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Record W4386072910 · doi:10.11159/htff23.180

Jet Direction Control Using Active Switching Nozzle

2023· article· en· W4386072910 on OpenAlexvenueno aff
Taisei Suzuoka, Koichi Nishibe, Kotaro SATO, Donghyuk KANG

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleJet (fluid)PhysicsControl theory (sociology)MechanicsControl (management)Aerospace engineeringMaterials scienceComputer scienceEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Many studies have been conducted on fluidic thrust vectoring, which uses a secondary flow to deflect a primary jet, instead of mechanical thrust vectoring including a variable exhaust nozzle, to improve maneuverability and maintainability by simplifying, downsizing, and reducing the weight of the entire thrust vectoring system In recent years, research has also begun on the utilization of synthetic or hybrid-synthetic jets as secondary flows for further increasing the deflection angle In addition, Mair et al. [3] proposed a novel fluidic valve with active switching using acoustic signals and a splitter; they determined the flow switching mechanism from experimental and numerical results. These technologies find applicability in not only aircraft development but also in a wide range of other fields, including heating, ventilation, and airconditioning systems. However, in the conventional methods, there is a dead zone where the deflection angle cannot be adjusted, and a technique to adjust the deflection angle precisely without a splitter, which is an issue in practical use, has not been established.

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 score0.057
Threshold uncertainty score0.702

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)0.0000.000

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 head0.006
GPT teacher head0.201
Teacher spread0.195 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

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