Flow Control in an Aggressive Inter-Turbine Duct Using Low Profile Vortex Generators
Bibliographic record
Abstract
This paper presents the experimental investigation of the flow in an aggressive inter-turbine duct (AITD). The goal is to improve the understanding of the flow mechanisms within the AITD and of the underlying physics of low-profile vortex generators (LPVGs). The flow structures in the AITD are dominated by counter-rotating vortices and boundary layer separations in both the casing and hub regions. At the first bend of the AITD, the casing boundary layer separates in a 3D mode because of the upstream wakes; this is followed by a massive 2D boundary layer separation. Due to the effect of the radial pressure gradient at the first bend, the streamwise vorticity generated by the casing 3D separation stays close to the casing endwall, and later mixes with the casing counter-rotating vortices formed at the second bend. By using LPVGs with different configurations installed on the casing, the casing boundary layer separation is significantly reduced. The streamwise vortices generated by the LPVGs have the potential to generate another pair of counter-rotating vortices at the AITD second bend, which help to delay/prevent the boundary layer separation. Therefore, the total pressure loss in the AITD was significantly reduced.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".