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Record W4283390314 · doi:10.2514/6.2022-3227

Matrix-free global stability analysis framework for 2D and 3D applications

2022· article· en· W4283390314 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 AVIATION 2022 Forum · 2022
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsJacobian matrix and determinantAirfoilTransonicSolverEigenvalues and eigenvectorsComputer scienceLaminar flowApplied mathematicsAerodynamicsMathematicsMathematical optimizationAerospace engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2022-3227.vid This paper presents the implementation of stability analysis methods in the CHApel Multi-Physics Simulation (CHAMPS) software. A classic method using the extraction of the Jacobian matrix of the Unsteady Reynolds-Averaged Navier-Stokes (URANS) equations and a resolution of eigenvalue problems with the PETSC and SLEPC libraries is implemented. A development to compute the stability of spanwise invariant flow with an assumption on the periodicity of the modes in the spanwise direction is included. This paper also proposes a matrix-free implementation, which relies on a Generalized Minimized Residual solver for the linear systems of equations. In all cases, an Arnoldi iteration with the shift-and-invert spectral transformation is used to compute the eigenpairs. The methods are verified for the case of a laminar cylinder and the transonic buffet over an airfoil, and applied to a transonic buffet case on a half wing-body aircraft configuration.

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: none
Teacher disagreement score0.918
Threshold uncertainty score0.516

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)0.0000.000

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 head0.005
GPT teacher head0.239
Teacher spread0.234 · 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