Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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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)

  • 2021FFT‐based homogenization using a reduced set of frequencies and a clustered microstructurecitations

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Gierden, Christian
1 / 2 shared
Waimann, Johanna
1 / 4 shared
Svendsen, Bob
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Reese, Stefanie
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2021

Co-Authors (by relevance)

  • Gierden, Christian
  • Waimann, Johanna
  • Svendsen, Bob
  • Reese, Stefanie
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article

FFT‐based homogenization using a reduced set of frequencies and a clustered microstructure

  • Gierden, Christian
  • Waimann, Johanna
  • Svendsen, Bob
  • Schmidt, Annika
  • Reese, Stefanie
Abstract

<jats:title>Abstract</jats:title><jats:p>To capture the material behavior of composite microstructures, Moulinec and Suquet [5] proposed a homogenization scheme making use of fast Fourier transforms (FFT) and fixed‐point iterations. To reduce the computational effort of this spectral method, Kochmann et al. [3] introduced a model order reduction technique, which is based on using a fixed reduced set of frequencies for the computations in Fourier space. Within the current work, we improved the accuracy of the approach by use of a geometrically adapted set of frequencies, see [1]. Since the constitutive relations are still evaluated in real space, the technique is most beneficial for a linear material behavior. Considering nonlinear material behavior, most of the computing time is related to solving the constitutive relations. Therefore, the total speed‐up is lower. To achieve a further reduction of the computational effort for a nonlinear material behavior, the earlier proposed model order reduction technique is coupled with a clustering analysis [4]. The whole microstructure is thus divided into clusters, which show a similar material behavior. Within these clusters, the micromechanical fields are assumed to be constant which leads to a significant reduction of computational costs compared to the highly resolved solution.</jats:p>

Topics
  • impedance spectroscopy
  • cluster
  • composite
  • homogenization
  • clustering