Materials Map

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2023Determination of fiber orientation model parameters for injection molding simulations via automated metamodel optimization2citations

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Chang, Li-Yang
1 / 2 shared
Stelzer, Philipp S.
1 / 4 shared
Major, Zoltán
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Rienesl, Konrad
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Zulueta, Kepa
1 / 4 shared
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2023

Co-Authors (by relevance)

  • Chang, Li-Yang
  • Stelzer, Philipp S.
  • Major, Zoltán
  • Rienesl, Konrad
  • Zulueta, Kepa
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article

Determination of fiber orientation model parameters for injection molding simulations via automated metamodel optimization

  • Chang, Li-Yang
  • Stelzer, Philipp S.
  • Hsu, Chih-Chung
  • Major, Zoltán
  • Rienesl, Konrad
  • Zulueta, Kepa
Abstract

<jats:p>Injection molded short fiber reinforced components reveal a sound light weight potential with moderate costs and thus are widely used in many demanding engineering applications. The accurate determination of the fiber orientation (FO) is essential for predicting the overall mechanical behavior of discontinuous (short or long, with varying aspect ratio) fiber reinforced composites. The simulation of the FO requires a proper modeling of the hydrodynamics, the closure transformation of the FO tensor and optionally the application of specific correction functions. The determination of parameters for the fiber orientation models commonly used in injection molding simulations is a challenging task because they cannot be determined directly in experiments. Hence, a novel way is shown in our paper to derive these parameters faster, more efficiently and accurately by the usage of an automated metamodel optimization. For this, injection molding simulations were performed iteratively by an optimization program until a minimal deviation error of the simulated parameters was reached. The optimization was performed based on proper computed tomography FO data of selected regions of interest. The new approach was tested for a rotationally symmetric Venturi tube geometry made from short glass fiber reinforced polyamide (PA-GF). The fiber orientation distribution models chosen were the iARD-RPR equation with 3 parameters and the novel anisotropic IISO equation with 5 parameters. It was shown that the optimization method is feasible for the calibration of fiber orientation models. Furthermore, the IISO equation with its 2 additional parameters allowed a more accurate prediction of the fiber orientation distribution, especially of the core layer of the injection molded part.</jats:p>

Topics
  • impedance spectroscopy
  • experiment
  • simulation
  • tomography
  • glass
  • glass
  • anisotropic
  • composite
  • injection molding