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Record W2997691128 · doi:10.2514/6.2020-2032

Adaptive Construction of Model-Consistent Wall Functions for Two-Equation Turbulence Models with Applications

2020· article· en· W2997691128 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 Scitech 2020 Forum · 2020
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsCouette flowTurbulenceFlow (mathematics)Boundary (topology)Plane (geometry)K-epsilon turbulence modelApplied mathematicsMathematicsAlgebraic numberBoundary value problemMathematical optimizationComputer scienceMathematical analysisMechanicsPhysicsGeometry

Abstract

fetched live from OpenAlex

This paper presents a cost-effective adaptive remeshing algorithm for constructing model- consistent wall functions for low-Reynods number models of turbulence. Traditional wall functions are obtained by developing algebraic expressions for the dependent variables (u, k, ε) in 1D plane turbulent Couette flow. However, in general, closed form solutions to the Couette flow coupled system of equations can only be obtained by invoking additional approximations whose impact on solution accuracy is difficult to quantify. Numerical solutions of the 1D Couette flow avoids this problem. The resulting tabulated wall functions are fully compatible and consistent with the turbulence model. We have opted for a finite element method based on adaptive remeshing because it yields highly accurate boundary conditions with a small number of optimally placed nodes.

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: Methods · Consensus signal: none
Teacher disagreement score0.859
Threshold uncertainty score0.561

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 head0.019
GPT teacher head0.208
Teacher spread0.189 · 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