Attenuation of Inlet Distortion Effects on Fans Using Asymmetric Inlet Guide Vanes
Bibliographic record
Abstract
Abstract This research proposes and preliminarily analyzes a novel concept to passively reduce the negative impact of deep inlet distortion on the fan of an aero-engine. It consists of placing a row of non-axisymmetric inlet guide vanes (IGVs) just upstream of the fan rotor to induce a spatially varying swirl distribution. The swirl distribution is tailored so as to reduce flow incidence in the distorted flow region and increase it in the undistorted flow region to decrease the fluctuation in aerodynamic force on the fan blades under large inlet distortion that can lead to blade failure, as well as attenuate the negative effect of flow non-uniformity on fan/engine aerodynamic performance. A computational study is carried out on a high-speed (transonic) fan rotor (NASA Rotor 67) from a published distortion study using full-annulus unsteady 3D computational fluid dynamics (CFD) simulations. The asymmetric IGV is designed through a process of manual iterations and CFD simulations to take into account the change in flow redistribution with IGV geometry. The asymmetric IGV design, though not optimized, reduces the aerodynamic force variation amplitude by around two-thirds. Moreover, it allows the fan to recover over half of the loss in total pressure rise due to inlet distortion. The asymmetric IGV is also able to reduce the total pressure distortion at the fan rotor exit. Spanwise analysis indicates that the effectiveness of the asymmetric IGV can be improved on all three metrics if better 3D IGV shaping is performed.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".