using the Canadian Bridge Design Code," assess the risk to 15 continuous four-span bridges in Montreal.All these bridges were designed according to the 2006 Canadian Highway Bridge Code and detailed with flexuredominated failures.By combining the seismic hazard to the Montreal region with the fragility curves for different limit states calculated using the incremental dynamic analysis, the authors conclude that the probability of exceeding these limit states is reasonably low.In the paper "Seismic Fragility Relationships of a Cable-Stayed Bridge Equipped with Response Modification Systems," Barnawi and Dyke present fragility curves developed using time-history analysis for a benchmark cable-stayed bridge subjected to 20 synthetic ground motions.The bridge was evaluated with various response modification systems, namely passive damper, an active control system, and a semiactive control system using magnetorheological (MR) dampers.Based on a comparison of their fragilities, the authors conclude that MR dampers are an effective response modification strategy for cable-stayed bridges.Wang et al., in the paper "Influence of Soil-Structure Interaction and Liquefaction on the Isolation Efficiency of a Typical Multispan Continuous Steel Girder Bridge," present results showing the effects
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.024 | 0.009 |
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".