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Record W2022665067 · doi:10.1002/cjce.5450830316

Analyse Expérimentale et Numérique du Comportement de Membranes Thermoplastiques en ABS et en HIPS dans le Procédé de Thermoformage

2008· article· fr· W2022665067 on OpenAlexaffvenue
Fouad Erchiqui, A. Derdouri

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2008
Typearticle
Languagefr
FieldEngineering
TopicElasticity and Material Modeling
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsHumanitiesPhysicsHyperelastic materialPhilosophyFinite element methodThermodynamics

Abstract

Dans cet article nous nous intéresserons, d'une part à la caractérisation biaxiale, en soufflage libre du comportement des membranes thermoplastiques circulaires en ABS et en HIPS et, d'autre part à la simulation numérique de la mise en forme d'une pièce creuse en ABS et en HIPS. Les modèles de comportement hyperélastique de Mooney-Rivlin et d'Ogden sont considérés. Dans un premier temps nous utilisons la méthode des différences finies à pas variables pour la résolution du problème d'équilibre de la membrane et un algorithme modifié de Levenberg-Marquardt pour minimiser la différence entre la pression calculée et celle mesurée. Ceci permet l'identification des constantes matérielles incorporées dans les modèles utilisés. Pour la modélisation numérique par la méthode dynamique des éléments finis, nous considérons une formulation lagrangienne, l'hypothèse de la théorie des membranes et une charge en pression, découlant de la loi des gaz parfaits, pour étudier l'influence des lois de comportements sur la distribution finale des épaisseurs et des contraintes dans une pièce thermoformée en ABS et en HIPS. In this work, we are interested, on the one hand in the characterization of circular polymeric ABS and HIPS membrane under biaxial deformation using the bubble inflation technique, on the other hand in modelling and numerical simulation of the thermoforming of ABS and HIPS materials using the dynamic finite element method. Hyperelastic models (Mooney-Rivlin, Ogden) are considered. First, the governing equations for the inflation of a flat circular membrane are solved using a variable-step-size-finite difference method and a modified Levenberg-Marquardt algorithm to minimize the difference between the calculated and measured inflation pressure. This will determine the material constants embedded within the models used. For numerical simulation, the lagrangian formulation together with the assumption of the membrane theory is used. Moreover, the influence of the hyperalastic model on the thickness and on the stress distribution in the thermoforming sheet are analysed for ABS and HIPS materials.

Stored with the screening record, where it is evidence for the labels above.

How this classification was reachedexpand

The three-model screen

all 5,600 screened works →

All three models called this out of scope.

stratum: french · design weight: 1554.47 (the sample is stratified; any rate computed without the weight is wrong)
Claude Opus 4.8OUT
genre: empirical
about Canada: no
confidence: high

Experimental and finite element analysis of thermoplastic membranes in thermoforming; the object is material behavior.

GPT-5.6 (high)OUT
genre: empirical
about Canada: no
confidence: high

The study models the thermoforming behavior of plastic membranes, not research practice.

Grok 4.5OUT
genre: empirical
about Canada: no
confidence: high

Engineering characterization of thermoplastic membrane mechanical behaviour; domain research.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.000

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.009
GPT teacher head0.199
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 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

Citations2
Published2008
Admission routes2
Has abstractyes

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