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Record W2750556615 · doi:10.1088/1361-6587/aa868d

Return current instability driven by a temperature gradient in ICF plasmas

2017· article· en· W2750556615 on OpenAlexaff
W. Rozmus, A. V. Brantov, M. Sherlock, V. Yu. Bychenkov

Bibliographic record

VenuePlasma Physics and Controlled Fusion · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Plasma Interactions and Diagnostics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsInstabilityPlasmaIonPhysicsConvectionElectron temperatureElectronAtomic physicsTurbulenceSaturation currentHeat fluxInertial confinement fusionComputational physicsMechanicsHeat transferNuclear physics

Abstract

fetched live from OpenAlex

Abstract Hot plasmas with strong temperature gradients in inertial confinement fusion experiments are examined for ion acoustic instabilities produced by electron heat flow. The return current instability (RCI) due to a neutralizing current of cold electrons arising in response to a large electron heat flux has been considered. First, the linear threshold and growth rates are derived in the non-local regime of thermal transport. They are compared with the results of Vlasov–Fokker–Planck (VFP) simulations in one spatial dimension. Very good agreement has been found between kinetic VFP simulations and the linear theory of the RCI. A quasi-stationary state of ion acoustic turbulence (IAT) produced by the RCI is achieved in the VFP simulations. Saturation of the RCI involves heating of ions in the tail of the ion distribution function and convection of the enhanced ion acoustic fluctuations from the unstable region of the plasma. Further evolution of the IAT and its effects on absorption and transport are also discussed.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.245
Teacher spread0.236 · 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 designObservational
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

Citations17
Published2017
Admission routes1
Has abstractyes

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