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Record W2033332256 · doi:10.1115/pvp2012-78071

Numerical Simulation of Mecano-Welding Process for Cylinder Manufacturing

2012· article· en· W2033332256 on OpenAlexaff
Zhengkun Feng, Henri Champliaud

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsBent molecular geometryWeldingBendingResidual stressProcess (computing)Structural engineeringMaterials scienceCylinderMechanical engineeringGas metal arc weldingPlanarArc weldingEngineeringComposite materialComputer science

Abstract

fetched live from OpenAlex

Pyramidal three-roll bending has the advantage of simple configuration and is widely used in manufacture. However, the bent shape has two planar zones near the front and rear ends. This paper proposes the modeling of the mecano-welding process which provides improved circularity of the bent shape. This process includes three sub-processes: the first sub-process is the roll bending from a plate with cylindrical rolls, the second sub-process which is the gas metal arc-welding process used to join the gap of the bent tubular section, and the third sub-process is the rerun roll bending of the welded shape. Results of the simulation of the first two sub-processes under the well-known ANSYS and ANSYS/LS-DYNA environment are reported. The bent shape after the first roll bending, the distributions of the temperature and residual stress after the welding are illustrated.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.286
Teacher spread0.256 · 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 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

Citations0
Published2012
Admission routes1
Has abstractyes

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