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Record W2037911773 · doi:10.1109/lawp.2014.2313737

A High-Accuracy ADI Scheme for the Vector Parabolic Equation Applied to the Modeling of Wave Propagation in Tunnels

2014· article· en· W2037911773 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 Antennas and Wireless Propagation Letters · 2014
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAlternating direction implicit methodCrank–Nicolson methodScheme (mathematics)Wave equationMathematical analysisParabolic partial differential equationMathematicsWave propagationApplied mathematicsAlgorithmPartial differential equationPhysicsFinite difference methodOptics

Abstract

fetched live from OpenAlex

The vector parabolic equation has been widely used to model radio wave propagation in tunnels. For its numerical solution, the Crank-Nicolson as well as the Alternating Direction Implicit (ADI) methods have been employed, with the latter being significantly faster than the former. This letter focuses on a modified ADI method, namely a Mitchell-Fairweather scheme. Applied to the vector parabolic equation, this scheme significantly improves the accuracy of the original ADI formulation while retaining its computational efficiency. The relative advantages of the Mitchell-Fairweather scheme are demonstrated in a case study involving an actual tunnel geometry.

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 score0.552
Threshold uncertainty score0.357

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 studies0.0000.000
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 head0.246
Teacher spread0.221 · 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