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Record W2575778894 · doi:10.1109/tap.2017.2653764

A Structured Grid Finite-Element Method Using Computed Basis Functions

2017· article· en· W2575778894 on OpenAlexafffund
Moein Nazari, Jon P. Webb

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicElectromagnetic Scattering and Analysis
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPolygon meshFinite element methodComputer scienceTetrahedronComputationBasis functionBasis (linear algebra)GridMesh generationAlgorithmRadar cross-sectionRegular gridComputational scienceMixed finite element methodExtended finite element methodMathematical optimizationRadarGeometryMathematicsMathematical analysisStructural engineeringComputer graphics (images)

Abstract

fetched live from OpenAlex

Structured (e.g., rectangular) meshes in finite-element (FE) analysis offer several advantages, but are not often used because of the error introduced in fitting material interfaces. The nonconforming voxel FE method (NVFEM) is a hierarchical structured method that systematically reduces the geometric error in an adaptive way, but it requires large numbers of elements and therefore is expensive. By computing basis functions that take into account the interface cutting through an element, the number of elements needed is greatly reduced. The resulting method, CBF-NVFEM, is applied to the computation of the radar cross section of free-space scatterers. Results indicate that CBF-NVFEM is much more efficient than NVFEM and is competitive with FEM using unstructured meshes of tetrahedra.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.898
Threshold uncertainty score0.819

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 studies0.0010.000
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 head0.021
GPT teacher head0.280
Teacher spread0.259 · 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 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

Citations5
Published2017
Admission routes2
Has abstractyes

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