CFD Analysis of a 15 Stage Axial Compressor: Part II — Results
Bibliographic record
Abstract
The flow field of a 15 stage axial compressor is analyzed using a 3-D Navier-Stokes CFD tool. The compressor under investigation is a prototype engine, first compressor version before optimization of the Siemens V84.3A family. The paper describes steady state and transient flow simulations of the entire 15 stages compressor in one computation (not piece by piece). The simulation includes tip gaps, mass bleeds, hub leakage flows, and ranges from single passage to full 360 degrees analysis. The work is divided into two companion papers. The second paper, “CFD Analysis of a 15 Stage Axial Compressor Part II: Results” describes the application of the methods in Part I to the entire 15 stage compressor (Belamri et al, 2005). The flow in the compressor is modeled first with one blade passage per component (periodicity assumed, an interface pitch change model employed). Steady state and transient models are compared. In a second series of computations, all blade passages in 360 degrees are modeled, (no periodicity or pitch change assumptions required), for portions of the compressor. The various simulation approaches are compared to each other, and to experimental data. Good agreement between predictions and experimental results, both in the details of the flow field and the integral prediction of operating range of the compressor, were found.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".