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Record W2329898411 · doi:10.2514/6.2016-1040

Semi-Analytical and Empirical Approaches to Aircraft Configuration Effects on Post-Stall Aerodynamics - Invited

2016· article· en· W2329898411 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.

Bibliographic record

VenueAIAA Atmospheric Flight Mechanics Conference · 2016
Typearticle
Languageen
FieldEngineering
TopicAerospace and Aviation Technology
Canadian institutionsUniversity of Toronto
FundersFederal Aviation Administration
KeywordsAerodynamicsStall (fluid mechanics)Aerospace engineeringAeronauticsComputer scienceEngineering

Abstract

fetched live from OpenAlex

Loss-of-control due to aerodynamic stall continues to be the largest contributor to fatal civil aviation accidents. Improved ground-based simulator training for post-stall recovery training would therefore be of great benefit. Post-stall aerodynamic models of aircraft will be required to carry out meaningful post-stall traning. This study offers a way to develop a representative aerodynamic model that will capture the effect of aircraft configuration changes relative to a baseline model. In this document, first a literature review on the effects of aircraft configuration changes on stall aerodynamics is presented. Next, an overview of the basic methodology in carrying out the configuration changes is shown, followed by details on how some of the coefficients are generated. Lastly, a full scale example of the application of the method is provided. Results from the application of the proposed method shows good match with wind tunnel data.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.898
Threshold uncertainty score0.973

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 head0.031
GPT teacher head0.216
Teacher spread0.184 · 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