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Influence of Spatial Grain Orientation Distribution on Sheet Metal Necking

2006· article· en· W2084044545 on OpenAlexaff
Pei Dong Wu, David J. Lloyd

Bibliographic record

VenueMaterials science forum · 2006
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsNovelis (Canada)McMaster University
Fundersnot available
KeywordsNeckingMaterials scienceElectron backscatter diffractionCube (algebra)Sheet metalTension (geology)PlasticityFinite element methodTexture (cosmology)Orientation (vector space)GeometryCrystal plasticityPole figurePlane (geometry)Composite materialStructural engineeringCompression (physics)MicrostructureMathematics

Abstract

fetched live from OpenAlex

Necking under in-plane plane strain tension along the transverse direction (TD) is numerically simulated for two sheets: one with very high Cube (HC) and the other with low Cube (LC). To do so, the EBSD measurement is performed in the TD-ND (normal direction) section for the sheets. The EBSD map (grain orientations and their spatial distributions) is directly implemented into the crystal plasticity based finite element code. More specifically, the measured orientations are assigned to elements in the mesh according to their positions. The values of the material parameters in the crystal plasticity model are determined by curve-fitting numerical simulations of uniaxial tension in the rolling direction (RD) to corresponding experimental data. The effect of spatial grain orientation distribution on necking is emphasized. It is found that both the global averaged texture and its spatial distribution are important to the onset of necking. The predicted results are in good agreement with experimental observations.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.360

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 head0.006
GPT teacher head0.238
Teacher spread0.232 · 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 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

Citations1
Published2006
Admission routes1
Has abstractyes

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