Minimising Clearance Consumption: A Key Factor for the Design of Blades Robust to Rotor/Stator Interactions?
Bibliographic record
Abstract
The recent development of a numerical strategy dedicated to the simulation of rotor/stator interactions stemming from structural contacts in modern aircraft engines led to the first optimization of a high-pressure compressor blade profile accounting for criteria related to non-linear contact simulations. This optimization procedure revealed very significant improvements in terms of amplitudes of vibration but failed to identify key design parameters. Satisfying numerical results were obtained by a minor modification of a combination of many design parameters. Based on this observation, this contribution intends to shed a new light on this previous redesign operation focusing on one key quantity: the clearance consumption. This quantity is presented in the first section. In the second section, results of the redesign operation are recalled before the presentation of original results, featuring detailed interaction maps in the frequency domain, on which focuses the third section of the article. Finally, the blade profiles are extensively compared based on their specific clearance consumption and presented results suggest that this quantity may be key in discriminating acceptable from unacceptable blade profiles with respect to their vibratory behaviour when structural contacts occur.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".