MétaCan
Menu
Back to cohort
Record W1979617133 · doi:10.1088/0953-2048/22/7/075018

AC losses in thin superconductors: the integral equation method applied to stacks and windings

2009· article· en· W1979617133 on OpenAlexaff
Roberto Brambilla, Francesco Grilli, Doan N. Nguyen, L. Martini, Frédéric Sirois

Bibliographic record

VenueSuperconductor Science and Technology · 2009
Typearticle
Languageen
FieldPhysics and Astronomy
TopicPhysics of Superconductivity and Magnetism
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsSuperconductivityComputationElectromagnetic coilSymmetry (geometry)Current (fluid)Current densityIntegral equationCritical currentDistribution (mathematics)PhysicsComputer scienceCondensed matter physicsMathematical analysisMathematicsThermodynamicsQuantum mechanicsAlgorithmGeometry

Abstract

fetched live from OpenAlex

In this paper we present a method for computing transport current ac losses in interacting thin superconductors. The method solves the integral equations for the sheet current density distribution and is specifically developed for those configurations where the symmetry of the current density distributions allows writing the equation in a self-consistent form, without the need for using an auxiliary 2D model to describe the interaction between superconducting tapes. This results in very short computation times and therefore the model can be very useful for optimizing the design of superconducting devices. The method has been tested for different cases of practical applications and the ac loss results have been compared with those obtained with analytical models and with experiments.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.278
Teacher spread0.263 · 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 designSimulation or modeling
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

Citations53
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueSuperconductor Science and TechnologySame topicPhysics of Superconductivity and MagnetismFrench-language works237,207