On Microstructure-Property Relationships Derived by Virtual Materials Testing with an Emphasis on Effective Conductivity View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018

AUTHORS

Matthias Neumann , Orkun Furat , Dzmitry Hlushkou , Ulrich Tallarek , Lorenz Holzer , Volker Schmidt

ABSTRACT

Based on virtual materials testing, which combines image analysis, stochastic microstructure modeling and numerical simulations, quantitative relationships between microstructure characteristics and effective conductivity can be derived. The idea of virtual materials testing is to generate a large variety of stochastically simulated microstructures in short time. These virtual, but realistic microstructures are used as input for numerical transport simulations. Finally, a large data basis is available to study microstructure-property relationships quantitatively by classical regression analysis and tools from statistical learning. The microstructure-property relationships obtained for effective conductivity can also be applied to Fickian diffusion. For validation, we discuss an example of Fickian diffusion in porous silica monoliths on the basis of 3D image data. More... »

PAGES

145-158

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-96271-9_9

DOI

http://dx.doi.org/10.1007/978-3-319-96271-9_9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106040964


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