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Record W2070803818 · doi:10.1108/03321640910918931

Stationary multi‐species models of the electric corona discharge in oxygen

2009· article· en· W2070803818 on OpenAlexaff
Jiacheng Zhang, Kazimierz Adamiak

Bibliographic record

VenueCOMPEL The International Journal for Computation and Mathematics in Electrical and Electronic Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsWestern University
Fundersnot available
KeywordsIonic bondingElectric fieldCorona dischargeDiscretizationCorona (planetary geology)IonCurrent densityCharge densityIonizationComputational physicsElectron densityChemistryAtomic physicsMechanicsElectronAnalytical Chemistry (journal)PhysicsMathematical analysisMathematicsElectrodePhysical chemistry

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to present a novel numerical algorithm, which can be used to simulate the stationary electric corona discharge in oxygen including some number of ionic species and ionic reactions. Design/methodology/approach Differential equations governing distribution of the electric field and space charge density for all ionic species have been solved using different numerical techniques: finite element method, method of characteristics (MoC) and donor‐cell method (DCM). Triangular discretization with linear interpolation of solution has been used. Findings Thickness of the ionisation layer in oxygen under normal conditions is in the order of a few hundred micrometers. Most electrons are attached to the neutral oxygen molecules forming negative ions in the drift zone. The current density on the ground plate basically follows the Warburg curve, but the DCM predicts a smooth current density distribution, while in the MoC the current density abruptly drops to zero at some radial distance. Originality/value This is the first attempt to solve this problem in the 2D point‐plane configuration. The results can lead to better understanding of all processes occurring in the corona discharge and provide information about density and distribution of different ionic species and current densities.

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: none
Teacher disagreement score0.633
Threshold uncertainty score0.362

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 head0.016
GPT teacher head0.248
Teacher spread0.231 · 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

Citations1
Published2009
Admission routes1
Has abstractyes

Explore more

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