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 (4/4 displayed)

  • 2024Structural Assessment of Architected Material Using the Redundancy Matrix and Experimental Testingcitations
  • 2024Toward reciprocal feedback between computational design, engineering, and fabrication to co-design coreless filament-wound structures6citations
  • 2023Data processing, analysis, and evaluation methods for co-design of coreless filament-wound building systems7citations
  • 2023Higher-order 3D-shell elements and anisotropic 3D yield functions for improved sheet metal forming simulations: Part IIcitations

Places of action

Chart of shared publication
Paul, Sagnik
1 / 1 shared
Sychterz, Ann C.
1 / 1 shared
Forster, David
3 / 3 shared
Middendorf, Peter
2 / 21 shared
Zechmeister, Christoph
2 / 7 shared
Knippers, Jan
2 / 15 shared
Mindermann, Pascal
2 / 10 shared
Menges, Achim
2 / 7 shared
Weiskopf, Daniel
1 / 1 shared
Yang, Xiliu
1 / 1 shared
Abdelaal, Moataz
1 / 1 shared
Guo, Yanan
2 / 4 shared
Gresser, Götz Theodor
2 / 3 shared
Schwieger, Volker
2 / 2 shared
Hügle, Sebastian
2 / 2 shared
Kannenberg, Fabian
2 / 2 shared
Balangé, Laura
2 / 2 shared
Pérez, Marta Gil
2 / 11 shared
Willmann, Tobias
1 / 1 shared
Wessel, Alexander
1 / 2 shared
Schilling, Maximilian
1 / 1 shared
Butz, Alexander
1 / 5 shared
Chart of publication period
2024
2023

Co-Authors (by relevance)

  • Paul, Sagnik
  • Sychterz, Ann C.
  • Forster, David
  • Middendorf, Peter
  • Zechmeister, Christoph
  • Knippers, Jan
  • Mindermann, Pascal
  • Menges, Achim
  • Weiskopf, Daniel
  • Yang, Xiliu
  • Abdelaal, Moataz
  • Guo, Yanan
  • Gresser, Götz Theodor
  • Schwieger, Volker
  • Hügle, Sebastian
  • Kannenberg, Fabian
  • Balangé, Laura
  • Pérez, Marta Gil
  • Willmann, Tobias
  • Wessel, Alexander
  • Schilling, Maximilian
  • Butz, Alexander
OrganizationsLocationPeople

article

Structural Assessment of Architected Material Using the Redundancy Matrix and Experimental Testing

  • Paul, Sagnik
  • Bischoff, Manfred
  • Sychterz, Ann C.
  • Forster, David
Abstract

<jats:title>Abstract</jats:title><jats:p>This paper presents the integration of a numerical structural model based on the redundancy matrix and experimental results of multi-layered randomized architected materials (MLRAM). It presents a combination of the relatively new field of architected materials with a load-independent performance indicator from theoretical structural mechanics. The redundancy matrix by itself provides a measure for structural assessment that is independent of a specific load case. Various layouts of the MLRAM samples and recorded testing allow the analysis of the redundancy distribution within the structure as it undergoes failure. An in-depth analysis of the tested MLRAM samples is provided, as they show a high degree of static indeterminacy and thus, multiple different load paths. A special focus lies on the change of the redundancy distribution as global progressive failure happens. Another focus is set on the investigation of the failure initiation, meaning that the redundancy distribution can help to identify critical elements. A simple introductory example shows the interdependence between the variation of the geometric location of nodes and the redundancy distribution. The study shows, that the distribution of static indeterminacy can be used as a measure to quantify vulnerability to failure and rank the individual element’s importance. Furthermore, progressive collapse is identified as a series of local effects in the highly statically indeterminate MLRAM samples, underlining the fact that the spatial distribution of static indeterminacy is of central importance for the assessment of structural safety.</jats:p>

Topics
  • impedance spectroscopy
  • layered