MétaCan
Menu
Back to cohort

A Stress-State Related Void Coalescence Criterion and its Validation

2010· article· en· W1965365834 on OpenAlexaff
Zengtao Chen, Rahul Datta

Bibliographic record

VenueApplied Mechanics and Materials · 2010
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsCoalescence (physics)Void (composites)Materials scienceUltimate tensile strengthStructural engineeringMechanicsVolume fractionComposite materialEngineeringPhysics

Abstract

fetched live from OpenAlex

We propose a new critical void volume fraction (fc) criterion that identifies the onset of void coalescence based on the stress state of the material as compared to the definition of the phenomenological criterion by Tvergaard and Needleman [1], where void coalescence is predicted based merely on a constant value for critical void volume fraction. The new fc criterion is obtained using the finite element analysis of the unit cell model of clustered voids. Validation of this new criterion is done by implementing the new coalescence criterion into the Gurson-Tvergaard-Needleman (GTN) [1-3] model and simulating the ductile fracture experiment of a series of angularly notched sheet samples of dual phase (DP), advanced high strength steels (AHSS). A methodology has been devised to construct a stress triaxiality-based void coalescence criterion. Validation of the methodology has been performed using tensile tests of angularly notched samples of DP490 AHSS. Experimental data is compared with FE simulations in order to verify the dependency of void coalescence on stress triaxiality.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.075
Threshold uncertainty score0.448

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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueApplied Mechanics and MaterialsSame topicMetal Forming Simulation TechniquesFrench-language works237,207