Analyzing the Dynamic Behavior of Suspension Bridge Towers Using GPS
Bibliographic record
Abstract
The aim of this work is to characterize the dynamic oscillation of the top of the towers of a suspension bridge with GPS and to analyze the resulting values by Fourier analysis and wavelet transform. It is a complementary research about the analysis of the dynamic movements of the Pierre-Laporte Suspension Bridge in Quebec City, Canada. A previous work [Larocca et al., 2005b] analyzed the deck’s movements of this bridge. Suspension bridge fundamentally consists of cables anchored to the earth at their ends and supported by towers at intermediate points. From these cables, a floor or 'deck' is suspended. Therefore, the towers have to be flexible enough to allow for changes in length due to live loads and temperature. Theoretically, the tower can be assumed as a thin beam. GPS data were collected at the towers of the bridge. The data sets were collected by researchers from the Centre de Recherche en Geomatique at Universite Laval in July 1996. One GPS receiver was installed on the top of each of the towers, both 110 m in height, whereas a third receiver was placed on the ground, used as reference. Two 3-hour GPS sessions with a data-sampling interval of 2 seconds were collected. As no other sensors were used for measuring the deflections, the conclusions about the results are supported by theoretical values.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".