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Record W2058469525 · doi:10.6112/kscfe.2014.19.2.049

DEVELOPMENT OF A 2-D GAS-KINETIC BGK SOLVER FOR CONTINUUM AND TRANSITIONAL FLOWS ON UNSTRUCTURED MESHES

2014· article· en· W2058469525 on OpenAlexaff
Taeyoung Yang, Oh Joon Kwon

Bibliographic record

VenueJournal of computational fluids engineering · 2014
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsSolverKinetic energyPolygon meshClassification of discontinuitiesKinetic schemeHypersonic speedPhysicsMechanicsReal gasBoltzmann equationCompressibilityStatistical physicsClassical mechanicsMathematicsThermodynamicsGeometryMathematical analysisMathematical optimization

Abstract

fetched live from OpenAlex

In the present study, 2-D gas-kinetic flow solver on unstructured meshes was developed for flows from continuum to transitional regimes. The gas-kinetic BGK scheme is based on numerical solutions of the BGK simplification of the Boltzmann transport equation. In the initial reconstruction, the unstructured version of the linear interpolation is applied to compute left and right states along a cell interface. In the gas evolution step, the numerical fluxes are computed from the evaluation of the time-dependent gas distribution function around a cell interface. Two-dimensional compressible flow calculations were performed to verify the accuracy and robustness of the current gas-kinetic approach. Gas-kinetic BGK scheme was successfully applied to two-dimensional steady and unsteady flow simulations with strong contact discontinuities. Exemplary hypersonic viscous simulations have been conducted to analyze the performances of the gas-kinetic scheme. The computed results show fair agreement with other standard particle-based approaches for both continuum part and transitional part.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.234
Teacher spread0.224 · 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
GenreMethods

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

Citations1
Published2014
Admission routes1
Has abstractyes

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