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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Materials Map under construction

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)

  • 2020Multiscale image-based modelling of damage and fracture in carbon fibre reinforced polymer composites30citations
  • 2016Generation of Micro-scale Finite Element Models from Synchrotron X-ray CT Images for Multidirectional Carbon Fibre Reinforced Composites95citations

Places of action

Chart of shared publication
Soutis, Costas
2 / 356 shared
Withers, Pj
2 / 103 shared
Wang, Yong
2 / 21 shared
Zhang, James
1 / 1 shared
Parson, A.
1 / 1 shared
Rau, Christopher
1 / 1 shared
Wang, Zhenjun
1 / 1 shared
Chart of publication period
2020
2016

Co-Authors (by relevance)

  • Soutis, Costas
  • Withers, Pj
  • Wang, Yong
  • Zhang, James
  • Parson, A.
  • Rau, Christopher
  • Wang, Zhenjun
OrganizationsLocationPeople

article

Generation of Micro-scale Finite Element Models from Synchrotron X-ray CT Images for Multidirectional Carbon Fibre Reinforced Composites

  • Parson, A.
  • Rau, Christopher
  • Soutis, Costas
  • Withers, Pj
  • Wang, Yong
  • Wang, Zhenjun
  • Sencu, Razvan
Abstract

This paper develops a new fibre tracking algorithm to efficiently locate fibre centrelines (skeletons), from X-ray Computed Tomography (X-ray CT) images of carbon fibre reinforced polymer (CFRP), which are then used to generate micro-scale finite element models. Three-dimensional images with 330nm voxel resolution of multidirectional [+45/90/-45/0] CFRP specimens were obtained by fast synchrotron X-ray CT scanning. Conventional image processing techniques, such as a combination of filters, delineation of plies, binarisation of images, and fibre identification by local maxima and ultimate eroding points, were tried first but found insufficient to produce continuous fibre centrelines for segmentation, especially in regions with highly congested fibres. The new algorithm uses a global overlapping stack filtering step followed by a local fibre tracking step. Both steps are based on the Bayesian inference theory. The new algorithm is found capable of efficiently define fibre centrelines for the generation of micro-scale finite element models with high fidelity.

Topics
  • impedance spectroscopy
  • polymer
  • Carbon
  • theory
  • tomography
  • composite