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Record W2392136864

Distributed parallel algorithms for hypersonic thermo-chemical non-equilibrium flows

2008· article· en· W2392136864 on OpenAlexaboutno aff
WU Yi-zhao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsnot available
Fundersnot available
KeywordsHypersonic speedDomain decomposition methodsDiscretizationControl volumeFinite volume methodComputer scienceParameterized complexityNavier–Stokes equationsAlgorithmFinite element methodApplied mathematicsMechanicsMathematicsPhysicsMathematical analysisThermodynamics
DOInot available

Abstract

fetched live from OpenAlex

A distributed parallel algorithm for hypersonic thermochemical non-equilibrium flow was presented. The control equations were Navier-Stokes equations with multi-components. The chemical kinetic model was, which was popularly used with the consideration of the weak ionization effects, that of seven species and six chemical reactions with a two-temperature model. The spatial discretization for the control equations was Jameson's finite volume scheme, with an explicit 5-stage time step method. The decomposition of the global computational domain was realized by means of a software named METIS, in view of cell number of sub-domains load-balanced. Test cases, obtained on a PCs-Cluster system with PVM protocol, were shown for a hypersonic blunt cone body. Satisfactory numerical results were obtained and compared with those of sequential results and references.

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: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.043
GPT teacher head0.283
Teacher spread0.240 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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