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Rate-Dependent Material Parameters of the Combined Isotropic/Kinematic Hardening Model for the TRIP980 Steel Sheet

2016· article· en· W2566447588 on OpenAlexaff
Geun Su Joo, Hoon Huh

Bibliographic record

VenueKey engineering materials · 2016
Typearticle
Languageen
FieldMaterials Science
TopicHigh-Velocity Impact and Material Behavior
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsMaterials scienceSheet metalHardening (computing)Strain hardening exponentIsotropyComposite materialStrain rateConstitutive equationCompression (physics)Tension (geology)TolaStructural engineeringFinite element methodEngineering

Abstract

fetched live from OpenAlex

This paper is concerned with rate-dependent hardening behaviors of the TRIP980 steel sheet. In sheet metal forming, sheet metals experiences complicated loading at various strain rates. In order to predict deformed shape in sheet metal forming, accurate material properties and an appropriate constitutive model in numerical simulation are important to consider reverse loading and various strain rates simultaneously.This paper deals with rate-dependent material parameters of the isotropic/kinematic hardening model. Tension/compression tests of the TRIP980 steel sheet are performed with a newly developed experimental technique at various strain rates ranging from 0.001 to 100 s − 1 . Tension/compression hardening curves of the TRIP980 steel sheet are approximated by the Chun et al model at each strain rate condition respectively. From acquired material parameters, rate dependencies of tension/compression hardening behaviors are investigated.

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)0.001
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 score0.018
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.022
GPT teacher head0.234
Teacher spread0.212 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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