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Record W3193992805 · doi:10.32920/ryerson.14666577.v1

A study of hot tearing during solidification of B206 aluminum alloy

2021· preprint· en· W3193992805 on OpenAlexafffund
F. D’Elia

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicAluminum Alloy Microstructure Properties
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaUniversities Space Research Association
KeywordsTearingMaterials scienceMicrostructureAlloyCastingMetallurgyStructural materialGrain sizeStress (linguistics)Suspension (topology)Composite material

Abstract

fetched live from OpenAlex

Aluminum-copper (Al-Cu) alloy B206 is a high strength and ductile alloy showing promise for use in automotive suspension components. Incorporation of lightweight B206 alloy in automotive suspension components may significantly reduce overall vehicle weight and increase the vehicle’s fuel efficiency. However, one of the major factors inhibiting the use of B206 is its high susceptibility to hot tearing during casting. Hot tearing is a complex phenomenon attributed to alloy solidification, microstructure and stress/strain development within a casting. Numerous methods (e.g. preheating of mold, grain refinement, elimination of sharp corners in a component) help to reduce the occurrence of hot tears in castings, but the underlying mechanisms responsible for hot tearing remain ambiguous. This research aims to advance the understanding of the mechanisms responsible for hot tearing in B206 Al alloy. In this research, the conditions associated with the formation of hot tears in B206 were investigated via ex situ and in situ methods. Titanium was added in three levels (i.e. unrefined, 0.02 and 0.05 wt%) to investigate the effect of grain refinement on hot tearing. Ex situ neutron diffraction strain mapping was carried out on the three B206 castings to determine casting strain and stress. Further, in situ techniques were used to establish the onset temperature and solid fraction of hot tearing in B206 and to improve the understanding of microstructure development in B206. The results indicate that titanium additions had a significant impact on the hot tearing susceptibility of B206, by effectively reducing grain size and transforming grain morphology from coarse dendrites to fine globular grains. Further, thermal analysis suggested that grain refinement delayed the onset of dendrite coherency in B206 and therefore enhanced the duration of bulk liquid metal feeding for the refined casting conditions. As a result, the interactive effects of such factors resulted in a more uniform distribution of strain, and subsequent higher resistance to hot tearing for the grain refined castings. Finally, in situ analysis determined the onset solid fraction of hot tearing in B206 and provided an understanding of the role of microstructure on hot tearing in B206.

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 categoriesMeta-epidemiology (narrow)
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 score0.083
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.019
GPT teacher head0.225
Teacher spread0.206 · 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 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
Published2021
Admission routes2
Has abstractyes

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