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Record W7061948531

Self-Piercing Riveting of High Ductility Al-Fe-Zn-Mg Casting Alloy (Nemalloy HE700) in F Temper: Modelling, Simulation and Experimental Analysis

2024· dissertation· en· W7061948531 on OpenAlex

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.

Bibliographic record

VenueMacSphere (McMaster University) · 2024
Typedissertation
Languageen
FieldEngineering
TopicAdvanced Power Generation Technologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsRivetAlloyDuctility (Earth science)Strain hardening exponentVoid (composites)Finite element methodFormabilityPlasticityAluminiumCasting
DOInot available

Abstract

fetched live from OpenAlex

This thesis presents a comprehensive investigation into the feasibility and optimization of self-piercing riveting (SPR) for joining high-ductility die-cast aluminum alloy Nemalloy HE700 in F temper (as-cast) condition to dissimilar sheet materials, namely wrought aluminum alloy 6082-T6 and dual-phase steel DP600. The study demonstrates successful SPR joining of HE700 to these materials, with optimized process parameters and joint quality meeting automotive industry standards. Systematic experimental studies were conducted to investigate the effects of key SPR process parameters, including die geometry, ring groove depth, rivet hardness, and length, on joint quality and performance. Microstructural characterization revealed distinct patterns of grain flow and localized hardening in HE700 around the rivet and die features, providing insights into its deformation characteristics. Finite element simulations, incorporating advanced material models such as Johnson-Cook plasticity and failure for AA6082 and DP600, and Voce hardening with Gurson-Tvergaard-Needleman void damage model for HE700, were developed and extensively validated against experimental results. The simulations accurately predicted potential failure sites in HE700, aligning with experimental observations of crack initiation. Numerical parametric studies demonstrated the intricate effects of process parameters and material properties on the stress and strain distributions, material flow, and damage accumulation during SPR. The research contributes to the growing body of knowledge on advanced joining techniques for dissimilar materials, supporting vehicle lightweighting efforts. It establishes a comprehensive methodology integrating experiments, microstructural characterization, and simulations for studying and optimizing SPR processes for low ductility casting alloys, serving as a blueprint for future research and industrial implementation. The findings demonstrate the viability and potential of SPR technology for integrating high-ductility die-cast aluminum alloy HE700 into lightweight automotive body structures, paving the way for its wider industrial adoption.

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 categoriesMeta-epidemiology (narrow)
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 score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.227
Teacher spread0.216 · 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