Numerical Simulation with a DES Approach for a High-Speed Train Subjected to the Crosswind
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Bibliographic record
Abstract
A Detached Eddy Simulation (DES) method based on the SST k-ω turbulence model was used to investigate the instantaneous and time-averaged flow characteristics around the train with a slender body and high Reynolds number subjected to strong crosswinds. The evolution trends of multi-scale coherent vortex structures in the leeward side were studied. These pressure oscillation characteristics of monitoring points on the train surfaces were discussed. Time-averaged pressure and aerodynamic loads on each part of the train were analyzed inhere. Also, the overturning moment coefficients were compared with the experimental data. The results show that the flow fields around the train present significant unsteady characteristics. Lots of vortex structures with different intensities, spatial geometrical scales, accompanied by a time change, appear in the leeward side of the train, in the wake of the tail car and below the bottom of the train. The oscillation characteristics of the flow field around the train directly affect the pressure change on the train surfaces, thereby affecting the aerodynamic loads of the train. The loads of each car fluctuate around some certain mean values, while the positive peak values can be higher than the mean ones by up to 34%. The load contributions of different parts to the total of the train are also obtained. According to it, to improve the crosswind stability of the high-speed train, much more attention should be paid on the aerodynamic shape design of the streamlined head and cross section. In addition, this work shows that the DES approach can give a better prediction of vortex structures in the wake compared with the RANS solution.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
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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