Sand erosion modeling in generic compressor rig testing
Bibliographic record
Abstract
Abstract Based on erosion coupon tests, a sand erosion model for 17-4PH steel was developed. The developed erosion model was validated against the results of compressor erosion tests from a generic rig and from other researchers. A high-fidelity computational fluid dynamics (CFD) model of the test rig was built, a user-defined function was developed to implement the erosion model into the ANSYS CFD software, and the turbulent, two-phase flow-field in multiple reference frames was solved. The simulation results are consistent with the test results from the compressor rig and with experimental findings from other researchers. Specifically, the sand erosion blunts the leading edge, sharpens the trailing edge and increases pressure-surface roughness. The comparisons between the experimental observations and numerical results as well as a quantitative comparison with three other sand erosion models indicate that the developed sand erosion model is adequate for erosion prediction of engine components made of 17-4PH steel.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".