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Record W2405604985 · doi:10.1063/1.3457666

Straight Tube Hydroforming of Dual Phase (DP780) Steel Tubes With End-Feed

2010· article· en· W2405604985 on OpenAlexafffund
Alexander Bardelcik, Michael J. Worswick, F. Barlat, Young Hoon Moon, M. G. Lee

Bibliographic record

VenueAIP conference proceedings · 2010
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaAUTO21 Network of Centres of ExcellenceArcelorMittal
KeywordsHydroformingNeckingFormabilityMaterials scienceInternal pressureUpper and lower boundsTube (container)Composite materialExpansion ratioYield (engineering)Structural engineeringMathematicsEngineering

Abstract

fetched live from OpenAlex

Dual phase (DP780) 76.2 mm (3”) diameter steel tubes were hydroformed with various levels of end‐feed (EF). The results of this study showed that when zero EF was applied during hydroforming, the average burst pressure was 70 MPa (10,075 psi) and the corner‐fill expansion (CFE), which is a measure of formability, was 6.4 mm. When an EF force of approximately 50% of the material yield strength was applied during hydroforming, the tube was able to support an internal pressure of 151.7 MPa (22,000 psi) without failure and achieved a CFE of 11.5 mm. Finite element (FE) models of the hydroforming process accurately predicted the CFE of the tubes for the various EF cases tested. Upper and lower bound strain‐based forming limit curves (εFLC) were determined from free‐expansion burst test data. These curves were then used to derive the upper and lower bound extended stress‐based forming limit curves (XSFLC), which were in turn used to predict the necking (failure) pressure in the FE models. For the two cases where burst was achieved in the experiments, the upper and lower XSFLC failure criteria curves bound the measured burst pressures. Also, two different friction coefficients were used in the FE models to evaluate their effect on predicting the failure pressure, CFE and end‐feed displacement.

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 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 score0.052
Threshold uncertainty score0.935

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 communication0.0000.001
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 head0.014
GPT teacher head0.250
Teacher spread0.236 · 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.

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

Citations2
Published2010
Admission routes2
Has abstractyes

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