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Record W4413773674 · doi:10.3390/inventions10050077

Open-Access Crystal Plasticity Finite Element Implementation in ANSYS for Dislocation-Induced Nanoindentation in Magnesium

2025· article· en· W4413773674 on OpenAlexafffund
Syed Taha Khursheed, Mina Imani, Yunhua Luo, Guo‐zhen Zhu

Bibliographic record

VenueInventions · 2025
Typearticle
Languageen
FieldEngineering
TopicMetal and Thin Film Mechanics
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanoindentationCrystal plasticityFinite element methodDislocationMagnesiumMaterials sciencePlasticityStructural engineeringMagnesium alloyMetallurgyComposite materialEngineering

Abstract

fetched live from OpenAlex

This study focuses on developing and implementing crystal plasticity finite element modeling (CPFEM) codes on the ANSYS platform. The code incorporates a plasticity constitutive law that describes the behaviors of basal, prismatic, and pyramidal slips in magnesium, and is validated against plane-strain compression experiments and simulations using established codes on the ABAQUS CAE platform. The validated CPFEM code is applied to simulate the dislocation-induced nanoindentation response of pure magnesium across different crystallographic orientations, allowing visualization of strain distributions associated with different slips. Consistent with experimental observations, basal slip is identified as the primary active slip, whereas prismatic and pyramidal slips show varying activities with respect to the direction of the indentation. Novelty arises from an ANSYS–native CPFEM implementation that is cross-validated against published ABAQUS simulations and an experiment under a single, consistent constitutive set. This framework enables orientation-resolved mapping of slip system activity and subsurface strain fields under spherical nanoindentation, providing analysis capability seldom available in prior ANSYS–based studies.

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)0.001
metaresearch head score (Gemma)0.002
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: Simulation or modeling
GenreCandidate signal: Software · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.004

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 head0.368
Teacher spread0.317 · 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
GenreSoftware

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

Citations1
Published2025
Admission routes2
Has abstractyes

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