Wall adaptation and determination of residual wall interferences for a 2D and a 3D model in the transonic wind tunnel TWG of DLR
Bibliographic record
Abstract
The transonic wind tunnel TWG of DLR Gottingen has been modernized with respect to an improved flow quality as well as to the logistics of exchangeable test sections, operational reliability and productivity. It is presently equipped with a Laval nozzle (supersonic), a perforated test section (transonic) and a two-dimensional adaptive (subsonic) test section. The latter can perform 2D adaptive tests on wing profiles using the Cauchy integral formula for wall adaptation, as well as 2D wall adaptation for 3D models utilizing the Wedemeyer/Lamarche (VKI) procedure. For both cases the wall adaptation was successful. The 3D force results compare quite well nominally interference-free results and to results from another adaptive test section. The pressure distribution from the wing profile tests agree quite well with theoretical results. For the 3D model, residual wall interferences were determined. It was found that the wall interferences had been reduced to nearly zero on the centreline of the test section by wall adaptation. Spanwise averages of the residual wall interferences have been used for further corrections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".