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Record W2145362397 · doi:10.1109/fie.1999.839294

Teaching transmission line transients using computer animation

2003· article· en· W2145362397 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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicExperimental Learning in Engineering
Canadian institutionsConcordia University
Fundersnot available
KeywordsTransmission lineAnimationComputer scienceElectric power transmissionComputer animationWaveformLine (geometry)Generator (circuit theory)Electronic circuitElectromagneticsElectronic engineeringElectrical engineeringComputer graphics (images)EngineeringTelecommunicationsPhysicsRadarMathematics

Abstract

fetched live from OpenAlex

Transmission line theory in electromagnetics comes alive when the travelling waves are animated on a computer screen, using program "BOUNCE". Fundamental concepts such as "travelling wave", "reflected wave", and "load matching" are forcefully demonstrated in the classroom. Problems using series connections of dissimilar line, shunt loads and branches can be readily examined. Transmission line theory is applied to problems in the design of tri-state logic circuits that cannot be solved readily by hand, using animation to show how the voltage waveforms arise. Animation is used with a sinusoidal generator to illustrate the evolution to the sinusoidal steady state, as an introduction to solving transmission line circuits with phasors. Students are encouraged to run BOUNCE at home as a computational laboratory to verify their solutions to homework problems. This paper presents the BOUNCE program, and some of the demonstrations with BOUNCE that are used in the classroom.

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: Empirical · Consensus signal: none
Teacher disagreement score0.533
Threshold uncertainty score0.507

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 head0.011
GPT teacher head0.236
Teacher spread0.225 · 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

Quick stats

Citations14
Published2003
Admission routes1
Has abstractyes

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