Comparison of Rotor - Fuselage Flow Fields and Unsteady Tail Interactions between Two CFD Codes and Experiment
Bibliographic record
Abstract
Experimental measurements of the unsteady flow fields generated by a scale model rotor, hub, and fuselage, plus the unsteady loads generated on a horizontal stabilizer, have been used as the basis for comparison to two computational fluid dynamics (CFD) simulations. The STAR-CCM+ commercial solver and CREATETM-AV HELIOS using the KCFD and SAMCART solver were applied to a series of seven test cases. The configurations were fuselage and hub with blades-on and blades-off for velocity fields, as well as the stabilizer in two locations for unsteady normal forces. The quantities examined included time averaged rotor, hub, fuselage, and tail forces and moments, time averaged, unsteady, and periodic velocities, and stabilizer forces. Overall for the forces and velocities, both codes did well for the time averages, and captured the trends and qualitative features of the unsteady quantities. Cases driven by a strong tip vortex – stabilizer interaction were modelled well, the key issue being rotor tip path plane trim. Cases driven by combined wakes from the hub, fuselage, and forward pointing blades were more challenging, and the codes often under-predicted the unsteady amplitudes or differed in the distribution of frequencies. Since this was accompanied by higher than measured Reynolds stresses, one cure may be resolved smaller scales in the solutions, increasing the order, or improving the turbulence modelling to better preserve the unsteady flow structures. However, application for industrial design still requires computational efficiency.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".