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Record W4319438373 · doi:10.1049/mia2.12340

On the use of combined surface integral equations for the analysis of high contrast penetrable objects

2023· article· en· W4319438373 on OpenAlexaff
Moein Nazari, R. Moini, Simon Fortin, F. Dawalibi

Bibliographic record

VenueIET Microwaves Antennas & Propagation · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsSafe Engineering Services & Technologies (Canada)
Fundersnot available
KeywordsIntegral equationMathematical analysisPermittivityRadar cross-sectionSurface (topology)ScatteringMethod of moments (probability theory)Surface integralMaxwell's equationsBilinear interpolationContrast (vision)MathematicsDielectricPhysicsGeometryOptics

Abstract

fetched live from OpenAlex

Abstract Accurate solutions of electromagnetic scattering problems involving objects made of materials with large permittivity contrasts are considered. Problems are formulated with different commonly used combined surface integral equations (SIEs). All studied formulations are discretised through the method of moments with rooftop basis functions over flat quadrilaterals represented as bilinear surfaces, with razor‐blade functions being used for the testing procedure. The accuracy of the results is first investigated in detail for several frequencies and permittivity values using different numerical measures. It is shown that numerical instabilities may appear at frequencies corresponding to the physical resonances of the object, in particular in the near field and for large material parameter contrasts. The example of a dielectric resonator (DR) with cubic geometry is considered for the purpose of analysis, especially since to achieve smaller DR type antennas, it is necessary to use higher contrast materials. The accuracy of the combined surface integral equations to determine the natural resonant modes of the DR is investigated. It is found that the resonance modes can be accurately determined by exploring the radar cross section (RCS) of the DR in free space only if a proper combination of the electric and magnetic fields equations is applied.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score0.281

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)0.0000.000

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 head0.032
GPT teacher head0.249
Teacher spread0.218 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2023
Admission routes1
Has abstractyes

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