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Record W1965309282 · doi:10.1115/imece2005-82527

Non Isothermal Hybrid Approach Using the Perfect Gas Law and Explicit Dynamic Finite Element Method for Modeling of Thermoforming and Blow Molding Processes

2005· article· en· W1965309282 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Mechanics · 2005
Typearticle
Languageen
FieldChemical Engineering
TopicRheology and Fluid Dynamics Studies
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsThermoformingFinite element methodMaterials scienceIsotropyCompressibilityIsothermal processViscoelasticityMechanicsMechanical engineeringMolding (decorative)Composite materialThermodynamicsEngineeringStructural engineeringPhysics

Abstract

fetched live from OpenAlex

Thermoforming of cut sheets is extensively used in the industry for various commercial applications. In this process, the sheet is heated to a softened state and subsequently deformed into the mould due to an applied pressure, a vacuum, a moving plug or a combination of these media. The thermoforming-process market is expanding to complex geometries and to a list of potential materials. In this work, I use a no isothermal hybrid approach which combines the dynamic finite element method and the thermodynamic law of perfect gases to study the effect of the temperature of the air flow on the blowing of a thin, isotropic and incompressible thermoplastic membrane. The viscoelastic behaviour of the K-BKZ model is considered. The Lagrangian formulation together with the assumption of the membrane shell theory is used. The numerical validation is performed by comparing the obtained results with the theoretical results for the HDPE grade. Moreover, the effect of the temperature on the thickness and stresses distribution is presented.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.684
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.247
Teacher spread0.233 · 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