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 (10/10 displayed)

  • 2022Coupling crystal plasticity and cellular automaton models to study meta-dynamic recrystallization during hot rolling at high strain rates25citations
  • 2022Coupling crystal plasticity and cellular automaton models to study meta-dynamic recrystallization during hot rolling at high strain rates25citations
  • 2020An efficient and robust approach to determine material parameters of crystal plasticity constitutive laws from macro-scale stress-strain curves109citations
  • 2019DAMASK – The Düsseldorf Advanced Material Simulation Kit for modeling multi-physics crystal plasticity, thermal, and damage phenomena from the single crystal up to the component scale637citations
  • 2019DAMASK - The Dusseldorf Advanced Material Simulation Kit for modeling multi-physics crystal plasticity, thermal, and damage phenomena from the single crystal up to the component scalecitations
  • 2017Crystal plasticity study on stress and strain partitioning in a measured 3D dual phase steel microstructure70citations
  • 2014In situ observation of collective grain-scale mechanics in Mg and Mg-rare earth alloys103citations
  • 2014Strain localization and damage in dual phase steels investigated by coupled in-situ deformation experiments and crystal plasticity simulations476citations
  • 2014Integrated experimental--simulation analysis of stress and strain partitioning in multiphase alloys320citations
  • 2012DAMASK: the Dusseldorf Advanced MAterial Simulation Kit for studying crystal plasticity using an FE based or a spectral numerical solver191citations

Places of action

Chart of shared publication
Dokkum, J. S. Van
1 / 1 shared
Sedighiani, Karo
2 / 11 shared
Roters, F.
9 / 51 shared
Bos, C.
2 / 14 shared
Shah, V.
2 / 2 shared
Van Dokkum, J. S.
1 / 2 shared
Sedighiani, K.
1 / 2 shared
Sietsma, Jilt
1 / 44 shared
Traka, K.
1 / 5 shared
Raabe, D.
4 / 79 shared
Meier, F.
2 / 6 shared
Fujita, N.
2 / 3 shared
Friák, M.
1 / 25 shared
Janssens, K. G. F.
1 / 5 shared
Grilli, N.
2 / 9 shared
Kok, P. J. J.
1 / 4 shared
Reuber, C.
2 / 3 shared
Stricker, M.
2 / 5 shared
Maiti, T.
2 / 2 shared
Wong, S. L.
1 / 2 shared
Hochrainer, T.
2 / 17 shared
Ebrahimi, A.
2 / 3 shared
Jia, N.
2 / 5 shared
Nikolov, S.
2 / 15 shared
Shanthraj, Pratheek
3 / 57 shared
Werner, E.
2 / 9 shared
Eisenlohr, P.
2 / 23 shared
Fabritius, H. O.
1 / 3 shared
Weygand, D.
2 / 40 shared
Ma, D.
2 / 22 shared
Friak, M.
1 / 18 shared
Kok, P.
1 / 1 shared
Shanthraj, P.
2 / 3 shared
Janssens, K.
1 / 4 shared
Fabritius, H.
1 / 9 shared
Wong, S.
1 / 4 shared
An, D.
1 / 1 shared
Zaefferer, S.
1 / 49 shared
Raabe, Dierk
4 / 523 shared
Sandloebes, S.
1 / 11 shared
Sharma, L.
1 / 3 shared
Wang, F.
1 / 48 shared
Tasan, Cc Cem
1 / 12 shared
Roters, Franz
2 / 39 shared
Yan, D.
2 / 4 shared
Hoefnagels, Jpm Johan
1 / 71 shared
Tasan, C. C.
1 / 18 shared
Zambaldi, Claudio
1 / 2 shared
Yan, Dingshun
1 / 2 shared
Diehl, Martin
1 / 29 shared
Tasan, Cemal Cem
1 / 6 shared
Zambaldi, C.
1 / 7 shared
Tjahjanto, D. D.
1 / 9 shared
Kords, C.
1 / 2 shared
Chart of publication period
2022
2020
2019
2017
2014
2012

Co-Authors (by relevance)

  • Dokkum, J. S. Van
  • Sedighiani, Karo
  • Roters, F.
  • Bos, C.
  • Shah, V.
  • Van Dokkum, J. S.
  • Sedighiani, K.
  • Sietsma, Jilt
  • Traka, K.
  • Raabe, D.
  • Meier, F.
  • Fujita, N.
  • Friák, M.
  • Janssens, K. G. F.
  • Grilli, N.
  • Kok, P. J. J.
  • Reuber, C.
  • Stricker, M.
  • Maiti, T.
  • Wong, S. L.
  • Hochrainer, T.
  • Ebrahimi, A.
  • Jia, N.
  • Nikolov, S.
  • Shanthraj, Pratheek
  • Werner, E.
  • Eisenlohr, P.
  • Fabritius, H. O.
  • Weygand, D.
  • Ma, D.
  • Friak, M.
  • Kok, P.
  • Shanthraj, P.
  • Janssens, K.
  • Fabritius, H.
  • Wong, S.
  • An, D.
  • Zaefferer, S.
  • Raabe, Dierk
  • Sandloebes, S.
  • Sharma, L.
  • Wang, F.
  • Tasan, Cc Cem
  • Roters, Franz
  • Yan, D.
  • Hoefnagels, Jpm Johan
  • Tasan, C. C.
  • Zambaldi, Claudio
  • Yan, Dingshun
  • Diehl, Martin
  • Tasan, Cemal Cem
  • Zambaldi, C.
  • Tjahjanto, D. D.
  • Kords, C.
OrganizationsLocationPeople

article

An efficient and robust approach to determine material parameters of crystal plasticity constitutive laws from macro-scale stress-strain curves

  • Sedighiani, Karo
  • Sietsma, Jilt
  • Roters, F.
  • Traka, K.
  • Diehl, M.
  • Raabe, D.
Abstract

A severe obstacle for the routine use of crystal plasticity models is the effort associated with determining their constitutive parameters. Obtaining these parameters usually requires time-consuming micromechanical tests that allow probing of individual grains. In this study, a novel, computationally efficient, and fully automated approach is introduced which allows the identification of constitutive parameters from macroscopic tests. The approach presented here uses the response surface methodology together with a genetic algorithm to determine an optimal set of parameters. It is especially suited for complex models with a large number of parameters. The proposed approach also helps to develop a quantitative and thorough understanding of the relative influence of the different constitutive parameters and their interactions. Such general insights into parameter relations in complex models can be used to improve constitutive laws and reduce redundancy in parameter sets. The merits of the methodology are demonstrated on the examples of a dislocation-density-based crystal plasticity model for bcc steel, a phenomenological crystal plasticity model for fcc copper, and a phenomenological crystal plasticity model incorporating twinning deformation for hcp magnesium. The approach proposed is, however, model-independent and can be also used to identify parameters of, for instance, fatigue, creep and damage models. The method has been implemented into the Düsseldorf Advanced Material Simulation Kit (DAMASK) and is available as free and open-source software. The capability of translating complex material response into a micromechanical digital twin is an essential precondition for the ongoing digitalization of material property prediction, quality control of semi-finished parts, material response in manufacturing and the long-term behavior of products and materials when in service. ; (OLD) MSE-3 ; Materials Science and Engineering

Topics
  • density
  • impedance spectroscopy
  • surface
  • grain
  • simulation
  • Magnesium
  • Magnesium
  • steel
  • stress-strain curve
  • fatigue
  • dislocation
  • copper
  • plasticity
  • crystal plasticity
  • creep