CFD Simulation of Ground Vortex Intake Test Case using ANSYS FLUENT
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2022-0222.vid The primary objective of this paper is to assess the ability of the general purpose CFD code, ANSYS Fluent, to predict ground vortex effects when an intake is placed near the ground and under crosswind conditions as defined by the 5th Propulsion Aerodynamics Workshop (PAW-05). Three crosswind speed configurations are studied. A hierarchy of workshop-supplied computational meshes is employed to perform mesh-independence studies. The anisotropic mesh adaptation module, ANSYS OptiGrid, is applied to precisely capture the ground and trailing vortices formed at the intake. The general-purpose k-ω Shear Stress Transport (SST) turbulence model is used to perform all simulations. Numerical predictions of total pressure recovery and distortion coefficient are compared against existing experimental data at a plane representative of the fan face at the engine intake, the Aerodynamic Interface Plane (AIP). In addition, incoming boundary layer profiles, surface static pressure plots, flow field contours and streamlines are used to study the complex physics generated by the presence of the intake in close proximity to the ground.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".