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Record W3084229775 · doi:10.1139/tcsme-2020-0071

A variable-order viscoelastic constitutive model under constant strain rate

2020· article· en· W3084229775 on OpenAlexvenueno aff
Yao Wang, Dagang Sun, Zhanlong Li, Yuan Qin, Bao Sun

Bibliographic record

VenueTransactions of the Canadian Society for Mechanical Engineering · 2020
Typearticle
Languageen
FieldMaterials Science
TopicNonlocal and gradient elasticity in micro/nano structures
Canadian institutionsnot available
Fundersnot available
KeywordsViscoelasticityConstitutive equationConstant (computer programming)OgdenCauchy elastic materialElasticity (physics)Nonlinear systemMaterials scienceMechanicsThermodynamicsPhysicsFinite element methodComposite materialComputer science

Abstract

fetched live from OpenAlex

Traditional viscoelastic constitutive models encounter the problems of massive parameters and ambiguous physical meanings. A new concept variable-order viscoelastic constitutive (called VOVC) model is put forward based on the constant fractional-order constitutive model and viscoelastic theory. The determination methods of the two parameters in the VOVC model, including the material coefficient and viscoelastic coefficient, are discussed both in the tensile and resilient processes. Comparisons are made between the VOVC model and traditional constitutive models, i.e., the constant fractional-order Kelvin–Voigt (CFKV) model, the Zhu–Wang–Tang nonlinear thermo-viscoelastic constitutive (ZWT) model, and the Ogden nonlinear hyper-elastic (Ogden) model. The results show that the VOVC model with the constant material coefficient and the variable viscoelastic coefficient predicts the whole evolution of the constitutive behavior of the viscoelastic material under the constant strain rate more precisely. The constant material coefficient in the VOVC model means the stiffness of the viscoelastic material. The variable viscoelastic coefficient in the model means the distribution of the elasticity and viscosity. The proposed VOVC model contains a simpler structure, fewer parameters, clearer physical meanings, and higher precision.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.935
Threshold uncertainty score0.547

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 head0.015
GPT teacher head0.204
Teacher spread0.190 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueTransactions of the Canadian Society for Mechanical EngineeringSame topicNonlocal and gradient elasticity in micro/nano structuresFrench-language works237,207