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Record W2270852322 · doi:10.1017/s0001924000092319

A study of aerodynamic performance degradation on aerofoils and aircraft wings due to accreted ice

2002· article· en· W2270852322 on OpenAlexaff
M. Khalid, F. Zhang, S. Chen

Bibliographic record

VenueThe Aeronautical Journal · 2002
Typearticle
Languageen
FieldEngineering
TopicIcing and De-icing Technologies
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsStall (fluid mechanics)Trailing edgeLeading edgeAirfoilAerodynamicsWingMechanicsVortexSwept wingBoundary layerAngle of attackAerospace engineeringLift (data mining)GeologyComputational fluid dynamicsMaterials sciencePhysicsEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract The aerodynamic performance of two dimensional (2D) aerofoils and finite aircraft wings is investigated when the leading edge is modified with a standard ice shape. Three ice-shapes, G1, G3 and R7 are selected for this investigation. For the aerofoils it was observed that the presence of strong vortex flows near the leading edge fundamentally changes the flow in that region forcing earlier transition and premature separation. Normal suction peaks designed to provide high aerodynamic lift and prolonged attached flow are replaced with a system of vortices which produce unwanted pressure spikes which influence the development of the boundary layer leading to earlier stall. The present study also includes the three dimensional (3D) effects due to iced leading edges on aircraft surfaces. As different from such studies elsewhere, which only considered the simple sweep back effects on constant cross section wings, the present work includes more realistic wings equipped with twist, taper and non-equal sweep back at leading and trailing edge of the wing. In absence of any experimental data on such real life type configurations, the computational fluid dynamic (CFD) results were first validated against measurements on non-swept wings. It was found that ice formations cause noticeable changes of the flow in the leading edge regions of the wing and promote strong 3D effects, which pervade across the entire span wise direction of the model.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.846
Threshold uncertainty score0.349

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 head0.021
GPT teacher head0.224
Teacher spread0.203 · 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 designOther design
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

Citations2
Published2002
Admission routes1
Has abstractyes

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