Effect of wing height layout on the aerodynamic performance ofhigh-speed train
Bibliographic record
Abstract
Purpose This paper aims to investigate the effect of different wing height layouts on the aerodynamic performance and flow structure of high-speed train, in a train-wing coupling method with multiple tandem wings installed on the train roof. Design/methodology/approach The improved delayed detached eddy simulation method based on shear stress transport k-ω turbulence model has been used to conduct computational fluid dynamics simulation on the train with three different wing height layouts, at a Reynolds number of 2.8 × 106. The accuracy of the numerical method has been validated by wind tunnel experiments. Findings The wing height layout has a significant effect on the lift, while its influence on the drag is weak. There are three distinctive vortex structures in the flow field: wingtip vortex, train body vortex and pillar vortex, which are influenced by the variation in wing height layout. The incremental wing layout reduces the mixing and merging between vortexes in the flow field, weakening the vorticity and turbulence intensity. This enhances the pressure difference between the upper and lower surfaces of both the train and wings, thereby increasing the overall lift. Simultaneously, it reduces the slipstream velocity at platform and trackside heights. Originality/value This paper contributes to understanding the aerodynamic characteristics and flow structure of a high-speed train coupled with wings. It provides a reference for the design aiming to achieve equivalent weight reduction through aerodynamic lift synergy in trains.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".