Influence of Rotor-Stator Interaction and Reflecting Boundary Conditions on Compressor Forced Response
Bibliographic record
Abstract
This paper focuses on the rotor forced response behavior in a 3.5-stage compressor rig. The aim is to provide an accurate prediction of forced response with the less computational effort. Previous research indicates that by reducing the computation domain from 7-row to a 3-row stator-rotor-stator (S1-R2-S2) configuration, the forcing function is over-predicted by 60%. To address this over prediction, an investigation of boundary conditions and a study with additional rows are conducted. The influence of reflecting boundary conditions on the blade modal force is studied by preventing wave reflection. Additionally, a 5-row simulation is studied to take an extra source of excitation force, the IGV row with the same blade count as the other stators, into consideration. Three conclusions were drawn from this study: 1) boundary reflection has a significant influence on unsteady simulation and the modal force, thus should be avoided by using mesh treatment up and down stream; 2) the IGV wake contributes to the forcing function and cannot be ignored; 3) the clocking feature of IGV, S1, and S2 leads to a transfer of energy from 1st harmonic to other higher harmonics. This research provides a guidance of forced response modeling and can be employed for industrial forced response analysis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".