IABSE Task Group 3.1 Benchmark Results. Numerical Full Bridge Stability and Buffeting Simulations
Bibliographic record
Abstract
Aerodynamic stability and buffeting response due to turbulent wind have a fundamental importance for long-span bridge design. However, there are no benchmark cases that can be used as a reference estimate for an independent validation of the numerical methods and theoretical approximations. Therefore, the IABSE Task Group 3.1 proposal is to fill this gap by defining a reasonably well predicted set case for the response to wind of long-span bridges, both in terms of aerodynamic stability and buffeting. Specifically, a statistical analysis was performed on the numerical results collected by the task group participants, who used their own methodology and tools (either in time domain and/or frequency domain) to predict the bridge stability to flutter and buffeting response to wind, sharing the same input data (wind conditions, bridge structural properties, and deck aerodynamic coefficients). The benchmark results presented in this paper can be used as a point of reference for other numerical codes, and they include the onset of flutter speed, damping ratio variation with mean wind speed and the root mean square of the displacements as a function of mean wind speed, power spectral density values, and time histories of displacements.
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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 | 0.013 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".