Rotor-Stator Interaction Scenarios for the Centrifugal Compressor of a Helicopter Engine
Bibliographic record
Abstract
The present paper deals with interaction phenomena that may arise in the centrifugal compressor of helicopter engines when structural contacts occur between the blade-tips and the surrounding casing. Those phenomena may lead to increased levels of vibration and are currently under investigation for axial compressors of aircraft engines for which blade failures were observed. The growing understanding of these phenomena allows for more challenging numerical simulations with increased geometrical complexity such as centrifugal compressors. The simulation of blade-tip/casing contacts is carried out based on an existing strategy previously introduced by the authors. An ovalized casing is considered and two contact configurations are investigated: (1) a single blade impacts the casing and (2) contact may occur on any blade of the cyclic assembly. Based on these two contact scenarios, an in-depth analysis is performed through both time and space Fourier transforms. Results highlight the plausibility of blade/casing interaction phenomena similar to those observed in axial compressors since interactions are detected with localized vibration levels on a single impacting blade. When contact is treated on all the blades of the centrifugal compressor, the witnessed interactions feature a higher degree of complexity and usual criteria become insufficient to predict interaction speeds as well as the location of significant peaks of vibration in the frequency domain.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.000 |
| 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".