Dual Point Redesign of Axial Turbines Using a Viscous Inverse Design Method
Bibliographic record
Abstract
A new dual-point inverse blade design method was developed and applied to the redesign of a highly loaded transonic vane, the VKI-LS89, and the first 2.5 stages of a low speed subsonic turbine, the E/TU-4 4-stage turbine that is built and tested at the university of Hannover, Germany. In this inverse method, the blade walls move with a virtual velocity distribution derived from the difference between the current and the target pressure distributions on the blade surfaces at both operating points. 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 dual-point inverse design method is then used to explore the effect of different choices of the pressure distributions on the suction surface of one or more rotor/stator on the blade/stage performance. The results show that single point inverse design resulted in a local performance improvement whereas the dual point design method allowed for improving the performance of both VKI-LS89 vane and E/TU-4 2.5 stage turbines over a wide range of operation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".