A Theoretical and Experimental Investigation on Ejector Acoustics and Ejector Silencer Design
Bibliographic record
Abstract
Ejectors are common devices used across many industries, however, they are often plagued by the presence of low frequency pressure pulsations causing both broadband and tonal noise.This thesis presents a theoretical and experimental investigation into the acoustics of an ejector-silencer combination with the emphasis placed on silencer design.More specifically, the noise generated by the jet, the diffuser and natural modes is explained and estimated.The noise generation mechanisms of impingement tones and edgetones are presented but accurate predictions are found to be hard to make.An outline of the experimental facility is followed by the mechanical, acoustical and aerodynamic design details of the approximately 70:1 ejector scale model.A detailed analysis on the primary nozzle control and calibration is presented before beginning an aerodynamic and acoustic characterization of both the ejector and the wind tunnel facility.From experimentation, it is found that the placement of a perforated cone in front of the solid cone is beneficial in reducing the noise generated without overly affecting the entrainment ratio.Other configurations tested tend not to be as acoustically effective or to decrease the entrainment ratio below an acceptable level.Experiments prove that the low frequency noise generated by the ejector is mainly caused by natural mode excitation.ivFirst and foremost I would like to thank my family and loved ones who were understanding of the long hours worked on this project and who were always by my side sympathizing with the hardships I faced.I am grateful to have a father who always taught me to dream big and act bigger, which has helped me get to where I am today.I would like to thank my research supervisor Professor Joana Rocha for presenting me with the opportunity to work on this project as well as for continuous consultation and support over the past two years.Without you this project would have been impossible.The kind and generous contributions of the team at MDS Aero helped move this project along and I am thankful for your support as well as for always making me feel like part of the team.To my past and present colleagues working under under the supervision of Professor Rocha, your patience and friendship proved invaluable.The input of John O'keefe for aerodynamics portion and Frank Giardino for essentially everything was of great value and I thank you both for that.I would like to express my utmost appreciation to
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".