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Record W2324377776 · doi:10.2514/6.2015-1744

Performance of a Newton-Krylov-Schur Algorithm for the Numerical Solution of the Steady Reynolds-Averaged Navier-Stokes Equations (Invited)

2015· article· en· W2324377776 on OpenAlexaff
David A. Brown, Howard Buckley, Michal Osusky, David W. Zingg

Bibliographic record

Venue53rd AIAA Aerospace Sciences Meeting · 2015
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsReynolds numberNavier–Stokes equationsComputer scienceApplied mathematicsNewton's methodMathematicsAlgorithmPhysicsMechanicsCompressibilityNonlinear system

Abstract

fetched live from OpenAlex

Computational results are presented for steady two-dimensional turbulent flows modelled through the Reynolds-averaged Navier-Stokes equations using the parallel NewtonKrylov-Schur finite-difference flow solver known as Diablo. The focus of this paper is to present performance results for the flow solver on three families of NACA 0012 grids for some specified operating conditions as part of a discussion group on turbulent flow computations. The results are presented in terms of computing time in TauBench work units as a function of the numerical error as the mesh is refined. Results for two three-dimensional cases are also presented.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.012
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.244
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations6
Published2015
Admission routes1
Has abstractyes

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Same venue53rd AIAA Aerospace Sciences MeetingSame topicComputational Fluid Dynamics and AerodynamicsFrench-language works237,207