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Record W1986434003 · doi:10.1029/2003ja010035

Finite element modeling of nonlinear dispersive field line resonances: Trapped shear Alfvén waves inside field‐aligned density structures

2003· article· en· W1986434003 on OpenAlexaff
J. Y. Lu, R. Rankin, R. Marchand, V. T. Tikhonchuk, J. A. Wanliss

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhysicsMagnetohydrodynamicsGyroradiusAlfvén waveField lineComputational physicsNonlinear systemClassical mechanicsMagnetic fieldQuantum mechanics

Abstract

fetched live from OpenAlex

Using a new two‐dimensional nonlinear finite element model, we investigate the interaction of dispersive shear Alfvén wave (SAW) field line resonances (FLRs) and ion acoustic waves in Earth's magnetosphere. We solve the full set of nonlinear reduced MHD equations self‐consistently in arbitrary geometries. Initially, a Cartesian box model is used to demonstrate the reliability of our numerical solution in determining the linear and nonlinear evolution of FLRs. Then the full reduced MHD equations with the effects of electron inertia, ion Larmor radius correction, and electron thermal pressure are solved in dipolar and stretched magnetic topologies. We show that time‐dependent dispersion and density steepening lead to localization of a highly structured FLR within an ionospheric (equatorial) density cavity (bump). When nonlinear effects are accounted for, we find that FLRs preferentially form in regions of low wave dispersion. Field line stretching and ponderomotive density redistribution lead to a significant reduction in FLR eigenfrequencies, bringing them into the range of observations. Nonlinear effects also cause a rapid acceleration of the timescale over which small perpendicular spatial scales appear. In our model, it is shown that density perturbations can be comparable to the equilibrium background density.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.319
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.301
Teacher spread0.280 · 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.

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

Citations29
Published2003
Admission routes1
Has abstractyes

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