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Microvoid Damage Model with Material Dilation for Ductile Fracture

2006· article· en· W2127407903 on OpenAlex
Heng-Aik A. Khoo, T. M. Hrudey, Jianwei Cheng

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Engineering Mechanics · 2006
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsCarleton UniversityUniversity of Alberta
Fundersnot available
KeywordsDilation (metric space)Materials scienceConstitutive equationStructural engineeringMonotonic functionIsotropyTest dataMechanicsFracture (geology)Tension (geology)Limit loadComposite materialCompression (physics)Finite element methodEngineeringMathematicsPhysicsGeometryMathematical analysis

Abstract

fetched live from OpenAlex

A constitutive model that incorporates material dilation and the concept of continuum damage mechanics is developed to predict ductile fracture of steel under monotonic quasi-static loading due to microvoids. In this model, damage is assumed to be isotropic and is a function of the state of stress and the plastic strain increment. Material dilation is assumed to vary with the state of damage. Fracture occurs when the damage limit is reached. Parameters for the model are calibrated using data obtained from tension coupon tests. The constitutive model and the process used to determine its parameters are described. Analyses have been carried out to illustrate the effect of incorporating material dilation. The model is able to closely predict the load versus deformation curve of the tension test. Additional test data required for verifying the model have also been outlined.

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.

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 score0.640
Threshold uncertainty score0.512

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 head0.004
GPT teacher head0.187
Teacher spread0.182 · 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