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Record W4410776057 · doi:10.1080/13640461.2025.2495509

Study on mechanical, tribological and fracture behaviour of n-Al <sub>2</sub> O <sub>3</sub> reinforced Al7075 composites using Taguchi technique

2025· article· en· W4410776057 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

VenueInternational Journal of Cast Metals Research · 2025
Typearticle
Languageen
FieldEngineering
TopicAluminum Alloys Composites Properties
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsMaterials scienceTaguchi methodsTribologyComposite materialFracture (geology)Metallurgy

Abstract

fetched live from OpenAlex

The work focuses on producing and investigating the mechanical, wear, and microstructure of Al7075 alloy nano-sized Alumina Oxide (n-Al2O3) particles with wt. % of 1, 2, and 3. Metallurgical methods have been used to create Al7075/n-Al2O3 composites. The microstructure showed that n-Al2O3 was distributed uniformly. Tests were done on a tribometer that was fastened to a hard steel disk to examine wear loss. In response to the surface approach, the wear parameters were optimised using the Taguchi L27 orthogonal array. The obtained result indicates that, hardness and tensile strength increase by 40% & 31% respectively. It is due to the increase of wt. % hard ceramic nano particulates. The Analysis of Variance (ANOVA) result indicates that, wt. % of n-Al2O3 is the most significant (61.02 %). With 95% reliability, the constructed model successfully predicted the wear rate, & ANOVA was used to corroborate the outcomes of all models.

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)0.002
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 score0.008
Threshold uncertainty score0.919

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.052
GPT teacher head0.354
Teacher spread0.302 · 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