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Record W2325479674 · doi:10.2514/6.2015-2284

Higher-order Unstructured Finite Volume Methods for Turbulent Aerodynamic Flows

2015· article· en· W2325479674 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

Venue22nd AIAA Computational Fluid Dynamics Conference · 2015
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAerodynamicsFinite volume methodTurbulenceMechanicsComputer scienceVolume (thermodynamics)Aerospace engineeringPhysicsEngineeringThermodynamics

Abstract

fetched live from OpenAlex

In this paper, we describe the steps for constructing a higher-order finite volume unstructured solver for turbulent aerodynamic flows. These include the strategies for curving the interior faces of a mesh, solution reconstruction on highly anisotropic meshes with curvature, robust implementation and coupling of a RANS turbulence model and efficient solution method. The solutions are verified by one of the verification test cases of the NASA Langley turbulence model resource. Also, the solutions and convergence behaviors are presented for fully turbulent flow over a flat plate and subsonic flow over the NACA 0012 airfoil. Our results show fast and efficient convergence for second-, thirdand fourthorder solutions for the flat plate test case and secondand third-order solutions for the airfoil. In addition, the accuracy of the solution is reasonable on meshes with sufficient degrees of freedom in which the turbulence features are captured appropriately.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.571
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.279
Teacher spread0.257 · 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