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Record W2196758556

Parametric study of an aircraft wing hot air anti-/de-icing system using numerical tools

2012· article· en· W2196758556 on OpenAlexaff
Ridha Hannat, François Morency

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsAirfoilIcingComputational fluid dynamicsReynolds-averaged Navier–Stokes equationsAerodynamicsEngineeringHeat exchangerParametric statisticsHeat transferMechanical engineeringMechanicsStructural engineeringAerospace engineeringMathematicsMeteorologyPhysics
DOInot available

Abstract

fetched live from OpenAlex

To design efficient anti/-de-icing systems for wing, appropriate conjugate heat transfer (CHT) methodology is helpful. Based on a design of experiment methodology, a parametric study of the heat ratio according to three design variables of the anti-icing system is presented. The anti-icing system geometry consists of a piccolo tube with three rows of round jets inside a swept wing based on NACA23014 airfoil. To model the anti-icing system, a conjugate heat transfer procedure from commercial CFD software is used to solve a cold air external flow, a compressible internal flow and the thermal conduction in the airfoil skin. Based on results available in literature, an appropriate test case for model validation is selected. Then, a description of the RANS equation model applied to a CHT problem and a short description of the finite volume based method are presented. Numerical results are compared against numerical results for a 3D hot air anti-icing. The Box-Behnken design of experiment methodology for three variables will be used to build a second order quadratic model of the heat ratio at the inlet and at the wing leading edge inner wall.

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: Empirical
Teacher disagreement score0.148
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.038
GPT teacher head0.268
Teacher spread0.230 · 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
Published2012
Admission routes1
Has abstractyes

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