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Record W2889315016 · doi:10.3390/sym10090362

Investigation on the Effect of Type of Cooling on the Properties of Aluminum Alloy during Warm/Hot Hydromechanical Deep Drawing

2018· article· en· W2889315016 on OpenAlexaff
Gaoshen Cai, Chuanyu Wu, Dongxing Zhang

Bibliographic record

VenueSymmetry · 2018
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsWestern University
FundersNatural Science Foundation of Zhejiang ProvinceZhejiang Sci-Tech University
KeywordsMicrostructureAlloyMaterials scienceAluminiumHydroformingMetallurgyGrain sizeWater coolingAir coolingComposite materialMechanical engineeringTube (container)

Abstract

fetched live from OpenAlex

The warm sheet cylindrical deep drawing experiment of aluminum alloy was carried out and macro-mechanical properties and microstructure evolution of hydro-formed cups with different cooling medium were analyzed, which aimed to investigate the effects of different types of cooling on mechanical properties and microstructure of cylindrical cups hydro-formed by warm Hydro-mechanical Deep Drawing (HDD). Results show that, under the condition of warm hydroforming, the mechanical properties such as yield stress and ultimate strength were influenced very little by air or water cooling. Grain coarsening of these hydro-formed cups can be inhibited to a certain extent with subsequent rapid water cooling. Moreover, it shows that the processing with warm sheet hydroforming and subsequent rapid cooling of 7075-O aluminum alloy has a positive significance in maintaining the stability of macro mechanical properties and inhibiting the degradation of the microstructure of materials.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.029
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.030
GPT teacher head0.239
Teacher spread0.209 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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