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 (3/3 displayed)

  • 2024Identification and characterization of damaged fiber-reinforced laminates in a Bayesian framework1citations
  • 2023Identification and characterization of damaged fiber-reinforced laminates in a Bayesian frameworkcitations
  • 2022Data fusion and non-destructive testing of damaged fiber-reinforced laminatescitations

Places of action

Chart of shared publication
Rodet, Thomas
3 / 3 shared
Lesselier, Dominique
3 / 22 shared
Chart of publication period
2024
2023
2022

Co-Authors (by relevance)

  • Rodet, Thomas
  • Lesselier, Dominique
OrganizationsLocationPeople

conferencepaper

Data fusion and non-destructive testing of damaged fiber-reinforced laminates

  • Rodet, Thomas
  • Lesselier, Dominique
  • Noël, Valentin
Abstract

International audience ; Efficient strategies for non-destructive testing of damaged composite laminates modeled from homogenization of fiber-reinforced polymers could in- volve fused data. Here, those are from electromagnetic and infrared thermographic modalities, for which semi-analytical models of the interaction are available. Focus is on inter-layer delaminations. Paths forward are outlined, mostly within the realm of Bayesian approaches and of convolutional neural networks, both of wide breadth and the second ones not involving too many prior regularization factors.

Topics
  • impedance spectroscopy
  • polymer
  • composite
  • homogenization
  • thermography