Prediction of De-Swirled Radial Inflow in Rotating Cavities With Hysteresis
Bibliographic record
Abstract
De-swirl nozzles are sometimes used in turbomachinery to reduce the pressure drop when air is drawn radially inwards through a rotating cavity. However, this can lead to non-unique steady state solutions with operating conditions achieved depending on how the steady point is approached. In the present study, a transient, 1D model of flow in a rotating cavity has been created. The model allows the vortex profile to change with through flow rate, and links this to estimates of disk windage, tangential velocity and, consequently, the vortex pressure gradient. The model was applied to the simulation of de-swirl nozzle fed, rotating cavities with radial inflow. The steady vortex flow characteristics (non-dimensional flow versus pressure ratio) predicted by the model were validated for 2 distinct cases. For a smooth rectangular cavity the flow characteristic was predicted using the model’s default parameters. For an engine-representative case with non-axisymmetric geometric features, the flow characteristic of the cavity was reproduced with some alignment of the model. The transient model reproduced experimentally observed hysteresis, discontinuity in operating characteristics, and regions where no steady-state solution could be found. A transient model is required as a steady state model would choose one of the possible solutions without physical justification. In the case of the engine-representative rig, part of the flow characteristic could not be obtained in testing. This is determined to be due to the interaction of the negative resistance region of the vortex and the flow modulating valve characteristic. Measures that allow the full capture of the flow characteristic in rig testing are identified.
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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".