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Record W1996841855 · doi:10.1177/0954405413501670

Single-point incremental forming of 6061-T6 using electrically assisted forming methods

2014· article· en· W1996841855 on OpenAlexaff
David W. Adams, Jack Jeswiet

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture · 2014
Typearticle
Languageen
FieldEngineering
TopicElectromagnetic Effects on Materials
Canadian institutionsQueen's University
Fundersnot available
KeywordsFormabilityCurrent (fluid)Current densityMaterials scienceResistive touchscreenSpallSurface finishRange (aeronautics)Composite materialSurface roughnessDirect currentMetallurgyVoltageEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

In this article, large direct current is applied through the tool to improve formability while forming 6061-T6 Al using single-point incremental forming. Special attention is paid to the direct effect of current density, as opposed to bulk resistive heating, to determine whether the electroplastic effect is significant in raising the formability without requiring temperature rise. Tests are performed to determine the maximum wall angle that can be formed for a variety of current and tool settings. The area of contact between the tool and sheet is modeled, and a control system is proposed and tested to vary the current to maintain a constant current density during tests. The phenomenon of current threshold density is observed at a current density range agreeing with previous studies forming the same material in different loading cases. A significant formability increase is observed at a range of current density values that agree with previously published work with this material in different loading cases. Surface roughness and spalling are also shown to be directly affected by current.

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: Bench or experimental
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 studies0.0000.000
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 head0.013
GPT teacher head0.238
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

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

Citations38
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part B Journal of Engineering ManufactureSame topicElectromagnetic Effects on MaterialsFrench-language works237,207