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Record W4210497850 · doi:10.1016/j.jmrt.2022.01.088

Effect of ECAP die angle on the strain homogeneity, microstructural evolution, crystallographic texture and mechanical properties of pure magnesium: numerical simulation and experimental approach

2022· article· en· W4210497850 on OpenAlexaff
A. I. Alateyah, Mohamed M. Z. Ahmed, Majed O. Alawad, Sally Elkatatny, Yasser Zedan, Ahmed Nassef, Waleed H. El-Garaihy

Bibliographic record

VenueJournal of Materials Research and Technology · 2022
Typearticle
Languageen
FieldMaterials Science
TopicMagnesium Alloys: Properties and Applications
Canadian institutionsÉcole de Technologie Supérieure
FundersDeanship of Scientific Research, King Saud UniversityQassim University
KeywordsMaterials scienceElectron backscatter diffractionDie (integrated circuit)Indentation hardnessTexture (cosmology)MetallurgySevere plastic deformationUltimate tensile strengthGrain sizeMicrostructureSlip (aerodynamics)Composite materialCrystallography

Abstract

fetched live from OpenAlex

Billets of pure Mg were processed using two ECAP dies with internal channel angle of 90° and 120° for 4-passes of route Bc at 225 °C. Finite element analysis was used to investigate the deformation behavior of Mg billets. Electron back-scatter diffraction was utilized to analyze the microstructural evolution and the crystallographic texture of the ECAPed billets. Vicker's microhardness and the tensile properties were studied. The finite element simulations showed that the 90°-die revealed a relative more homogenous distribution of the plastic strain compared with the 120°-die. From EBSD analysis, 1-pass condition of the 90°-die showed a bimodal structure that consisted of newly formed fine grains and heavily distorted large ones, whereas 120°-die counterpart revealed fewer areas with fine-grained structure. Accumulating the plastic strain up to 4-passes in the 90°-die and 120°-die resulted in significant refining of 0.88 μm and 1.89 μm, respectively compared to the as-annealed counterpart of 6.34 μm. The texture after 1-Pass and 2-Passes showed weakening in its intensity, which resembles the B fiber texture of ideal orientation {0 0 0 1} . Increasing the number of ECAP passes to 4-passes resulted in a significant strong texture with more than 26 times random with the intense {0001} poles. This was attributed to the grain refining that occurred after 1-Pass and 2-Passes, which allowed the activation of more slip systems upon the 4-Passes. On the other hand, ECAP processing resulted in a significant increase in the tensile strength, hardness, and ductility.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0020.000

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 head0.027
GPT teacher head0.293
Teacher spread0.266 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations42
Published2022
Admission routes1
Has abstractyes

Explore more

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