Turbulent Transition Model Validation with Multiple Rotors for Industry Application
Bibliographic record
Abstract
The Langtry-Mentor transition model with k-w Shear Stress Transport (SST) model has been assessed for multiple rotors. In this assessment, an adverse impact of the sustaining term has been identified and a modification has been introduced. It was found that the original sustaining term behaved poorly for the separated flows investigated herein, making separation worse and leading to a premature stall in hover. The modified sustaining term uses F1-μ_t blending to deactivate the sustaining term inside boundary layer. The Langtry-Mentor transition model with the modified sustaining term has been validated for multiple rotors with various scales and characteristics, including the XV-15 rotor, the Hover Validation and Acoustic Baseline (HVAB) rotor, and Sikorsky’s model- and full-scale rotors. Helios, with OVERFLOW as near-body solver, was used for these calculations. The validation showed very good correlation with measured hover figure of merit data for all rotors from low thrust to high thrust conditions, using a consistent transition model and sustaining-term settings. It was found that the modified sustaining term removed the adverse impact of the original sustaining term.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".