Novel Approach to Characterizing Tare & Interference Effects on the Lockheed Martin CRANE Wind Tunnel Model
Bibliographic record
Abstract
View Video Presentation: https://doi.org/10.2514/6.2023-2494.vid A novel approach for identifying and quantifying wind tunnel strut interference effects was developed for a wind tunnel test with the Lockheed Martin DARPA CRANE model. The large-scale wind tunnel measurements were done at the Wichita State University National Institute for Aviation Research Beech Wind Tunnel facility. A smaller model that included a replica of the support strut was used in the Lockheed Martin Low-speed 2 Wind Tunnel that measured the force and moment distortions created by the presence of the support strut. Differences in Reynolds numbers between the large- and small-scale facilities were determined to be insignificant to the strut interference corrections. As a result, high-quality aerodynamic force and moment data were obtained from the NIAR Beech Wind Tunnel test, which resulted in excellent agreement with computational fluid dynamic simulations.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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 | 0.000 |
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".