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Record W4390451705 · doi:10.1177/1475472x231225628

Supersonic jet noise and screech tone suppression using cross-wire

2023· article· en· W4390451705 on OpenAlexaboutno aff
Kaleeswaran Periyasamy, Kadiresh Parthasarathy Natarajan

Bibliographic record

VenueInternational Journal of Aeroacoustics · 2023
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleStrouhal numberSupersonic speedAcousticsJet (fluid)PhysicsSound pressureNoise (video)Mach numberShock (circulatory)Schlieren imagingJet noiseSchlierenMechanicsComputer scienceTurbulence

Abstract

fetched live from OpenAlex

This experimental investigation is aimed at assessing how the introduction of a cross-wire at the exit of a CD nozzle influences the performance of a supersonic nozzle. The study focuses on cold air jets generated by De Laval nozzles equipped with cross-wires and baseline configurations, particularly at design Mach numbers of 1.5 and 1.75. The investigation involves collecting measurements from the noise field emitted by the cross-wire nozzle with a 2% obstruction at the exit. This passive control approach effectively reduces the occurrence of screech tones in both over-expanded and under-expanded conditions in the azimuthal plane at appropriate operating pressures. Various acoustic parameters, including sound pressure levels (SPL), Strouhal numbers, and the overall sound pressure level spectra (OASPL) are recorded. Schlieren imaging captures images of shock cell patterns, illustrating the impact of shock-associated noise. In comparison to a baseline nozzle, the results demonstrate that a CD nozzle equipped with a cross-wire proves to be a proficient screech tone suppressor, leading to an average reduction of up to 5 dB in OASPL in under-expanded and over-expanded scenarios.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.017
GPT teacher head0.305
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of AeroacousticsSame topicAerodynamics and Acoustics in Jet FlowsFrench-language works237,207