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Record W2900041768 · doi:10.3390/met8110901

Finite Element Simulation of High-Speed Blow Forming of an Automotive Component

2018· article· en· W2900041768 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMetals · 2018
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsViscoplasticityForming processesMaterials scienceFinite element methodSuperplasticityConstitutive equationDeformation (meteorology)Component (thermodynamics)MechanicsStructural engineeringComposite materialAlloyEngineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

High-speed blow forming (HSBF) is a new technology for producing components with complex geometries made of high strength aluminum alloy sheets. HSBF is considered a hybrid-superplastic forming method, which combines crash forming and gas blow forming. Due to its novelty, optimization of the deformation process parameters is essential. In this study, using the finite element (FE) code ABAQUS, thinning of an aluminum component produced by HSBF under different strain rates was investigated. The impact of element size, variation of friction coefficient, and material constitutive model on thinning predictions were determined and quantified. The performance of the FE simulations was validated through forming of industrial size parts with a complex geometry for the three investigated strain rates. The results indicated that the predictions are sensitive to the element size and the coefficient of friction. Remarkably, compared to a conventional power law model, the variable m-value viscoplastic (VmV) model could precisely predict the thickness variation of the industrial size component.

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.

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: Empirical
Teacher disagreement score0.384
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 head0.024
GPT teacher head0.286
Teacher spread0.262 · 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