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Record W2034374573 · doi:10.1109/tcpmt.2013.2245377

Macromodeling of Multilayered Power Distribution Networks Based on Multiconductor Transmission Line Approach

2013· article· en· W2034374573 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 Transactions on Components Packaging and Manufacturing Technology · 2013
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Compatibility and Noise Suppression
Canadian institutionsWestern University
Fundersnot available
KeywordsSpiceDiscretizationTransmission lineHelmholtz equationElectric power transmissionCoupling (piping)Partial differential equationFinite differenceComputer scienceFinite difference methodElectronic engineeringPower (physics)Topology (electrical circuits)Line (geometry)Helmholtz free energyMathematicsMathematical analysisPhysicsEngineeringElectrical engineeringGeometryTelecommunicationsBoundary value problem

Abstract

fetched live from OpenAlex

Typical modeling algorithms for multilayered irregular shaped power distribution networks are based on a finite difference solution of the Helmholtz equation. In this paper, the finite difference solution is demonstrated to be equivalent to a discretization of the Telegraphers partial differential equations for multiconductor transmission lines (MTL). With this concept, an efficient macromodeling algorithm for multilayered structures based on MTL theory is presented. The electromagnetic coupling between the plane layers due to wraparound currents is captured by the inductive and capacitive coupling between the multiconductor lines. A delay extraction-based macromodel is used to represent the MTL in SPICE that can better capture the distributed effects of the structure than existing lumped models. This approach is successfully implemented for multilayered structures with irregular geometries and is shown to be more accurate and efficient compared with existing SPICE lumped models.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.443
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.010
GPT teacher head0.202
Teacher spread0.192 · 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