A computational modeling approach based on random fields for short fiber-reinforced composites with experimental verification by nanoindentation and tensile tests
Publication date
2021-02
Document type
Research article
Author
Organisational unit
Scopus ID
Series or journal
Computational Mechanics
Periodical volume
67
First page
699
Last page
722
Is part of
Peer-reviewed
✅
Part of the university bibliography
✅
Keyword
Karhunen–Loève expansion
Nanoindentation
Random fields
SFRC
Abstract
In this study a modeling approach for short fiber-reinforced composites is presented which allows one to consider information from the microstructure of the compound while modeling on the component level. The proposed technique is based on the determination of correlation functions by the moving window method. Using these correlation functions random fields are generated by the Karhunen–Loève expansion. Linear elastic numerical simulations are conducted on the mesoscale and component level based on the probabilistic characteristics of the microstructure derived from a two-dimensional micrograph. The experimental validation by nanoindentation on the mesoscale shows good conformity with the numerical simulations. For the numerical modeling on the component level the comparison of experimentally obtained Young’s modulus by tensile tests with numerical simulations indicate that the presented approach requires three-dimensional information of the probabilistic characteristics of the microstructure. Using this information not only the overall material properties are approximated sufficiently, but also the local distribution of the material properties shows the same trend as the results of conducted tensile tests.
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