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Record W1997293393 · doi:10.1115/ht2005-72433

Numerical Calculations of Heat Conduction Between Soot Aggregates and the Surrounding Gas in the Free-Molecular Regime Using the DSMC Method

2005· article· en· W1997293393 on OpenAlexaff
Fengshan Liu, Min Yang, David R. Snelling, Gregory J. Smallwood

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsThermal conductionSootIncandescenceHeat transferMonte Carlo methodCluster (spacecraft)Materials scienceDirect simulation Monte CarloFractal dimensionParticle (ecology)MoleculeMolecular physicsThermodynamicsMechanicsPhysicsFractalChemistryDynamic Monte Carlo methodCombustionPhysical chemistry

Abstract

fetched live from OpenAlex

Numerical calculations were conducted to calculate the heat conduction rate between soot (carbon) aggregates of different sizes and the surrounding gas in the free-molecular regime using the direct simulation Monte Carlo method. This method is based on simulation of the trajectories of individual molecules and calculation of the heat transfer at each of the molecule/molecule collisions and the molecule/particle collisions. Soot aggregates of known fractal dimension and pre-factor are first numerically generated using a cluster-cluster aggregation algorithm. Effect of incomplete thermal accommodation was accounted for by employing the Maxwell gas-surface interaction model. Gas collisions were treated using the simple hard sphere model. Numerical results were obtained for aggregate sizes between 10 and 228 primary particles and the thermal accommodation coefficient between 0.1 and 1. A simple scaling for the heat transfer equivalent sphere diameter was also presented for incorporation into a laser-induced incandescence model.

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)0.000
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.022
GPT teacher head0.287
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

Citations2
Published2005
Admission routes1
Has abstractyes

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