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Record W4220719626 · doi:10.18280/rcma.320106

Bending Titanium Sheets with 3D-Printed PETG Tools

2022· article· fr· W4220719626 on OpenAlexvenueno aff
Wisam Hameed Hanoon, Nasri S. M. Namer, Sami Ali Nama

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2022
Typearticle
Languagefr
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsBendingMaterials scienceTitaniumComposite material3d printedStructural engineeringMetallurgyEngineeringManufacturing engineering

Abstract

fetched live from OpenAlex

3D printing is one of the contemporary technologies that can be used effectively to produce forming tools. Punch-rotary rocker arrangements were printed from Polyethylene Terephthalate Glycol (PETG) filament, and were used to perform bending process for sheets of Titanium Grade2 (TiG2). Four variables, each of which has four levels were investigated numerically by means of DEFORM 2D software to find out their effect on springback angle. Wall thickness (4, 6, 8mm, and solid 100% infill), rocker inner radius (1, 1.5, 2, 2.5mm), punch radius (1, 1.5, 2, 2.5mm), and plate thickness (0.5, 0.8, 1, 1.25mm). experimental work was also conducted to verify the numerical work. The results showed that increasing wall thickness decreases the resulting springback angle, and the deviation of spring back angle between the solid rocker and that of (6 and 8mm wall thickness) was 1.14% and 1.10% respectively. Also, it was found that increasing rocker inner radius, punch radius, and plate thickness decreases the spring back. For different rocker bending angle, "hook" phenomenon plays a major role in the resulting spring back value.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.489
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.255
Teacher spread0.198 · 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.

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

Citations5
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueRevue des composites et des matériaux avancésSame topicAdditive Manufacturing and 3D Printing TechnologiesFrench-language works237,207