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Record W2516396533 · doi:10.1109/plasma.2016.7534020

Nonlinear simulations and anomalous transport in hall thruster plasma

2016· article· en· W2516396533 on OpenAlexaff
Oleksandr Koshkarov, Winston Frias Pombo, A. I. Smolyakov, Yevgeny Raitses, Igor Kaganovich, M. Umansky

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPlasma Diagnostics and Applications
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPlasmaPhysicsNonlinear systemElectronInertiaAdvectionElectron densityInstabilityComputational physicsElectron temperatureMechanicsAtomic physicsClassical mechanicsNuclear physics

Abstract

fetched live from OpenAlex

Summary form only given. The plasma inside a Hall thruster is a complex environment full of instabilities and interesting physical phenomena such as anomalous transport. To better understand this complex plasma dynamics, a nonlinear fluid model has been developed. The model contains the effect of electron inertia, electron collisions, electron temperature and density gradients as well as nonlinearities in the ion velocity and the electron advection term that arises from the ExB drift. The model is simulated using BOUT++, a framework for plasma simulations developed at the Lawrence Livermore National Laboratory. The linear limits of the model correspond to the lower hybrid mode rendered unstable by collisions and to the density gradient drift instabilities. Two cases are simulated using BOUT++, one without density gradients and one with density gradients. Both these cases exhibit energy saturation as well as an axial current much larger than the classical collisional value. The simulations with density gradients seem to show a larger axial electron current as well as exhibiting azimuthally propagating structures similar to the spokes observed experimentally.

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: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.202
Teacher spread0.194 · 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
Published2016
Admission routes1
Has abstractyes

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