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Record W2779295571 · doi:10.1109/tap.2017.2787658

Vector Parabolic Equation-Based Derivation of Rectangular Waveguide Surrogate Models of Arched Tunnels

2017· article· en· W2779295571 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 · 2017
Typearticle
Languageen
FieldEngineering
TopicRadio Wave Propagation Studies
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWaveguideMathematical analysisPhysicsOpticsGeometryMathematicsAcoustics

Abstract

fetched live from OpenAlex

Radio-wave propagation in tunnels and mines can be qualitatively understood by representing these environments as overmoded waveguides. Waveguide models are fast and intuitive, but the accurate prediction of the propagation characteristics of realistic geometries is beyond their scope. Such predictions can be derived by computationally intensive techniques, such as ray-tracing and vector parabolic equation (VPE) methods. This paper combines the two approaches, to extract surrogate models of arched tunnels in the form of rectangular waveguides. The parameters of the latter are optimized to match their propagation characteristics to those of the original arched tunnel, as predicted by the VPE method. The accuracy and limitations of these surrogate models are thoroughly evaluated. Their practical usefulness is demonstrated in an application where they are iteratively used, in lieu of the original computationally costly arched tunnel model, to optimally distribute the access points of an in-tunnel wireless communication system.

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: none
Teacher disagreement score0.707
Threshold uncertainty score0.645

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 head0.047
GPT teacher head0.254
Teacher spread0.207 · 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