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Record W1588692935 · doi:10.1063/1.2740927

Some Considerations In Modeling Axisymmetric Deep Drawing And Redrawing Process And LDR Prediction

2007· article· en· W1588692935 on OpenAlexaff
Sang Wook Han, M. Bruhis, Mukesh Jain

Bibliographic record

VenueAIP conference proceedings · 2007
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDeep drawingClampingStiffnessDisplacement (psychology)AnisotropyRotational symmetryWork (physics)Computer scienceDie (integrated circuit)Structural engineeringMechanical engineeringEngineeringGeometryMathematics

Abstract

fetched live from OpenAlex

The drawability of sheet material in deep drawing followed by redrawing has not been studied theoretically in detail. In addition, the clamping force during deep drawing has not been properly simulated by FE method in the past due to the neglect of the operating machine stiffness. Both of these aspects are studied in this work. A new FE model for deep drawing and redrawing has been developed, which accounts for the operating machine stiffness. In this model, the draw die is connected to a semi‐rigid component of the test frame by spring elements so that the stiffness of the operating machine can be controlled by the stiffness of these springs. Also, a mathematical model to determine the limiting drawing ratio (LDR) of deep drawing and redrawing processes has been derived based on the extension of an existing analytical model and Hill’s anisotropic criterion. The results of the mathematical model have been validated by corresponding experimental and FE simulation work in terms of punch load and clamping force versus punch displacement and thickness distributions along the product profile.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.924
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.023
GPT teacher head0.261
Teacher spread0.238 · 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".

Quick stats

Citations1
Published2007
Admission routes1
Has abstractyes

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