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Record W3111390158 · doi:10.1002/pen.25616

Fourier transform fatigue analysis of the stress in tension/tension of HDPE and PA6

2020· article· en· W3111390158 on OpenAlexaff
Valerian Hirschberg, Denis Rodrigue

Bibliographic record

VenuePolymer Engineering and Science · 2020
Typearticle
Languageen
FieldEngineering
TopicMechanical Behavior of Composites
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMaterials scienceTension (geology)ViscoelasticityComposite materialHigh-density polyethyleneFourier transformAmplitudeNonlinear systemStress (linguistics)BucklingHarmonicsElongationCompression (physics)PolyethyleneStructural engineeringUltimate tensile strengthMathematical analysisMathematicsPhysicsOptics

Abstract

fetched live from OpenAlex

Abstract Mechanical fatigue under strain controlled tension/tension (T/T) of rectangular un‐notched and notched specimens of high density polyethylene and polyamide 6 was performed. Under large amplitude oscillatory elongation, the stress response is nonlinear asymmetric due to a different stress response during loading and unloading and was analyzed via discrete Fourier transform. Dynamic strain ( ε 0 ) sweep tests revealed odd ( I 3/1 α ε 0 2 ) and even ( I 2/1 α ε 0 1 ) harmonics in the stress, well described by the Neo‐Hooke's law. Before crack onset for the Nc specimens, the storage and loss moduli and I 2/1 are constant, but I 3/1 increases with fatigue. The first derivative of I 3/1 ( dI 3/1 /dN ) and the cumulative nonlinearity Q f parameter (integral of I 3/1 / ε 0 2 ) were found to be strong criteria predicting fatigue. To break the unnotched specimens in the low and high cycle fatigue regime, large strain amplitudes were applied, resulting for both materials in initial plastic deformation followed by buckling when a critical compression force is exceeded. This results in a different time evolution of the linear and nonlinear parameters, especially as a minimum in the I 2/1 curve. Finally, a model is proposed to describe the nonlinear viscoelastic specimen response under T/T and the effect of buckling.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.626
Threshold uncertainty score0.224

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 integrity0.0000.000
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 head0.016
GPT teacher head0.220
Teacher spread0.203 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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