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Record W2044030974 · doi:10.2202/1934-2659.1197

Finite Element Modeling of Viscous Mixing: A Review

2008· review· en· W2044030974 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

VenueChemical Product and Process Modeling · 2008
Typereview
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsFinite element methodMixing (physics)SolverNewtonian fluidComputational fluid dynamicsNon-Newtonian fluidFlow (mathematics)Computer scienceMechanical engineeringField (mathematics)Viscous liquidMechanicsComputational scienceMathematical optimizationEngineeringMathematicsPhysicsStructural engineering

Abstract

fetched live from OpenAlex

The objective of this paper is to review the application of the finite element-based CFD methods in mixing engineering. It provides a good opportunity to summarize the thirty five years of finite element achievements in the field of fluid flow started in the 70's, with the development of the first 2D Navier-Stokes solver for Newtonian and non-Newtonian viscous fluids, and extended in the 80's, with new solution algorithms to tackle 3D problems. For mixing simulations, a corner stone was the introduction of the "virtual finite element method" in the mid 90's for the simulation of flow systems with internal moving parts. In the on-going quest to improve the characterization of mixing systems for industrial needs, further developments are required, and progress could come from the next generation of computationally efficient multi-physics solvers.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.309
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.035
GPT teacher head0.290
Teacher spread0.255 · 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