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Record W2120662324 · doi:10.2514/6.2003-1076

Prediction of 2D Airfoil Ice Accretion by Bisection Method and by Rivulets and Beads Modeling

2003· article· en· W2120662324 on OpenAlex
Guy Fortin, Adrian Ilinca, Jean-Louis Laforte, Vincenzo Brandi

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

Venue41st Aerospace Sciences Meeting and Exhibit · 2003
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsUniversité du Québec à RimouskiUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsAirfoilBisection methodComputer scienceGeologyMechanicsAlgorithmPhysics

Abstract

fetched live from OpenAlex

The paper presents recent developments in wet and dry ice accretion simulation at AMIL (Anti-Icing Materials International Laboratory) in a joint project with CIRA (Italian Aerospace Research Center). The thermodynamic model of ice accretion is similar to existing ones developed by LEWICE in USA, DRA in British, ONERA in France and Ecole Polytechnique de Montreal in Canada. However, this paper introduces an analytical model to calculate the surface roughness in the wet regime based on the residual, runback and shedding liquid water mass on an airfoil surface. Also, a new geometric model to build the ice surface, based on panel angle bisections, is presented. In the wet regime, the empirical LEWICE correlation used to determine the equivalent sand-grain roughness is replaced by two analytical formulations to calculate the local roughness height. The first one considers the maximal height that the bead can reach before moving, while the second computes the wave height on the water film. The maximum bead height before moving is determined from the equilibrium between aerodynamic, gravitational and surface tension forces. The bead behavior in dry and wet regimes was described analytically Based on the work of Al-Khalil and Hansman, which led to the determination of a water surface state (film, rivulets or beads). A mass balance is used to determine the residual and runback mass of water when the water state and the maximal bead height before moving are known. The water shedding mass is equal to the runback water mass for the lower surface and is zero for the upper surface of the airfoil respectively. A geometrical model based on panel bisection allows the ice growth in normal direction to the surface. This method simulates the ice surface accretion continually without gaps between panels. The accretion model is validated with icing profiles obtained experimentally in wind tunnel by Shin and Bond for a NACA0012 wing profile with a 0.5334 m chord, a 20 µm median volume droplet diameter, a 1 g/m³ liquid water content and a 65 m/s airspeed. These results cover both ice accretion regimes in the -4.4° to -28.3°C temperature interval. The roughness calculated analytically is in the same order of magnitude as LEWICE correlation. The use of analytical models for roughness generated the complex icing shapes (horn) as the ones observed experimentally. However, in most cases, the accreted ice was slightly bigger than the measured.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.023
GPT teacher head0.232
Teacher spread0.209 · 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