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Record W3181992747 · doi:10.21203/rs.3.rs-689165/v1

Unsteady Aerodynamic Performance of a Maglev Train: The Effect of the Ground Condition

2021· preprint· en· W3181992747 on OpenAlexaff
Meng Shi, Guang Chen, Dan Zhou, Shuang Meng

Bibliographic record

VenueResearch Square · 2021
Typepreprint
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsMaglevWakeVortex sheddingDetached eddy simulationVortexAerodynamicsCrosswindWake turbulencePhysicsMechanicsGround effect (cars)Aerospace engineeringEngineeringComputational fluid dynamicsMeteorologyTurbulenceReynolds-averaged Navier–Stokes equations

Abstract

fetched live from OpenAlex

Abstract The effect of the ground condition on unsteady aerodynamic performance of maglev train was numerically investigated with an IDDES (Improved Delayed Detached Eddy Simulation) method. The accuracy of the numerical method has been validated by wind tunnel experiments. The flow structure, slipstream and aerodynamic force around the train under stationary and moving ground conditions were compared. Compared with the stationary ground condition, the vortex structure under the condition of moving ground generated by the wake region is narrower and higher because of the track. Near the nose point of the head and tail vehicles, the peak value of slipstream under the condition of moving ground is slightly higher than that under stationary ground. In the wake area, the effect of the main vortex structure on both sides of the tail vehicle and the track makes the vortex structure in the wake area stronger than that under moving ground, the slipstream peak is larger and the locus thereof is further forward. Under the two ground conditions, the vortex structure is periodically shed from both sides of the train into the wake area, and the shedding frequency of the main vortex under the moving ground condition is lower than that under the stationary ground condition. Moving ground can increase the resistance of the maglev train, reduce the lift of the maglev train, and decrease the standard deviation of the maglev train’s aerodynamic force.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.140
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.314
Teacher spread0.296 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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