Acoustic Design and Validation of Radial Inflow Turbine
Bibliographic record
Abstract
A radial inflow turbine installed in a large extraction facility in Canada has shown to be a significant contributor to the noise generated in that facility. These high sound pressure levels have led to the expenditure of millions of dollars in sound abatement measures over the last 20 years, and pose a health danger to employees. Based on shop testing and field data, it was believed that a new rotor design could dramatically reduce the noise generated. It was further believed that Computational Fluid Dynamics with Aeroacoustic analyses was capable of predicting this improvement. Such a process can allow parts to be designed and installed quickly, when time and budget does not allow for detailed factory testing. This paper describes this turbine redesign procedure and the details of the analyses performed throughout the process. This new rotor has now been installed on-site, and measurements have been made before and after the replacement. This offers a unique opportunity to validate the numerical work performed through this redesign, which is also presented in the paper.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".