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Prediction of Forming Limit Diagrams for Aluminum Alloy Sheet Using Finite Element Analysis

2006· article· en· W2035949836 on OpenAlexaff
Bing Li, T. J. Nye

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsMcMaster UniversityPublic Safety Canada
Fundersnot available
KeywordsNeckingForming limit diagramMaterials scienceFinite element methodSheet metalHardening (computing)AluminiumAlloyAnisotropyStrain hardening exponentComposite materialFormabilityForming processesStructural engineeringPhysicsOptics

Abstract

fetched live from OpenAlex

Prediction of forming limit diagram (FLD) for aluminum alloy sheet using finite element analysis without implementing pre-defined geometrical imperfections or material imperfections was studied. The limit strains of the FLD were determined by applying a new proposed localization criterion in the dome stretching test. The elements just outside the necking area, where their major and minor principal strains have no simultaneous change after localized necking happens, were chosen as the reference elements for measurement of limit strains. Simulations were carried out for various strain paths ranging from balanced biaxial stretching to uniaxial stretching. The effects of material properties, sheet thickness, anisotropic parameter and friction coefficient at the sheet punch interface on the locus of FLD were investigated. It was found that the material yield stress and average anisotropic parameter value has almost no effect on forming limits; larger strain-hardening exponent and higher sheet thickness result in higher level of forming limit strains; the friction coefficient has little influence on the locus of FLD but does affect the strain path taken during the deformation. The predicted FLD of AA 5182-O was compared with an experimentally determined FLD and very good agreement has been achieved. It was demonstrated that forming limit diagrams can be predicted by the finite element method without requiring any assumed geometric or material imperfections in the numerical model.

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 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 score0.614
Threshold uncertainty score0.462

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)0.0000.000

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 head0.030
GPT teacher head0.249
Teacher spread0.220 · 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.

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".

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Citations0
Published2006
Admission routes1
Has abstractyes

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