IABSE Task Group 3.1 Benchmark Results. Part 2: Numerical Analysis of a Three-Degree-of-Freedom Bridge Deck Section Based on Experimental Aerodynamics
Bibliographic record
Abstract
IABSE Task Group 3.1 has the mandate to define reference results for the validation of methodologies and programs used to study both stability and buffeting responses of long-span bridges. To this end, the working group set up a benchmark procedure consisting of several steps with increasing complexity to define reference results useful for this validation. The simplest step (1.1a) was presented in Part 1. In this paper (Part 2), the contributions and reference results of the second sub-step (1.1c) are discussed. It consists of the simulation of the aeroelastic response of a three-degree-of-freedom bridge deck section forced by turbulent wind, using experimental aerodynamic coefficients measured in a wind tunnel. The increase in complexity, compared to the previous step, involves the experimental definition of unsteady force coefficients that are defined in a limited range of reduced velocities, and inclusion of the lateral motion and horizontal turbulent wind velocity components. Comparison of the different outputs, obtained by Task Group 3.1 participants with the same input data, is presented, revealing differences that are not always negligible. Moreover, the increase in complexity of the test case results in larger spreads of the results compared to the fully analytical case, analysed in Part 1.
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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 | 0.020 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".