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Record W4280604518 · doi:10.1142/s1758825122500417

An Improved Mechanism-Based Strain Gradient Plasticity Model and Its Application to Size Effect Under Complex Loading

2022· article· en· W4280604518 on OpenAlexafffund
Leilei Zhao, Kecheng Zhou, Ding Tang, Huamiao Wang, Peidong Wu, Dayong Li, Yinghong Peng

Bibliographic record

VenueInternational Journal of Applied Mechanics · 2022
Typearticle
Languageen
FieldMaterials Science
TopicNonlocal and gradient elasticity in micro/nano structures
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMicroscale chemistryGrain sizeFinite element methodMaterials sciencePlasticityTorsion (gastropod)Work (physics)Structural engineeringComposite materialMechanicsMechanical engineeringMathematicsEngineeringPhysics

Abstract

fetched live from OpenAlex

The ingredient devices tend to be designed and fabricated with microscale, high accuracy, and complex geometry and are subjected to complex loading. Many experiments have proved that the size effect plays a significant role in designing and manufacturing an engineering component. This size effect is largely attributed to the grain size and the strain gradient. While the grain size effect was omitted in conventional strain gradient theories, an extended model that considers both effects of grain size and strain gradient has been proposed in the current work (denoted as GMSG). The proposed GMSG model has been implemented into the finite element method (denoted as GMSG-FEM) to investigate the size effect of copper wires under complex working conditions. The simulation results show that the hollow structure can improve the bearing capacity of the micro-wires under torsion. Among micro-wires with different cross-sections, the bearing capacity of the micro-wire with a circular section is the largest, followed by those with square and triangle sections. Complex loading also has an important influence on stress distribution. Based on the current study, it can be envisaged that the GMSG-FEM could be a useful tool in engineering applications where the size effect has to be considered.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.751

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.011
GPT teacher head0.258
Teacher spread0.246 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueInternational Journal of Applied MechanicsSame topicNonlocal and gradient elasticity in micro/nano structuresFrench-language works237,207