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Record W4319996748 · doi:10.5267/j.esm.2023.1.003

A micromechanical study on the correlation of the microstructure and failure mechanism of dual-phase steels under tension

2023· article· en· W4319996748 on OpenAlexvenueno aff
M.S. Mohsenzadeh

Bibliographic record

VenueEngineering Solid Mechanics · 2023
Typearticle
Languageen
FieldEngineering
TopicMicrostructure and Mechanical Properties of Steels
Canadian institutionsnot available
Fundersnot available
KeywordsMartensiteMaterials scienceVolume fractionComposite materialParticle (ecology)Fracture (geology)MicrostructureStress (linguistics)DislocationParticle sizeMetallurgyChemistry

Abstract

fetched live from OpenAlex

In this study, the influence of the volume fraction of the martensite phase as well as the size of the martensite particles on the mechanism of particle fracture in dual-phase steel were examined. A combined continuum/dislocation based approach was used in order to model the average stress in the martensite particles. It was found that the model predictions are in accordance with the experimental results. For the same volume fraction of the martensite particles, the model predicts an increase of the internal stress and the average stress in the martensite particles with increasing the particles size. Since the fracture strength of the martensite depends on its volume fraction, the particle size has no effect on the mechanism of particle fracture. Increasing the volume fraction of the martensite particles results in the enhancement of the internal stress in the martensite particles. However, it has a slight influence on the average stress in the particles. Nevertheless, because of decreasing the fracture strength of martensite with increasing its volume fraction, this parameter has a main role in the occurrence of the particle fracture mechanism.

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 score0.340
Threshold uncertainty score0.798

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.221
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
Published2023
Admission routes1
Has abstractyes

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