Influence of Stator Hub Cavities on the Forced Response Behaviour of an Embedded Compressor Rotor
Bibliographic record
Abstract
Abstract This paper focuses on the impact of hub labyrinth seal leakage flows on the aeromechanical behavior of an embedded compressor rotor. End wall flows are critical in determining the performance of gas turbine engine compressors, particularly the hub leakage flows that can contribute to a significant reduction in performance due to the loss in efficiency induced by the leakage. While the current literature does contribute extensively to the understanding of the influence of this leakage flow on the steady compressor performance, no attention has been given to its impact on the multi-row unsteady aeromechanical influence. The authors of this paper have talked about the multi-row influence at various modes and operating condition using models without the hub cavities included [11–12;33–34]. The embedded compressor rotor utilized for this study is a part of a 3.5 stage subsonic rig located at the Zucrow Laboratory at Purdue University. The current paper first addresses the steady aerodynamics of a multi-row compressor with hub cavities and talks in detail about the effect of cavities on the performance at both the torsional mode and a higher order mode. Next the influence on the forcing function utilizing both 3-row (S1/R2/S2) and 4-row (S1/R2/S2/R3) simulations at both the Peak Efficiency (PE) and the High Loading (HL) operating conditions is determined. To reduce the computational domain significantly, the time transformation (TT) method was utilized within ANSYS CFX. The first part of the paper describes the multi-row influence of two neighboring stators having the same vane count, which excites the embedded rotor at the same resonant frequency; the second part shows the influence of having physical waves reflecting from a rotating row downstream (R3). The results show the significance of modelling the stator hub cavities and the drastic improvement in the modal force prediction with the cavities included. However, the authors observed that the impact tends to be more significant when the computational domain is small, i.e., fewer rows are included. As the number of rows are increased the influence of hub cavities diminish. Some of the conclusions drawn from this study are: 1) The presence of hub cavities changes the angle of incidence to the stators thereby reducing flow separation at the hub. The influence of these propagate throughout the domain i.e., a change in the angle of incidence in the first stage has an effect even at a downstream row. 2) The modal force prediction improved by ∼10% for the 3-row case and 1% for the 4-row case and the values moved closer to the experimental values in both cases. 3) The influence of hub cavities is more significant at torsional modes compared to higher order modes.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".