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Record W2314507360 · doi:10.1115/fedsm-icnmm2010-31022

Gas Properties Effects in Microchannel Studies Using Direct Simulation Monte Carlo

2010· article· en· W2314507360 on OpenAlexaff
Masoud Darbandi, A. Karchani, Hassan Akhlaghi, G. E. Schneider

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsKnudsen numberHeat transferPolyatomic ionMach numberMicrochannelTemperature jumpMechanicsMonte Carlo methodDirect simulation Monte CarloHeliumMaterials scienceMonatomic ionThermodynamicsAtomic physicsChemistryIonPhysicsDynamic Monte Carlo method

Abstract

fetched live from OpenAlex

This paper concern is to study the gas properties effect in flow and heat transfer behaviors through microchannels using the direct simulation Monte Carlo method. The flow is rarefied and supersonic. The channels are investigated at two different inlet boundary conditions. The collision process is modeled using the NTC (no-time-counter) scheme. The VHS model is chosen to simulate collision between particle pairs. The study is provided for many different gases including nitrogen, helium, and oxygen. The Knudsen number is chosen in a manner to provide slip flow through the channel. The results show that the heat transfer from the wall is lower for heavier gases. A comparative study among the monatomic, diatomic, polyatomic gases shows that the heat transfer rate is lower for the polyatomic gases. The result shows that, the heat transfer from the wall is lower for the heavier gases than that for the lighter gas. For a fixed Mach number, the heat transfer from the wall decreases as the molecular diameter increases.

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)0.002
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: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.064
GPT teacher head0.329
Teacher spread0.265 · 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
Published2010
Admission routes1
Has abstractyes

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