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Record W4403478630 · doi:10.6000/1929-5995.2024.13.18

Polymer Shaped Punches Produces with Fused Filament Fabrication to Improve Cup Accuracy in Sheet Metal Forming

2024· article· en· W4403478630 on OpenAlexvenueno aff
Luca Giorleo, I.K. Deniz, M. Ravelli

Bibliographic record

VenueJournal of Research Updates in Polymer Science · 2024
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceFabricationFused filament fabricationSheet metalProtein filamentPolymerComposite materialMetalMetallurgy

Abstract

fetched live from OpenAlex

Rapid tooling has become an effective solution for reducing time and costs in tool production. In sheet metal forming, polymer tools produced via additive manufacturing offer performance comparable to traditional tools. However, a key challenge in this area is compensating for the radial expansion of polymer tools during the forming process, which leads to reduced accuracy in the produced parts and limits the achievable forming depth. To address this issue, the authors of this study proposed a novel punch design aimed at containing radial expansion, thereby enabling greater drawing depth and improved part accuracy. Different punch geometries were designed with a re-entrant angle varying between 150° and 180°. Numerical simulations were conducted to evaluate the optimal geometry, identifying the 160° angle as the best option to compensate for radial expansion and reduce punch load. Experimental tests were then performed to verify the numerical results, demonstrating the potential of this new design producing cups with higher drawing depth and best radial accuracy.

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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.333
Teacher spread0.302 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Research Updates in Polymer ScienceSame topicAdditive Manufacturing and 3D Printing TechnologiesFrench-language works237,207