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Record W3016071471 · doi:10.1177/0954406220917406

A novel approach to hot die-less clinching process for high strength AA7075-T6 sheets

2020· article· en· W3016071471 on OpenAlexaff
Mostafa K. Sabra Atia, Mukesh Jain

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Welding Techniques Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMaterials scienceComposite materialHot stampingShear (geology)Die (integrated circuit)MicrostructureDuctility (Earth science)BlankMetallurgy

Abstract

fetched live from OpenAlex

High strength AA7075-T6 aluminum sheets were joined by hot die-less clinching by locally heating the clinching region with an electrical resistance heating method. This method applied a large amount of current in the range 7.5–15 kA over a time period of 2–3 s to enhance the local ductility of AA7075-T6 sheets. A modified die-less clinching tool was developed to carry current from the blank holder to the anvil through a pair of AA7075-T6 sheets to be clinched. The above range of applied current and time duration led to an increase in sheet metal temperature in the range 175–260 ℃ leading to material softening and a consequent reduction in the clinch forming force as well as improved material flow. The clinched joints produced with constant forming force of 60 kN resulted in an increase in lap shear joint strength up to 41% with an applied current of 15 kA. Microstructure examination of the clinched region for a range of electrical resistance heating conditions revealed sound joints with previously reported forming and force locking mechanisms as well as recently identified elevated temperature material locking mechanism in the literature. The geometric interlock resulted in nonlinear increase in force with displacement in the lap shear test as well as instantaneous drop in the force due to failure of material locking.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.670
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.255
Teacher spread0.229 · 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.

Study designSimulation or modeling
Domainnot available
GenreMethods

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering ScienceSame topicAdvanced Welding Techniques AnalysisFrench-language works237,207