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Numerical and Experimental Study of Preforming Stage in Tube Hydroforming

2014· article· en· W2082726744 on OpenAlex
Saeed Mojarad Farimani, Javad Gholipour, Henri Champliaud, Jean Savoie, Priti Wanjara

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

VenueKey engineering materials · 2014
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsNational Research Council CanadaÉcole de Technologie Supérieure
FundersDivision of Materials ResearchNatural Sciences and Engineering Research Council of Canada
KeywordsHydroformingMaterials scienceTube (container)Stage (stratigraphy)Deformation (meteorology)Selective laser sinteringForming processesProcess (computing)Composite materialAerospacePressingComputer simulationSinteringMechanical engineeringStructural engineeringEngineeringComputer scienceAerospace engineering

Abstract

fetched live from OpenAlex

The preforming stage in hydroforming of an aerospace generic shape was investigated using a combination of experimentation and numerical modeling. The preform die was manufactured using a rapid prototyping method, namely the selective laser sintering (SLS) process. The preforming experiments were conducted on 0.9 mm and 1.2 mm thick stainless steel 321 (SS321) tubes. To evaluate the preforming process, an automated deformation measurement system, ARGUS ® , was used to measure the 3-dimensional (3D) strains on the deformed tubes. Data collected from the experiments were used to validate the simulation of the preforming stage. The simulation and experimental results were found to be in good agreement, indicating that the preform model can be used as a starting point for simulating the tube hydroforming (THF) process. In addition, the SLS approach was found to be very promising, as it reduced greatly the lead time and cost of process development for THF.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.722

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.231
Teacher spread0.223 · 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