Influence of Changing Casing Groove Parameters on the Performance of Centrifugal Compressors Near Stall Condition
Bibliographic record
Abstract
The casing treatment is an effective method for increasing the stall margin of compressors and enhancing the flow distribution at the blades tip. The present numerical study focuses on making an optimization of the casing groove parameters which can enhance the centrifugal compressor performance during stall. The casing grooves parameters considered are the groove cross section aspect ratio (the groove height to width ratio), groove location, and the number of grooves. Five groove aspect ratios were considered ranging from 0.2 to 1.8. Three groove locations were studied: at full blades leading edge, at splitter blades leading edge, and after the splitter blades leading edge by a distance equals to the distance between the first and second groove locations. Comparisons were made among different cases with number of grooves starting from one up to seven grooves located at the most effective locations and have the optimum cross section dimensions as deduced from the results of the groove aspect ratio and groove location optimization. Results showed that by using groove aspect ratio less than one, the reinjected groove flow is relatively weak but when the aspect ratio is equal to one, there is enough space inside the groove for the flow to circulate and generate the reinjected groove flow with higher velocities. When the groove aspect ratio was increased to be more than one, the reinjected flow velocity was increased slightly and its effective area was increased in the circumferential direction. Results also indicated that the best location for the groove is at the full blades leading edge because the stall area can be minimized and controlled in a better way comparing with the other groove locations. Results showed that by increasing the number of grooves, the surge margin (SM) increases and the isentropic efficiency decreases, but the stall area at the shroud surface decreases in size and its location is shifted toward the blades trailing edge.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".