Numerical Study on the Effect of Back Cavity on the Aerodynamic Behavior of a Non-Axisymmetric Casing Treatment for Transonic Axial Compressors
Bibliographic record
Abstract
Abstract For decades, aeronautic engineers have studied the potential of Casing Treatments (CT) to improve the aerodynamic operability of tip-limited compressors. Axial Slot Casing Treatment (or ASCT) has shown very good results on modern transonic compressor. One possible variant of ASCT uses a circumferential back cavity that links the slots outside the compressor main flow path. This study does a back-to-back comparison of two CT designs that differ only by the presence or the absence of the back cavity. The influence of both CT designs on transonic rotor performances and aerodynamics is presented. CT flows are detailed and analyzed. The analysis focuses on fluid exchanges between the CT and the main flow path. This study is based on CFD simulation; CFD results are, at first, confronted with available experimental data and then analyzed. Detailed CT flow analyses show that the presence of the cavity reduces the amplitude of the velocity fluctuations and allows for a more uniform redistribution of the recirculated mass flow. The presence of the back cavity reduces significantly the flow mass transfer between the main flow and the front part of the slots (situated before the rotor leading edge), as a consequence of the action of the transient vortex developing inside. In addition, the synchronization between the rotor blade passage and the extraction cycle, by the rear part of the slots, differs when back cavity is present or not. With the back cavity, the slot tends to extract mass flow mostly when it is close to the pressure side. Without the back cavity, the extraction is performed mostly in the middle of the blade channel. Because of these differences, the back cavity reduces the influence of the CT on rotor efficiency at the cost of a reduction in its capability to improve stall margin.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".