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Record W2015934325 · doi:10.2514/1.37369

Multi-Property Measurements at High Sampling Rates Using Rayleigh Scattering

2009· article· en· W2015934325 on OpenAlexfundno aff
Amy F. Mielke, Kristie Elam, Chih‐Jen Sung

Bibliographic record

VenueAIAA Journal · 2009
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsnot available
FundersGlenn Research CenterUniversity of Waterloo
KeywordsRayleigh scatteringOpticsNozzleJet (fluid)Materials scienceCombustorInterferometryRayleigh lengthPhysicsPhotomultiplierScatteringParticle image velocimetryLaserTurbulenceMechanicsCombustionDetector

Abstract

fetched live from OpenAlex

A molecular Rayleigh scattering technique is developed to measure gas velocity, temperature, and density in unseeded gas flows at sampling rates up to 32 kHz. A high-power continuous-wave laser beam is focused at a point in an air flowfield, and Rayleigh scattered light is collected and fiber-optically transmitted to a Fabry-Perot interferometer for spectral analysis. Photomultiplier tubes operated in the photon-counting mode allow highfrequency sampling of the total signal level and the circular interference pattern to provide density, temperature, and velocity measurements. Mean and root-mean-square fluctuation measurements in both an electrically heated jet facility with a 10-mm-diam nozzle and in a hydrogen-combustor-heated-jet facility with a 50.8-mm-diam nozzle at NASA John H. Glenn Research Center at Lewis Field are presented. Measurements are compared with hot-wire anemometry, cold-wire thermometry, and temporally resolved particle image velocimetry to validate the Rayleigh technique.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.087
GPT teacher head0.283
Teacher spread0.196 · 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

Citations54
Published2009
Admission routes1
Has abstractyes

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