Redesign of a Low Speed Turbine Stage Using a New Viscous Inverse Design Method
Bibliographic record
Abstract
The midspan section of a low speed subsonic turbine stage that is built and tested at DFVLR, Cologne, is redesigned using a new inverse blade design method, where the blade walls move with a virtual velocity distribution derived from the difference between the current and target pressure distributions on the blade surfaces. This new inverse method is fully consistent with the viscous flow assumption and is implemented into the time-accurate solution of the Reynolds-averaged Navier–Stokes equations. An algebraic Baldwin–Lomax turbulence model is used for turbulence closure. The mixing plane approach is used to couple the stator and rotor regions. The computational fluid dynamics (CFD) analysis formulation is first assessed against the turbine stage experimental data. The inverse formulation that is implemented in the same CFD code is assessed for its robustness and merits. The inverse design method is then used to study the effect of the rotor pressure loading on the blade shape and stage performance. It is also used to simultaneously redesign both stator and rotor blades for improved stage performance. The results show that by carefully tailoring the target pressure loading on both blade rows, improvement can be achieved in the stage performance.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".