Nonlinear Wind Tunnel Tests of Cable-Supported Bridges
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Bibliographic record
Abstract
Following the collapse of the Tacoma Narrows Bridge due to an aeroelastic instability, it has been common practice to test cable-supported bridges in a wind tunnel to check the soundness of bridge designs with respect to wind dynamic actions. Due to their simplicity, versatility and cost effectiveness, section model tests have become the standard approach for testing bridges. More advanced testing techniques, like full-aeroelastic model tests, are only utilized for validation purposes toward the end of the design process. Nevertheless, some generalizations with regard to the behavior of the bridge are necessary in section model tests in order to reach such simplicity. One of them is that they assume a linear structural behavior of the bridge structure. This might be inaccurate for very long cable-supported bridges as the structural behavior of such bridges is governed by their cable system, which is geometrically nonlinear. Considering that span lengths are getting longer, it is believed that it is needed to develop a better understanding of the influence of geometric nonlinearities on the wind response of bridges. Thus, this paper presents an experimental assessment of the effect of structural nonlinearities on the aeroelastic stability and wind response of cable-supported bridges. At first, the development of a new experimental apparatus for nonlinear section model tests of bridges is discussed. Then, the results of nonlinear section model tests conducted using the experimental apparatus are presented. Three different suspension bridge configurations are tested. The first one is for a single-box girder suspension bridge, and the second and third ones are for two twin-box girder suspension bridges having different span lengths. By comparing the results of linear tests to those of nonlinear tests, it is possible to assess the effect of structural nonlinearities. It is found that structural nonlinearities can have an effect on the critical velocity for flutter.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it