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Record W7132569663

Additive manufacturing of soft and hard magnetics materials used in electrical machines

2019· article· en· W7132569663 on OpenAlexaffvenue
Fabrice Bernier, Maged Ibrahim, Mihaela Mihai, Yannig Thomas, Jean-Michel Lamarre

Bibliographic record

VenueNPARC · 2019
Typearticle
Languageen
FieldEngineering
TopicMetallic Glasses and Amorphous Alloys
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsFabricationFinite element methodContext (archaeology)Fused filament fabricationElectrical steelMaterial properties
DOInot available

Abstract

fetched live from OpenAlex

Additive manufacturing (AM) techniques such as cold spray and fused filament fabrication allows for 3D build-up permitting fabrication of high complexity shapes and configurations. The fabrication of soft and hard magnetic materials using these techniques was investigated in the context of 3D electrical machines. The use of 3D finite element analysis (FEA) to develop new motor topologies based on the advantages offered by AM will be discussed. FEA was also used to orientate the material development by identifying the most critical properties. The hard magnetic properties (coercivity and remanence), soft magnetic properties (permeability and losses) of both types of materials fabricated by both AM processes will be presented.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.089
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 integrity0.0000.000
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 head0.007
GPT teacher head0.193
Teacher spread0.186 · 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 teacher head, not a consensus.

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

Citations0
Published2019
Admission routes2
Has abstractyes

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Same venueNPARCSame topicMetallic Glasses and Amorphous AlloysFrench-language works237,207