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Record W2036359291 · doi:10.1063/1.4804336

Modeling of current characteristics of segmented Langmuir probe on DEMETER

2013· article· en· W2036359291 on OpenAlexafffund
Nadia Imtiaz, R. Marchand, Jean‐Pierre Lebreton

Bibliographic record

VenuePhysics of Plasmas · 2013
Typearticle
Languageen
FieldPhysics and Astronomy
TopicIonosphere and magnetosphere dynamics
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaWestern Canada Research Grid
KeywordsPhysicsComputational physicsLangmuir probeIonospherePlasmaParticle-in-cellMagnetic fieldElectric fieldPlasma diagnosticsElectron densityCurrent sheetAtomic physicsMagnetohydrodynamicsGeophysics

Abstract

fetched live from OpenAlex

We model the current characteristics of the DEMETER Segmented Langmuir probe (SLP). The probe is used to measure electron density and temperature in the ionosphere at an altitude of approximately 700 km. It is also used to measure the plasma flow velocity in the satellite frame of reference. The probe is partitioned into seven collectors: six electrically insulated spherical segments and a guard electrode (the rest of the sphere and the small post). Comparisons are made between the predictions of the model and DEMETER measurements for actual ionospheric plasma conditions encountered along the satellite orbit. Segment characteristics are computed numerically with PTetra, a three-dimensional particle in cell simulation code. In PTetra, space is discretized with an unstructured tetrahedral mesh, thus, enabling a good representation of the probe geometry. The model also accounts for several physical effects of importance in the interaction of spacecraft with the space environment. These include satellite charging, photoelectron, and secondary electron emissions. The model is electrostatic, but it accounts for the presence of a uniform background magnetic field. PTetra simulation results show different characteristics for the different probe segments. The current collected by each segment depends on its orientation with respect to the ram direction, the plasma composition, the magnitude, and the orientation of the magnetic field. It is observed that the presence of light H+ ions leads to a significant increase in the ion current branch of the I-V curves of the negatively polarized SLP. The effect of the magnetic field is demonstrated by varying its magnitude and direction with respect to the reference magnetic field. It is found that the magnetic field appreciably affects the electron current branch of the I-V curves of certain segments on the SLP, whereas the ion current branch remains almost unaffected. PTetra simulations are validated by comparing the computed characteristics and their angular anisotropy with the DEMETER measurements, as simulation results are found to be in good agreement with the measurements.

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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.234
Teacher spread0.219 · 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

Citations15
Published2013
Admission routes2
Has abstractyes

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