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Record W2140001569 · doi:10.1109/mper.2001.4311080

Power Losses in Steel Pipe Deliverring Very Large Currents

2001· article· en· W2140001569 on OpenAlexaff
Bruce C. W. McGee, F. Vermeulen

Bibliographic record

VenueIEEE Power Engineering Review · 2001
Typearticle
Languageen
FieldMaterials Science
TopicMagnetic Properties and Applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEddy currentHysteresisPermeability (electromagnetism)Materials scienceMechanicsMagnetic hysteresisFerromagnetismCurrent (fluid)Power (physics)Magnetic fieldCondensed matter physicsElectrical engineeringPhysicsThermodynamicsMagnetizationEngineeringChemistry

Abstract

fetched live from OpenAlex

This paper presents a finite difference time domain solution for the electromagnetic fields in ferromagnetic conducting steel pipes of the type used to deliver large currents for in-situ heating of heavy oil reservoirs and for in-situ environmental decontamination. A method is described whereby a single measured hysteresis loop can be used to deduce the family of hysteresis loops that governs the variable magnetic behavior throughout the pipe wall. Hysteresis and eddy current losses are calculated, and it is shown that hysteresis effects greatly alter the eddy current distribution and can more than triple the total power losses in the steel pipe when compared to the power losses that would be present if hysteresis effects are ignored and magnetic permeability is assumed constant.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.250
Teacher spread0.236 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2001
Admission routes1
Has abstractyes

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