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Record W4309309295 · doi:10.3390/fluids7110353

Aerodynamic Shape Optimization of a Symmetric Airfoil from Subsonic to Hypersonic Flight Regimes

2022· article· en· W4309309295 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

VenueFluids · 2022
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsTransonicAirfoilAerospace engineeringHypersonic speedAerodynamicsSupersonic speedLift coefficientAngle of attackPhysicsComputational fluid dynamicsDragComputer scienceMechanicsEngineeringTurbulence

Abstract

fetched live from OpenAlex

Hypersonic flight has been the subject of numerous research studies during the last eight decades. This work aims to optimize the aerodynamic performance of a two-dimensional baseline airfoil (NACA0012) at distinct flight regimes from subsonic to hypersonic speeds. A mission profile has been defined, where four points representing the subsonic, transonic, supersonic, and hypersonic flow conditions have been selected. A framework has been implemented based on high-fidelity RANS computational fluid dynamics simulations. Gradient-based optimizations have been conducted with the objective of minimizing the drag. The optimization results show an overall improvement in aerodynamic performance, including a decrease in the drag coefficient of up to 79.2% when compared to the baseline airfoil. In the end, a morphing strategy has been laid out based on the optimal shapes produced by the optimization.

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 score0.034
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.005
GPT teacher head0.187
Teacher spread0.182 · 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