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Record W2086994280 · doi:10.1299/jsmeb.48.293

Correlation of Burning Rate of the Interacting Liquid Droplets with Internal Circulation

2005· article· en· W2086994280 on OpenAlexfundno aff
Ho‐Young Kim, Chong Pyo Cho, Jin Taek Chung

Bibliographic record

VenueJSME International Journal Series B · 2005
Typearticle
Languageen
FieldEngineering
TopicCombustion and flame dynamics
Canadian institutionsnot available
FundersCanada Excellence Research Chairs, Government of Canada
KeywordsMechanicsReynolds numberCombustionConvectionTransient (computer programming)Flow (mathematics)Volumetric flow rateCirculation (fluid dynamics)Materials scienceChemistryPhysicsTurbulence

Abstract

fetched live from OpenAlex

The combustion characteristics of interacting liquid droplets with internal circulation in a convective flow are numerically investigated in order to determine the burning rate correlation of interacting droplets. For the transient analysis of 2-dimensionally arranged interacting droplets, Reynolds number based on the relative velocity between the liquid droplet and surrounding gas, vertical and horizontal distances between neighboring droplets are chosen as major parameters. The time variations of flame structure and combustion characteristics as well as the burning rate during the droplet lifetime are obtained. The results reveal that the transient flame configuration and retardation of droplet internal motion for the arbitrary droplets arrangement substantially influence on the burning rate of interacting droplets. The burning rate of interacting droplets exhibits a strong dependence on Reynolds number, the horizontal and vertical distances between droplets. The correction factor of burning rate for interacting droplets based on the single droplet combustion is also suggested in terms of major parameters.

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 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 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 score0.066
Threshold uncertainty score0.273

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0000.000
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 head0.004
GPT teacher head0.206
Teacher spread0.202 · 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 teacher head, 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

Citations4
Published2005
Admission routes1
Has abstractyes

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