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FE Study for Reducing Forming Forces and Flat End Areas of Cylindrical Shapes Obtained by the Roll-Bending Process

2014· article· en· W2244643682 on OpenAlex
Henri Champliaud Quan Hoang Tran, Zhengkun Feng, Thiên My Dao

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

VenueJournal of Mechanics Engineering and Automation · 2014
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBendingProcess (computing)Structural engineeringMechanical engineeringMaterials scienceRoll formingEngineeringMechanicsPhysicsComputer science

Abstract

fetched live from OpenAlex

A roll-bending process that minimizes the flat areas on the leading and trailing ends of formed plates will produce more accurate and easier assemble final shapes. There are several methods of minimizing flat areas, but they are costly or difficult to apply for thick plates. This study proposes a new, simple approach that reduces these flat areas. This approach includes moving the bottom roll slightly along the feeding direction and adjusting the bottom roll location. Sensitivity analyses were performed using a developed 3D dynamic FE (finite element) model of an asymmetrical roll-bending process in the Ansys/LS-Dyna software package. Simulations were validated by experiments run on an instrumented roll-bending machine. The FE results indicate that this new approach not only minimizes the flat areas but also reduces the forming forces.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.356
Threshold uncertainty score0.384

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.008
GPT teacher head0.241
Teacher spread0.233 · 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