IABSE Task Group 3.1 Benchmark Results. Numerical Full Bridge Stability and Buffeting Simulations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it