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 (2/2 displayed)

  • 2023A virtual stylus method for non-destructive roughness profile measurement of additive manufactured lattice structures3citations
  • 2022A Comparison of Statistically Equivalent and Realistic Microstructural Representative Volume Elements for Crystal Plasticity Models15citations

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Downing, David
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Elambasseril, Joe
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Qian, Ma
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Rogers, Jason
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Tino, Rance
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Leary, Martin
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Brandt, Milan
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Sterjovski, Zoran
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Agius, Dylan
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Davids, William
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Chen, Hansheng
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Ringer, Simon P.
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Wang, Chun H.
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Schaffer, Graham
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Crawford, Bruce R.
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2023
2022

Co-Authors (by relevance)

  • Downing, David
  • Elambasseril, Joe
  • Qian, Ma
  • Rogers, Jason
  • Tino, Rance
  • Leary, Martin
  • Brandt, Milan
  • Sterjovski, Zoran
  • Agius, Dylan
  • Davids, William
  • Chen, Hansheng
  • Ringer, Simon P.
  • Wang, Chun H.
  • Schaffer, Graham
  • Crawford, Bruce R.
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article

A Comparison of Statistically Equivalent and Realistic Microstructural Representative Volume Elements for Crystal Plasticity Models

  • Sterjovski, Zoran
  • Wallbrink, Chris
  • Agius, Dylan
  • Davids, William
  • Chen, Hansheng
  • Ringer, Simon P.
  • Wang, Chun H.
  • Schaffer, Graham
  • Crawford, Bruce R.
Abstract

<jats:title>Abstract</jats:title><jats:p>Two methods used to construct a microstructural representative volume element (RVE) were evaluated for their accuracy when used in a crystal plasticity-based finite element (CP-FE) model. The RVE-based CP-FE model has been shown to accurately predict the complete tensile stress–strain response of a Ti–6Al–4V alloy manufactured by laser powder bed fusion. Each method utilized a different image-based technique to create a three-dimensional (3D) RVE from electron backscatter diffraction (EBSD) images. The first method, referred to as the realistic RVE (R-RVE), reconstructed a physical 3D microstructure of the alloy from a series of parallel EBSD images obtained using serial-sectioning (or slicing). The second method captures key information from three orthogonal EBSD images to create a statistically equivalent microstructural RVE (SERVE). Based on the R-RVEs and SERVEs, the CP-FE model was then used to predict the complete tensile stress–strain response of the alloy, including the post-necking damage progression. The accuracy of the predicted stress–strain responses using the R-RVEs and SERVEs was assessed, including the effects of each microstructure descriptor. The results show that the R-RVE and the SERVE offer comparable accuracy for the CP-FE purposes of this study.</jats:p>

Topics
  • microstructure
  • selective laser melting
  • plasticity
  • electron backscatter diffraction
  • crystal plasticity
  • sectioning