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Record W2032296167 · doi:10.4271/2011-38-0102

FENSAP-ICE: 3D Simulation, and Validation, of De-icing with Inter-cycle Ice Accretion

2011· article· en· W2032296167 on OpenAlexaff
Thomas Reid, Guido S. Baruzzi, Isik Ozcer, Wagdi G. Habashi

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2011
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsIcingAccretion (finance)Environmental scienceGeologyMeteorologyIce formationClimatologyAtmospheric sciencesPhysicsAstrophysics

Abstract

fetched live from OpenAlex

<div class="section abstract"><div class="htmlview paragraph">The assessment of an unsteady approach for the simulation of in-flight electro-thermal de-icing using a Conjugate Heat Transfer (CHT) technique is presented for a NACA0012 wing and a swept wing. This approach is implemented in the FENSAP-ICE in-flight icing system, and provides simulation capabilities for the heat transfer and ice accretion phenomena occurring during in-flight de-icing with power cycling through several heater pads. At each time step, a thermodynamic balance is established between the water film, the ice layer and the solid domains. The ice shape is then modified according to ice accretion and melting rates. Numerical results show the complex interactions between the water film, the ice layer and the heating system. The NACA0012 validation test case compares well against one of the very few experimental de-icing test cases available in the open literature. The other simulation displays the importance of 3D effects in analyzing the de-icing of a tapered, swept and twisted wing, while providing significant data for the design of the system.</div></div>

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.015
GPT teacher head0.241
Teacher spread0.225 · 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.

Study designObservational
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

Citations9
Published2011
Admission routes1
Has abstractyes

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