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Record W2028726382 · doi:10.1002/pen.10061

Deformation behavior of an epoxy resin subject to multiaxial loadings. Part II: Constitutive modeling and predictions

2003· article· en· W2028726382 on OpenAlexaff
Zihui Xia, Yafei Hu, Fernand Ellyin

Bibliographic record

VenuePolymer Engineering and Science · 2003
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMaterials scienceEpoxyViscoelasticityConstitutive equationNonlinear systemComposite materialDeformation (meteorology)ModulusStructural engineeringFinite element methodPhysics

Abstract

fetched live from OpenAlex

Abstract Based on the experimental data presented in Part I, a nonlinear viscoelastic constitutive model, in differential form, is presented here. A distinctive feature of this model is the inclusion of a criterion to delineate loading and unloading in multiaxial stress states, and different moduli for loading and unloading behaviors. In addition, the model contains only five material constants and one modulus function, which can be calibrated in accordance with a well‐defined procedure. A comparison with the experimental data shows that the current differential model is capable of predicting the nonlinear viscoelastic behavior of the epoxy polymer qualitatively and quantitatively, including both the loading and unloading behavior. The predictions of an integral form of constitutive model are also included for comparative purposes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0030.001

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 head0.014
GPT teacher head0.229
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations50
Published2003
Admission routes1
Has abstractyes

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