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Record W2903498831 · doi:10.22215/etd/2017-12015

Modelling and optimizing through-the-Earth radio transmissions

2017· dissertation· en· W2903498831 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

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicElectromagnetic Simulation and Numerical Methods
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFinite-difference time-domain methodTransmitterSIGNAL (programming language)Radio propagationContext (archaeology)AcousticsPerfectly matched layerComputer scienceElectrical conductorRange (aeronautics)Radio frequencyEngineeringElectronic engineeringElectrical engineeringGeologyTelecommunicationsPhysicsOpticsAerospace engineering

Abstract

fetched live from OpenAlex

Through-the-Earth (TTE) radio has been proposed for emergency communications in locations inaccessible by conventional means, such as underground mines. While the technology is viable, it is unclear how the signal propagates in inhomogeneous media; neither modelling or obtaining a conductivity distribution in the context of TTE radio has been previously attempted. With a robust model, many practical questions can be answered, such as what is the maximum range or the optimal frequency to use, or where the transmitter and receiver should be ideally placed. To this end, a finitedifference time-domain (FDTD) code was developed and optimized for the forward modelling of TTE radio transmissions. This method is computationally intensive, and to improve performance, it was run on a graphics processing unit (GPU). The code was validated against analytical solutions for simple geometries.

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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.295
Threshold uncertainty score0.569

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 head0.028
GPT teacher head0.299
Teacher spread0.270 · 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