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Record W1559211729 · doi:10.4271/2010-01-0222

Experimental Exploration of the Aluminum Tube Drawing Process for Producing Variable Wall Thickness Components used in Light Structural Applications

2010· article· en· W1559211729 on OpenAlexafffund
Michel Guillot, Mario Fafard, Sébastien Girard, Ahmed Rahem, Guillaume D’Amours

Bibliographic record

VenueSAE technical papers on CD-ROM/SAE technical paper series · 2010
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsNational Research Council CanadaUniversité Laval
FundersUniversité Laval
KeywordsMandrelTube (container)Materials scienceSizingComposite materialDeformation (meteorology)LubricationProcess (computing)Mechanical engineeringEngineeringComputer science

Abstract

fetched live from OpenAlex

Tube drawing is a well known process involving at room temperature the reduction of diameter and wall thickness to obtain specified values. The initial tube is drawn into a die of a smaller opening and its thickness achieved by use of a mandrel. Usually, the mandrel has a land area which diameter defines by sizing the inside diameter of the final tube. Some structural components found in cars, aircrafts and other vehicles require bent or hydroformed tubes of lower weight. It is of interest to have tubes of varying axial or circumferential thickness so that to reduce overweight in low stressed areas and reinforce it otherwise. However, the production of tubes of varying thickness is more difficult in reason notably of higher metal flow stresses in the deformation zone and the need to control precisely the mandrel position during drawing. Axial thickness variation is obtained using a mandrel with stepped lands or with a slight taper while circumferential variation is achieved with a mandrel of desired internal or external shape (e.g. oval). In this paper, two techniques for axial tube wall thickness variation and one technique for circumferential variations are introduced and tested. First, the techniques to produce drawn tubes with thickness variations are presented. For testing, a small (335 kN) instrumented tube drawing machine is used. Details on this machine, process lubrication, monitored data and on the tooling implemented are also presented. Initial tubes are mainly AA6063 extrusions of 63.5mm O.D. and 2.6mm thick and the final outside diameter, i.e. the inside diameter of the die, is about 47.5 mm. AA6061 tubes are also drawn. Starting with drawing tests without mandrel, the natural flow of the tube and the drawing force involved are measured. Secondly, tubes of 4 different thicknesses are produced with a stepped mandrel and the strain hardening effect on mechanical properties established. Using a tapered mandrel, tubes of continuously varying wall thickness are tested. Higher local pressure in the die corner radius restricts proper lubrication in certain conditions but results are promising in most cases. We also study the effect of thickness rate of change along the tube. Finally, tests with a stepped oval mandrel provided good results for circumferential thickness variations. The dimensional quality is measured using a coordinate measuring machine and mechanical properties obtained from tensile tests in both initial and drawn tubes. Finally, despite some minor problems, the techniques proposed can efficiently produce tubes with thickness variations and have a very strong potential for industrial use.

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)0.001
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.020
GPT teacher head0.276
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 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

Citations15
Published2010
Admission routes2
Has abstractyes

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