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Record W2075502687 · doi:10.1063/1.4813253

Numerical magnetohydrodynamic simulations of expanding flux ropes: Influence of boundary driving

2013· article· en· W2075502687 on OpenAlexaff
T. Tacke, Jürgen Dreher, R. D. Sydora

Bibliographic record

VenuePhysics of Plasmas · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicSolar and Space Plasma Dynamics
Canadian institutionsUniversity of Alberta
FundersDeutsche Forschungsgemeinschaft
KeywordsPhysicsMagnetohydrodynamicsMagnetohydrodynamic drivePlasmaArchMechanicsElectric fieldPerturbation (astronomy)Boundary value problemBoundary (topology)Magnetic fieldElectric currentClassical mechanicsMathematical analysis

Abstract

fetched live from OpenAlex

The expansion dynamics of a magnetized, current-carrying plasma arch is studied by means of time-dependent ideal MHD simulations. Initial conditions model the setup used in recent laboratory experiments that in turn simulate coronal loops [J. Tenfelde et al., Phys. Plasmas 19, 072513 (2012); E. V. Stenson and P. M. Bellan, Plasma Phys. Controlled Fusion 54, 124017 (2012)]. Boundary conditions of the electric field at the “lower” boundary, intersected by the arch, are chosen such that poloidal magnetic flux is injected into the domain, either localized at the arch footpoints themselves or halfway between them. These conditions are motivated by the tangential electric field expected to exist in the laboratory experiments due to the external circuit that drives the plasma current. The boundary driving is found to systematically enhance the expansion velocity of the plasma arch. While perturbations at the arch footpoints also deform its legs and create characteristic elongated segments, a perturbation between the footpoints tends to push the entire structure upwards, retaining an ellipsoidal shape.

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 score0.340
Threshold uncertainty score0.675

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 head0.006
GPT teacher head0.233
Teacher spread0.228 · 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

Citations2
Published2013
Admission routes1
Has abstractyes

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