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Record W2315035116 · doi:10.2495/cmem110521

Simulation of intergranular crack nucleation and evolution in polycrystal metals on mesoscale

2011· article· en· W2315035116 on OpenAlexafffund
Guicai Shi, Guillaume Renaud

Bibliographic record

VenueWIT transactions on modelling and simulation · 2011
Typearticle
Languageen
FieldEngineering
TopicFatigue and fracture mechanics
Canadian institutionsNational Research Council Canada
FundersMinistère de la Défense Nationale
KeywordsNucleationGrain boundaryIntergranular corrosionMesoscale meteorologyMaterials scienceIntergranular fractureFinite element methodGrain boundary strengtheningFracture mechanicsMechanicsMetallurgyStructural engineeringComposite materialGeologyMicrostructureThermodynamicsEngineeringPhysics

Abstract

fetched live from OpenAlex

This paper presents research on the development of a simulation method for the study of the mechanisms of intergranular crack nucleation and propagation in polycrystal metals on the mesoscale. Microstructural geometry models were built randomly using Voronoi techniques. Based on these grain structure geometry models, two-dimensional grain structure finite element models were created using a Patran Command Language (PCL) program. Techniques for the implementation of the cohesive elements between grain boundaries were developed in PCL for the generation of two-dimensional cohesive models. Simulations on intergranular crack nucleation and evolution along grain boundaries using two-dimensional finite element cohesive models were carried out on the mesoscale level. Several aspects that affect the crack nucleation and propagation were studied, which included random grain geometries, grain boundary misorientations, grain boundary peak strength, grain boundary fracture energy, grain properties, and grain plasticity. The simulations demonstrated that the cohesive model is a useful and efficient modeling tool for the study of the intergranular crack nucleation and evolution on the mesoscale level. The simulation results showed that the factors studied have large impacts on intergranular crack nucleation and evolution based on the current model capabilities and conditions.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.608
Threshold uncertainty score0.506

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.026
GPT teacher head0.220
Teacher spread0.194 · 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 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

Citations0
Published2011
Admission routes2
Has abstractyes

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