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Record W2272935298 · doi:10.4271/2006-01-0787

Contact Pressure Distribution for Flow of Metal through Drawbeads

2006· article· en· W2272935298 on OpenAlexaff
Sumithra Sriram

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2006
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsMitel (Canada)
FundersFord Motor Company
KeywordsFlow (mathematics)Distribution (mathematics)Materials scienceComputer scienceMechanicsMathematicsPhysics

Abstract

fetched live from OpenAlex

To aid in understanding die wear when stamping AHSS, a study to characterize the contact pressure distribution in drawbeads during stamping had been undertaken. As direct measurement of contact pressure for a drawbead is not feasible during metal flow, a combination of experimental and Finite Element (FE) simulation techniques were used to determine the contact pressure distributions and the maximum contact pressure for a number of different conditions. Testing was conducted using the Drawbead Simulator (DBS) for two different bead configurations. The materials in this investigation were 0.7mm and 0.8mm EG BH210 and EG DP500. Static Implicit FE analyses were conducted with ABAQUS Standard using 2D plane strain continuum elements. A combined hardening model in conjunction with strain rate effects was used to describe material behavior as it flows through the drawbeads. Trends for the maximum contact pressure as a function of drawbead radius, material yield strength and thickness were generated.

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 score0.008
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.001

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 head0.009
GPT teacher head0.229
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 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

Citations1
Published2006
Admission routes1
Has abstractyes

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