A Computational Framework for the Aerodynamic Shape Optimization of Long-Span Bridge Decks
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Bibliographic record
Abstract
A computational framework for automated shape modification of long-span bridge decks is proposed. The proposed technique involves the use of computational fluid dynamics (CFD) for aerodynamic analysis, surrogate models for response function approximation and numerical optimization routines for iterative selection of optimal shapes. A brief review of aerodynamic shape modification measures for decks of long-span bridges is presented. The framework is applied for aerodynamic fairing design of a typical plate-girder stiffened deck with the objective of reducing the lateral wind load and improving aerodynamic stability under smooth flow. Numerically evaluated optimal fairing shapes are compared with that of Bronx Whitestone Bridge and Deer Isle Bridge. It is shown that sharper triangular fairings are effective to reduce wind induced drag, but shorter fairings with height around 60% to 70% of deck depth are effective to improve the aerodynamic stability of elongated H-shaped decks. Furthermore, asymmetric triangular fairings are found to be effective to improve the aerodynamic performance of asymmetric decks.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it