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Record W2231565641 · doi:10.4271/2015-01-2125

Technique for Ice Crystal Particle Size Measurements and Results for the National Research Council of Canada Altitude Ice Crystal Test System

2015· article· en· W2231565641 on OpenAlexaffabout
Dan Fuleki, Jennifer L. Chalmers, Brian Galeote

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2015
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsIce crystalsAltitude (triangle)Crystal (programming language)Particle (ecology)MeteorologyTest (biology)Materials scienceEnvironmental scienceAtmospheric sciencesPhysicsGeologyComputer scienceGeometryMathematicsOceanography

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">This paper describes the equipment, analysis methods and results obtained for particle size measurements based on a particle imaging velocimetry (PIV) system in which a short duration laser pulse is used to backlight airborne particles. This produces high quality and high resolution images of fast moving airborne particles in a non-intrusive manner. This imaging technique is also used to examine particle morphology and 2D particle trajectory and velocity. The image analysis methods are outlined and validation test results discussed which show the measurement of reference glass beads between 20 and 400 microns were generally to within their stated size. As well, validation testing using known icing wind tunnel droplet distributions were compared with Spraytek 2000 Malvern droplet size measurements and showed agreement of the MVD's to be within ±5% for distributions having nominally 20, 40 and 80 micron MVD's. Implementing this non-intrusive shadowgraphy technique at the NRC ice crystal test system installed at its research altitude test facility (RATFac) showed ice particle size distributions could be generated from approximately 60 to700 micron median mass diameters (MMD's) with the ability to create larger particles well above 1 mm in diameter.</div></div>

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)0.008
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.862
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.097
GPT teacher head0.292
Teacher spread0.194 · 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.

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

Citations15
Published2015
Admission routes2
Has abstractyes

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