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Record W3047639943 · doi:10.14447/jnmes.v23i1.a09

Cluster Analysis of Lost Foam Casted Al-Zn-Mg-Cu Alloy with K–Mean Algorithm

2020· article· en· W3047639943 on OpenAlexvenueno aff
Kathirvel Thiyagarajan, M. Jayaraman, V. Vijayan, R. Ramkumar

Bibliographic record

VenueJournal of New Materials for Electrochemical Systems · 2020
Typearticle
Languageen
FieldEngineering
TopicMetallurgy and Material Forming
Canadian institutionsnot available
Fundersnot available
KeywordsCluster (spacecraft)AlloyMaterials scienceComputer scienceAlgorithmMetallurgyOperating system

Abstract

fetched live from OpenAlex

AA7075 is super-strength aluminum alloys to under the Al-Zn-Mg-Cu group and natural aging characteristic. The increasing need for metal matrix composites to be cost-effective and at the same time have an optimum level of performance. The contemporary market of industryoriented software for structural strength analysis impresses very much by its versatility. The effect of conventional casting and lost foam casting of AA7075 materials mechanical properties, cluster analysis, surface roughness, and FEA analysis has been studied. The finite element analysis models were generated in ANSYS. The surface roughness of aluminum alloy 7075 made by conventional casting is lower than the by lost foam casting. From this SEM images of the aluminum alloy 7075 part made of foam casting posse's better bonding of aluminum material than conventional casting. The dense molecular bonding of aluminum in foam casting may improve the mechanical properties.

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 score0.053
Threshold uncertainty score0.797

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 science0.0000.000
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 head0.013
GPT teacher head0.226
Teacher spread0.213 · 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
Published2020
Admission routes1
Has abstractyes

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