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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Rokoš, O.

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Eindhoven University of Technology

in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (10/10 displayed)

  • 2025Reduced-Order Modeling for Second-Order Computational Homogenization With Applications to Geometrically Parameterized Elastomeric Metamaterials2citations
  • 2024A comparative study of enriched computational homogenization schemes applied to two-dimensional pattern-transforming elastomeric mechanical metamaterials5citations
  • 2024A comparative study of enriched computational homogenization schemes applied to two-dimensional pattern-transforming elastomeric mechanical metamaterials5citations
  • 2024Harvesting deformation modes for micromorphic homogenization from experiments on mechanical metamaterials2citations
  • 2023Bayesian approach to micromechanical parameter identification using Integrated Digital Image Correlation3citations
  • 2023Integrated digital image correlation for micro-mechanical parameter identification in multiscale experiments12citations
  • 2021Comparative study of multiscale computational strategies for materials with discrete microstructures5citations
  • 2020Reduced integration schemes in micromorphic computational homogenization of elastomeric mechanical metamaterials13citations
  • 2020Extended micromorphic computational homogenization for mechanical metamaterials exhibiting multiple geometric pattern transformations25citations
  • 2020A Newton solver for micromorphic computational homogenization enabling multiscale buckling analysis of pattern-transforming metamaterials22citations

Places of action

Chart of shared publication
Geers, M. G. D.
4 / 95 shared
Kouznetsova, V. G.
2 / 13 shared
Guo, T.
3 / 6 shared
Veroy, K.
1 / 1 shared
Sperling, S. O.
1 / 1 shared
Peerlings, R. H. J.
6 / 31 shared
D., Geers M. G.
1 / 1 shared
G., Kouznetsova V.
1 / 1 shared
O., Sperling S.
1 / 1 shared
J., Peerlings R. H.
1 / 1 shared
Geers, Mgd Marc
2 / 117 shared
Maraghechi, Siavash
1 / 3 shared
Hoefnagels, Jpm Johan
2 / 71 shared
Gaynutdinova, L.
1 / 1 shared
Zeman, J.
1 / 4 shared
Pultarová, I.
1 / 1 shared
Havelka, J.
1 / 1 shared
Mikeš, K.
1 / 1 shared
Bormann, F.
1 / 3 shared
Ameen, M. M.
1 / 2 shared
Doškář, M.
1 / 1 shared
Van Bree, S. E. H. M.
1 / 1 shared
Chart of publication period
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Co-Authors (by relevance)

  • Geers, M. G. D.
  • Kouznetsova, V. G.
  • Guo, T.
  • Veroy, K.
  • Sperling, S. O.
  • Peerlings, R. H. J.
  • D., Geers M. G.
  • G., Kouznetsova V.
  • O., Sperling S.
  • J., Peerlings R. H.
  • Geers, Mgd Marc
  • Maraghechi, Siavash
  • Hoefnagels, Jpm Johan
  • Gaynutdinova, L.
  • Zeman, J.
  • Pultarová, I.
  • Havelka, J.
  • Mikeš, K.
  • Bormann, F.
  • Ameen, M. M.
  • Doškář, M.
  • Van Bree, S. E. H. M.
OrganizationsLocationPeople

article

Integrated digital image correlation for micro-mechanical parameter identification in multiscale experiments

  • Geers, Mgd Marc
  • Peerlings, R. H. J.
  • Rokoš, O.
  • Hoefnagels, Jpm Johan
Abstract

Micromechanical constitutive parameters are important for many engineering materials, typically in microelectronic applications and material design. Their accurate identification poses a three-fold experimental challenge: (i) deformation of the microstructure is observable only at small scales, requiring SEM or other microscopy techniques; (ii) external loadings are applied at a (larger) engineering or device scale; and (iii) material parameters typically depend on the applied manufacturing process, necessitating measurements on material produced with the same process. In this paper, micromechanical parameter identification in heterogeneous solids is addressed through multiscale experiments combined with Integrated Digital Image Correlation (IDIC) in conjunction with various possible computational homogenization schemes. To this end, some basic concepts underlying multiscale approaches available in the literature are first reviewed, discussing their respective advantages and disadvantages from the computational as well as experimental point of view. A link is made with recently introduced uncoupled methods, which allow for identification of material parameter ratios at the microscale, still lacking a proper normalization. Two multiscale methods are analysed, allowing to bridge the gap between microstructural kinematics and macroscopically measured forces, providing the required normalization. It is shown that an integrated experimental–computational scheme provides relaxed requirements on scale separation. The accuracy and performance of the discussed techniques are analysed by means of virtual experimentation under plane strain and large strain assumptions for unidirectional fibre-reinforced composites. The robustness against image noise is also assessed. The obtained results demonstrate that the expected accuracy is typically within 10% RMS error for all multiscale methods, but decreasing to 1% RMS error for the optimal method.

Topics
  • impedance spectroscopy
  • microstructure
  • scanning electron microscopy
  • experiment
  • composite
  • homogenization