Poster Details
Data-driven crack assessment (Poster)
In Session:
PL03: Poster Track & Poster Session
Wednesday, 11 Oct 2017; 14:30 - 15:30 in room 7.02
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1st and presenting Author
Katrin Schulz
Institute for Applied Materials - Computational Materials Science
Karlsruhe Institute of Technology (KIT)
Karlsruhe, Germany
Institute for Applied Materials - Computational Materials Science
Karlsruhe Institute of Technology (KIT)
Karlsruhe, Germany
2nd Author
Valentin Verrier
Institute for Applied Materials - Computational Materials Science
Karlsruhe Institute of Technology (KIT)
Karlsruhe, Germany
Institute for Applied Materials - Computational Materials Science
Karlsruhe Institute of Technology (KIT)
Karlsruhe, Germany
3rd Author
Stephan Kreis
Institute for Applied Materials - Computational Materials Science
Karlsruhe Institute of Technology (KIT)
Karlsruhe, Germany
Institute for Applied Materials - Computational Materials Science
Karlsruhe Institute of Technology (KIT)
Karlsruhe, Germany
Micro Abstract:
Different methods of selection and feature creation are considered in order to discuss the chances and limits of a data driven assessment of cracks. We apply different methods of data mining to find correlations which yield an unconventional approach for the prediction of critical crack states and material failure. The results of different explorative multivariate analyses will be compared and discussed in the context of applicability in engineering science.