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Record W4312191399 · doi:10.1109/tap.2022.3209253

Comparison of Electromagnetic Forces Evaluated in Yee-Lattice Finite-Difference Time-Domain and Lattice-Boltzmann Method

2022· article· en· W4312191399 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2022
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of British Columbia, Okanagan CampusKelowna General Hospital
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLattice Boltzmann methodsPhysicsElectric fieldMagnetic fieldComputational physicsFinite-difference time-domain methodTime domainForce between magnetsLattice (music)ScatteringMathematical analysisClassical mechanicsMathematicsMechanicsMagnetic energyMagnetizationComputer scienceQuantum mechanicsAcoustics

Abstract

fetched live from OpenAlex

Electrodynamic simulations in the Yee-lattice finite-difference time-domain method (YL-FDTDM) require half-unit-cell and half-time-unit offsets between electric and magnetic field components. To evaluate energy, momentum, and force in the YL-FDTDM, electric and magnetic fields must be colocated in both space and time. Colocation operations can be computationally intensive while introducing implementation complexity and numerical error. As an alternative to the YL-FDTDM, the Hauser and Verhey electrodynamic lattice-Boltzmann method (HV ELBM) is implemented on a single lattice representing electric and magnetic fields at the same location and time. Since colocation is not required on a single lattice, its central differences are simpler to implement and more accurate. Continuous plane-wave scattering of electric and magnetic fields from a nondispersive dielectric sphere is solved using the YL-FDTDM, the HV ELBM, and Mie scattering analysis. The YL-FDTDM and HV ELBM are compared in terms of numerical error and computational time representing the analytical Mie solution for the Einstein and Laub time-averaged force density. The HV ELBM requires less computational time to evaluate a time-averaged force density with half the error of the YL-FDTDM. At a similar absolute error, the HV ELBM evaluates a time-averaged force density in less than 10% of the computational time.

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 categoriesnone
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 score0.832
Threshold uncertainty score0.613

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 head0.025
GPT teacher head0.310
Teacher spread0.286 · 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