A review on aerodynamic optimization of turbomachinery using adjoint method
Why this work is in the frame
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Bibliographic record
Abstract
Improvements in aerodynamic turbomachinery design have gained attraction due to the increased demand for a more sustainable future. Several optimization approaches have been presented and employed in the realm of aerodynamic design. However, among all of them, the adjoint approach has emerged as a hot research topic for aerodynamic optimization in the field of turbomachinery. The ability of this method to efficiently compute the derivatives of objective functions for several design variables has made it a promising optimization tool. This study provides a comprehensive review of all significant studies undertaken since the turn of the 21st century when the adjoint method was employed for the aerodynamic optimization of turbomachinery applications. The application of the adjoint approach in that context is extensively discussed under various aspects, including shape optimization in both steady and unsteady flows, varied eddy viscosity, non-ideal compressible fluid-dynamics, multi-objective and multi-point optimizations, multidisciplinary optimization, coupling adjoint method with other approaches, parametrization methods, and uncertainty quantification. Finally, the review concludes by highlighting key points and outlooks on future developments.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it