Towards Reliable Experimental Drag Measurements on an Airfoil at Low Reynolds Numbers
Bibliographic record
Abstract
The effects of control volume boundary placement and common approximations on drag estimates obtained via the momentum integral method are investigated in this work. Wind tunnel experiments were performed on a NACA 0018 airfoil at a chord Reynolds number of 100,000. Four angles of attack were investigated, namely, 0°, 5°, 10°, and 15°. At the three lower angles of attack, a separation bubble forms on the upper surface of the airfoil; whereas, at the highest angle of attack investigated, the airfoil is stalled. Wake velocity measurements were performed with a cross-wire probe at several downstream locations, up to 4.5 chord lengths downstream of the model, to investigate the effect of the wake survey location on the drag estimate. In addition, test section pressure distributions were acquired to quantify the variation of the outer flow velocity and pressure along the test section. The acquired data were used to investigate the variability of drag estimates produced with commonly used assumption and momentum balance formulations. The results show that some common approximations can significantly affect the drag estimates, with changes of up to 200% observed in some cases. Furthermore, drag estimates can vary substantially with the position of the wake survey plane; however, the effect diminishes as the survey plane is moved further downstream. The findings highlight the importance of providing a detailed description of the methodology employed for estimating the drag via momentum integral analysis, so as to enable an adequate comparison and assessment of experimental results. Finally, the study offers some guidelines for conducting momentum integral analysis on airfoils in low Reynolds number flows.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".