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Record W2801381987 · doi:10.1139/tcsme-2013-0052

A STUDY ON THE ENGINE COMPARTMENT AIRFLOW OF A LIGHT AIRCRAFT USING COMPUTATIONAL FLUID DYNAMICS

2013· article· en· W2801381987 on OpenAlexvenueno aff
Hsu-jeng Liu, Chih-chun Su, Sheng-liang Huang

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2013
Typearticle
Languageen
FieldEngineering
TopicAerodynamics and Fluid Dynamics Research
Canadian institutionsnot available
Fundersnot available
KeywordsAirflowDuct (anatomy)Computational fluid dynamicsInletFluentCompartment (ship)MechanicsEnvironmental scienceMarine engineeringEngineeringSimulationMechanical engineeringGeologyPhysics

Abstract

fetched live from OpenAlex

This study applies FLUENT to simulate and analyze the flow characteristics in the engine compartment of a light aircraft. The air inlet, air duct, guide vane, and air outlet are designed to improve the flow conditions according to the drawbacks of the prototype model. The results show that the air duct and guide vane lead the airflow to the certain position of cylinders, and the air outlet reduces the pressure in the engine compartment. Moreover, combining these designs significantly increases the overall airflow velocity in the engine compartment.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.495
Threshold uncertainty score0.535

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 head0.017
GPT teacher head0.228
Teacher spread0.210 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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