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Record W2329547420 · doi:10.1115/imece2010-39229

A Coupled-Constitutive Model for Ductile Fracture: Void Nucleation to Coalescence

2010· article· en· W2329547420 on OpenAlexafffund
Cliff Butcher, Zengtao Chen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceHomogenization (climate)NucleationCoalescence (physics)Constitutive equationVoid (composites)Composite materialVolume fractionPlasticityStress spaceMechanicsStructural engineeringFinite element methodThermodynamicsPhysicsEngineering

Abstract

fetched live from OpenAlex

A novel framework and integration scheme has been developed to implement a secant-based homogenization theory for particle-reinforced plasticity into an existing damage-based constitutive model, the well known Gurson-Tvergaard (GT) model. In this approach, the material is treated as a three-phase composite composed of voids and particles embedded in a ductile matrix. Two successive homogenization theories (damage- and particle-based) are then applied to determine the macro-mechanical response of the material as well as the average stress state within the constituents as a function of the particle shape, composition, and volume fraction. By identifying the stress state within the particles and the matrix, void nucleation can be accurately represented and the void growth and coalescence models are improved through knowledge of the stress state within the matrix. The performance of the coupled model is evaluated using a model aluminum alloy. A parametric study is performed to elucidate the influence of the second-phase particles and their shape on damage evolution and ductile fracture.

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 score0.719
Threshold uncertainty score0.374

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 head0.012
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 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
Published2010
Admission routes2
Has abstractyes

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