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.
M. Neumann and V. Schmidt—The work of MN and VS has been partially funded by the German Federal Ministry for Economic Affairs and Energy (BMWi) under grant 03ET6095E.
D. Hlushkou and U. Tallarek—The work of DH and UT has been supported by the Deutsche Forschungsgemeinschaft DFG (Bonn, Germany) under grant TA 268/9-1.
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Neumann, M., Furat, O., Hlushkou, D., Tallarek, U., Holzer, L., Schmidt, V. (2018). On Microstructure-Property Relationships Derived by Virtual Materials Testing with an Emphasis on Effective Conductivity. In: Baum, M., Brenner, G., Grabowski, J., Hanschke, T., Hartmann, S., Schöbel, A. (eds) Simulation Science. SimScience 2017. Communications in Computer and Information Science, vol 889. Springer, Cham. https://doi.org/10.1007/978-3-319-96271-9_9
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