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Record W2009335538 · doi:10.2514/1.5594

Three-Dimensional Integrated Thermodynamic Simulation for Wing Anti-Icing System

2004· article· en· W2009335538 on OpenAlexaff
Hugh H. T. Liu, Jun Hua

Bibliographic record

VenueJournal of Aircraft · 2004
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsIcingWingAerospace engineeringComputer scienceEnvironmental scienceEngineeringPhysicsMeteorology

Abstract

fetched live from OpenAlex

Thermal flow in an aircraft wing leading-edge anti-icing system is a complicated physical phenomenon and remains a challenging research topic of modeling and analysis. We present a complete three-dimensional simulation of a wing segment including the piccolo-type thermal anti-icing bays inside the leading edge is presented. The Navier-Stokes analysis has been conducted for the integrated internal/external thermal flows with heat conductivity through the solid skin. The fully structured zones and boundary-layer meshing have reduced the total cell number and enhanced the near-wall impingement and the heat transfer analysis. Simulation results visually reveal the hot/cold flow interactions and heat conductivity through the fluid and solid zones. The calculated leading-edge surface temperature is compared with flight-test data of a similar configuration. The computational fluid dynamics model and its analysis under different flight conditions and configuration modifications provide a valuable assessment for wing anti-icing system research and development

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.229
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations31
Published2004
Admission routes1
Has abstractyes

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