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Prediction of Fiber Orientation Distribution in Injection Molded Parts Using Moldex3D Simulation

Identifieur interne : 000045 ( Main/Exploration ); précédent : 000044; suivant : 000046

Prediction of Fiber Orientation Distribution in Injection Molded Parts Using Moldex3D Simulation

Auteurs : Peter H. Foss [États-Unis] ; Huan-Chang Tseng [Taïwan] ; John Snawerdt [Taïwan] ; Yuan-Jung Chang [Taïwan] ; Wen-Hsien Yang [Taïwan] ; Chia-Hsiang Hsu [Taïwan]

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Mots-clés :

Abstract

In the automotive industry, glass-filled thermoplastics are used in air intake manifolds, radiator tanks, and many other parts. However, widespread application of glass-filled thermoplastic materials has been limited in many cases by the inability to accurately predict performance and durability. Since a more accurate fiber orientation prediction will lead to more accurate local mechanical property predictions, this work investigated a recently proposed mathematic model of fiber suspension rheology, which considers the anisotropic fiber diffusion and fiber-matrix interaction from a microscopic viewpoint. The new model proved able to predict many details of the fiber orientation distribution and could be applied advantageously as part of the product and manufacturing development processes.


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Le document en format XML

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<term>Durability</term>
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<div type="abstract" xml:lang="en">In the automotive industry, glass-filled thermoplastics are used in air intake manifolds, radiator tanks, and many other parts. However, widespread application of glass-filled thermoplastic materials has been limited in many cases by the inability to accurately predict performance and durability. Since a more accurate fiber orientation prediction will lead to more accurate local mechanical property predictions, this work investigated a recently proposed mathematic model of fiber suspension rheology, which considers the anisotropic fiber diffusion and fiber-matrix interaction from a microscopic viewpoint. The new model proved able to predict many details of the fiber orientation distribution and could be applied advantageously as part of the product and manufacturing development processes.</div>
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