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Record W2004022227 · doi:10.2514/2.2613

Heat and Mass Transfer in the Case of Anti-Icing System Simulation

2000· article· en· W2004022227 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Aircraft · 2000
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsBombardier (Canada)Polytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIcingBoundary layerIcing conditionsMass transferHeat transferFinite difference methodMechanicsFinite differenceBoundary value problemMaterials scienceAerospace engineeringThermodynamicsPhysicsMeteorologyMathematicsEngineeringMathematical analysis

Abstract

fetched live from OpenAlex

Aircraft manufacturers need anti-icing system simulations to help in the design of ice protection systems. Heat and mass transfer predictions obtained with two different methods to solve the boundary layer in the case of an anti-icing simulation are compared. The integral method and the finite difference method are used to solve the boundary-layer equations, including the mass diffusion equation. The boundary-layer solvers are implemented into the code CANICE, which models the ice accretion process. Comparison of heat and mass transfer distributions and surface temperature distributions are made. Surface temperatures predicted with the finite difference method are closer to experimental results than surface temperatures predicted with the integral method

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.

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 score0.048
Threshold uncertainty score0.168

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 head0.009
GPT teacher head0.223
Teacher spread0.213 · 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