MétaCan
Menu
Back to cohort
Record W3149164910 · doi:10.4236/jfcmv.2021.92002

Application of Rainbow Schlieren Deflectometry for Jets from Round Laval Nozzles Followed by Cylindrical Ducts

2021· article· en· W3149164910 on OpenAlexaboutno aff
Ryota Fukunaga, Muhammad Minarul Islam, Yusuke Awata, Shinichiro Nakao, Yoshiaki Miyazato

Bibliographic record

VenueJournal of Flow Control Measurement &amp Visualization · 2021
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Acoustics in Jet Flows
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleSchlierenJet (fluid)Duct (anatomy)Mach numberFlow visualizationMechanicsOpticsSchlieren imagingPhysicsMaterials scienceFlow (mathematics)Anatomy

Abstract

fetched live from OpenAlex

The jet from a round Laval nozzle followed by a cylindrical duct with an inner diameter of 10 mm and a length of 50 mm is investigated experimentally. The Laval nozzle has a design Mach number of 1.5. Quantitative flow visualization of the jet issued from the duct exit is performed over a range of nozzle pressure ratios from 2.0 to 4.5 using the rainbow schlieren deflectometry combined with the computed tomography to investigate the jet three-dimensional structure. The flow features of the near-field shock systems in the jets are displayed with the density contour plot at the cross-section including the jet centerline. Effects of the nozzle pressure ratio on the density profile along the jet centerline are clarified quantitatively. In addition, a comparison between the present experiment and the previous one with a conventional Laval nozzle for jet centerline density profiles is carried out to examine the effect of the cylindrical duct. Furthermore, the three-dimensional structures of overexpanded and underexpanded jets are demonstrated with the isopycnic surfaces to visualize the internal flow features.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.901
Threshold uncertainty score0.796

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0000.000

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 head0.019
GPT teacher head0.263
Teacher spread0.244 · 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 designSimulation or modeling
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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Flow Control Measurement &amp VisualizationSame topicAerodynamics and Acoustics in Jet FlowsFrench-language works237,207