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Record W7024583954

Simulation and numerical modeling of polymers forming processes using NRC’s BlowView software package

2018· other· en· W7024583954 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2018
Typeother
Languageen
FieldPhysics and Astronomy
TopicPlanetary Science and Exploration
Canadian institutionsnot available
Fundersnot available
KeywordsThermoformingBlow moldingExtrusionFinite element methodMolding (decorative)Forming processesSoftwareDie swellDie (integrated circuit)
DOInot available

Abstract

fetched live from OpenAlex

BlowView is a 2.5D finite element based simulation software, developed at NRC and dedicated to simulate conventional extrusion blow molding, twin-sheet extrusion blow molding, suction blow molding, stretch blow molding and thermoforming processes. This versatile engineering simulation software is highly automated, flexible and user-friendly, yet allows users in-depth analysis capabilities for a wide range of materials, and includes warpage, optimization and permeability applications. Conventional and twin-sheet extrusion blow molding processes are extensively used in manufacturing automotive parts. These processes consist of three main phases: parison/sheet formation, inflation and part cooling and solidification. The parison/sheet formation is the most critical stage, as the final dimensions and mechanical performance of the part are directly related to the initial extrudate shape, which often requires the use of advanced die shaping technologies such as: VWDS, PWDS, SFDR, DSM, and/or a combination of all four. These complex extrusion technologies are all accessible in the BlowView software, and can be simultaneously synchronized and optimized with the machine programming points. An illustration of the optimization methodology, and the gain in terms of part weight reduction, will be presented for an industrial case study. For stretch blow molding & thermoforming applications, the heating stage is of primary importance. The software’s capability to simulate the complex heating stages for thin gauge roll-fed plastic sheets and plastic preforms, including radiation and preferential heating, as well as the inflation/vacuum stages will be highlighted and discussed. A robust and reliable contact algorithm has been implemented in order to manage the sheet/plug, preform/rod and part/mold contact. Finally, the latest advances in 3D forming will be presented on various blow molded parts to predict the induced welding deformation in the pinch zones, which are subjected to high strain ratios.

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)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.027
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0270.004

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 head0.032
GPT teacher head0.271
Teacher spread0.239 · 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
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

Citations0
Published2018
Admission routes1
Has abstractyes

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