Validating the URANS shear stress transport <i>γ</i> −<i>Re</i><sub>θ</sub> model for low‐Reynolds‐number external aerodynamics
Bibliographic record
Abstract
SUMMARY A numerical investigation on low‐Reynolds‐number external aerodynamics was conducted using the transitional unsteady Reynolds‐averaged Navier–Stokes shear stress transport γ −Reθ model and the ANSYS‐CFX computational fluid dynamics suite. The NACA 0012 airfoil was exposed to chord‐based Reynolds numbers of 5.0 ×104, 1.0 ×105 and 2.5 ×105 at 0°, 4°and 8°angles of attack. Time‐averaged and instantaneous flow features were extracted and compared with fully turbulent shear stress transport results, XFLR5 panel e N method results, and published higher order numerical and experimental studies. The current model was shown to reproduce the complex flow phenomena, including the laminar separation bubble dynamics and aerodynamic performance, with a very good degree of accuracy. The sensitivity of the model to domain size, grid resolution and quality, timestepping scheme, and free‐stream turbulence intensity was also presented. In view of the results obtained, the proposed model is deemed appropriate for modelling low‐Reynolds‐number external aerodynamics and provides a framework for future studies for the better understanding of this complex flow regime. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".