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Record W4388468801 · doi:10.1017/flo.2023.28

Turbulence-induced electrical discharges in charged particle-laden Martian boundary layers

2023· article· en· W4388468801 on OpenAlexafffund
Mustafa Mutiur Rahman, Ahmed Saieed, Jean-Pierre Hickey

Bibliographic record

VenueFlow · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAeolian processes and effects
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaAlliance de recherche numérique du Canada
KeywordsMartianElectric fieldMars Exploration ProgramAtmosphere of MarsBoundary layerPlanetary boundary layerMechanicsAtmospheric sciencesPhysicsCharged particleParticle (ecology)TurbulenceGeophysicsEnvironmental scienceAstrobiologyGeologyIon

Abstract

fetched live from OpenAlex

Martian dust storms in the planetary boundary layer share many qualitative similarities to terrestrial sandstorms. Both of these turbulence-driven, particle-laden boundary layer flows are known to generate electric fields due to the transport of differentially charged particles; this charge separation can be strong enough to lead to dielectric breakdown in the form of sparks or lightning. Using wall-modelled large-eddy simulations supplemented with conservation of equations for the charged particle transport, representative simulations of neutrally stable Martian and terrestrial particle-laden boundary layer flows are compared. The simulations, albeit canonical in nature, provide evidence to support previous observations of the less frequent occurrence of lightning on Mars but a higher occurrence of localised electric discharge events due to the much lower breakdown potential. The rarefied Martian atmosphere impedes charged particle transport, resulting in a weaker electric field than the equivalent terrestrial sandstorm. The lower drag force in the rarefied Martian atmosphere means that the electrostatic force plays a more significant role in the particle transport, which results in a self-regulation of the electric field. The strongest Martian dust storms show evidence of significant breakdown events and these discharge events only occur very close to the ground despite the very large boundary layer on Mars.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.361
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.003

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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2023
Admission routes2
Has abstractyes

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