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Record W3124624333 · doi:10.1109/temc.2020.3048704

3-D FDTD Method for Fast Calculation of Geomagnetic Storm Electromagnetic Fields

2021· article· en· W3124624333 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIEEE Transactions on Electromagnetic Compatibility · 2021
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsFinite-difference time-domain methodCurvatureGeomagnetic stormEarth's magnetic fieldFinite difference methodComputational physicsPhysicsGeophysicsMagnetic fieldMathematicsMathematical analysisOpticsGeometry

Abstract

fetched live from OpenAlex

In this article, a 3-D finite-difference time-domain (FDTD) method is proposed for rigorous modeling and fast calculation of ultralow frequency geomagnetic storm electromagnetic fields (GS-EMFs). The proposed FDTD approach enables modeling of large-scale and complex 3-D earth structure (e.g., multilayer ground and earth curvature). Unlike conventional FDTD methods, the proposed FDTD method does not require extensive computational resources when dealing with ultralow frequency problems. In this article, the ground surface GS-EMFs produced by an electrojet (line current and sheet current sources) are compared with those obtained using the classical 1-D approaches for case of uniform and horizontally stratified ground. The effect of horizontally vertically multilayer ground and earth curvature on the GS-EMFs is evaluated by the proposed FDTD method. The presented results fully support the adequacy and efficiency of the proposed FDTD method for modeling of large-scale and complex 3-D earth structures for calculation of GS-EMFs.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.514
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.286
Teacher spread0.270 · 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