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Record W2758627514 · doi:10.1109/tgrs.2017.2747404

Subgridded FDTD Modeling of Ground Penetrating Radar Scenarios Beyond the Courant Stability Limit

2017· article· en· W2758627514 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 Geoscience and Remote Sensing · 2017
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of Toronto
FundersChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsFinite-difference time-domain methodGround-penetrating radarLossy compressionStability (learning theory)Limit (mathematics)RadarComputer scienceOverhead (engineering)Finite difference methodDispersion (optics)AlgorithmOpticsPhysicsMathematicsMathematical analysisTelecommunications

Abstract

fetched live from OpenAlex

This paper presents an efficient 3-D finite-difference time-domain (FDTD) subgridding scheme that is free of the Courant-Friedrichs-Lewy stability condition, for the modeling of ground-penetrating radar (GPR) scenarios in lossy dispersive media. Spatial filtering of FDTD fields within the subgrid is employed to render the time step independent of the cell size in the fine-cell subgrids. This process is applied with minimal modification of the original FDTD code, no implicit operations, and very modest computational overhead. Moreover, multiterm dispersion is included to model practical GPR scenarios involving the detection of realistic scatterers within dispersive soil. Several numerical examples are provided to demonstrate the potential of the proposed method as a powerful GPR modeling tool.

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)0.001
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 score0.909
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.033
GPT teacher head0.267
Teacher spread0.234 · 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