Super-Long Span Bridge Aerodynamics: First Results of the Numerical Benchmark Tests from Task Group 10
Bibliographic record
Abstract
The IABSE Task Group 10 (super-long span bridge aerodynamics) has the mandate to create a standard procedure for validation of methodology and software programs applied for stability and buffeting response analyses of super-long span bridges. Precise estimations of structural stability and response to strong winds are critical for the successful design of long-span bridges. Task Group 10 covers several important problems related to its mandate including: review and verification of methods developed and adopted by researchers and bridge designers; the definition of guidelines and sample tests for verification and calibration of analytical procedures; identification of fundamental problems of the computation methods; relevant input and output data. Since the beginning of its work, this working group has developed a 3-step benchmark, with multiple sub-steps of fundamental problems to resolve. The first step of this benchmark has been a numerical comparison of the results obtained using different models adopted across the workgroup members. Using the same inputs: flutter stability and the buffeting response of both a deck sectional model and a full bridge are studied. Step 2 will be the comparison of predicted results and experimental tests in wind tunnels, and Step 3 will be of validation against full scale measurements. In this paper, the results of Step 1 will be presented, highlighting critical issues and differences found during the comparison of results. The response of a 3-degrees of freedom bridge deck will be presented both in terms of aeroelastic stability and buffeting response. The results presented are intended to be a reference for the validation of methodologies and software programs that solve for wind response of bridges.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".