Estimating a Seismic Wave Velocity for Exciting the Greatest Anticipated Vertical Deck Displacement of a Cable-Stayed Bridge Subjected to Asynchronous Excitation
Bibliographic record
Abstract
Abstract The purpose of this study is to examine the effects of the seismic wave velocity on vertical displacement of a cable-stayed bridge’s deck under asynchronous excitation. The Quincy Bayview Bridge located in Illinois, USA, and four other generic bridges are selected for the study. Ten records obtained from earthquakes in US, Japan, and Taiwan are used as input for the seismic excitation in the time-history analysis. Two equations are proposed in this study to determine a critical seismic wave velocity that would produce the greatest vertical deck displacement. The critical wave velocity depends on the total length of the bridge, the fundamental period of the bridge, and the C-factor. The C-factor in this study is 0.72, which is based on analyzed results from the five selected bridges. The two equations and the C-factor are verified through application on two 3-span cable-stayed bridges studied previously by Nazmy and Abdel-Ghaffar. The proposed C-factor of 0.72 is recommended for use for typical 3-span cable-stayed bridges with a side-to-main span ratio of about 0.48. The methodology developed in the study, however, can be applied to any specific bridge to examine the excitation of the deck vertical displacement under the longitudinal seismic ground motion.
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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 | 0.001 |
| 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 | 0.000 | 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".