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Record W2907070140 · doi:10.22215/etd/2018-13197

A Theoretical and Experimental Investigation on Ejector Acoustics and Ejector Silencer Design

2018· dissertation· en· W2907070140 on OpenAlexaff
Gerard Desmarais

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsCarleton University
Fundersnot available
KeywordsSilencerInjectorAcousticsAerodynamicsNozzleWind tunnelNoise (video)EngineeringDiffuser (optics)BroadbandSound pressureJet noiseSupersonic speedMechanical engineeringAerospace engineeringPhysicsComputer scienceInletOpticsTelecommunications

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.136
Threshold uncertainty score0.733

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.244
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2018
Admission routes1
Has abstractyes

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