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Assessment of Newly Developed Ductile Fracture Criteria for Lightweight Metals

2019· article· en· W2918130651 on OpenAlexaff
Ru Gang Chai, Yanshan Lou, Jeong Whan Yoon

Bibliographic record

VenueKey engineering materials · 2019
Typearticle
Languageen
FieldEngineering
TopicMetal Forming Simulation Techniques
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsLodeMaterials scienceFracture (geology)Structural engineeringCoupling (piping)Stress (linguistics)Shear (geology)Composite materialForensic engineeringMetallurgyEngineering

Abstract

fetched live from OpenAlex

This paper assesses various newly developed ductile fracture criteria including modified Mohr-Coulomb (MMC), DF2012, DF2014, DF2016, Hu-Chen and Mu-Zang, which were all proposed in the last decade. The AA2024-T351 is used for the assessment by comparing the predicted fracture limits to the experimental results both in strain and stress spaces. Fracture loci are also constructed by these criteria to evaluate their characteristics. The evaluation demonstrates that the Lode parameter and stress triaxiality should be properly coupled for reasonable modeling of ductile fracture in wide loading conditions. This study also shows that the coupling of the Lode parameter can also be realized by introducing the effect of the largest shear stress in fracture criteria.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.033
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.013
GPT teacher head0.278
Teacher spread0.265 · 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.

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

Citations3
Published2019
Admission routes1
Has abstractyes

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