Structural and topological information play a key role in modeling flow and transport through fractured rock in the sub-surface. Discrete fracture Restricting the flowing fracture network to this backbone provides a significant reduction in the network's effective size. However, the particle tracking simulations needed to determine the reduction are computationally intensive. Such methods may be impractical for large systems or for robust uncertainty quantification of fracture networks, where thousands of forward simulations are needed to bound system behavior.In this paper, we develop an alternative network reduction approach to characterizing transport in DFNs, by combining graph theoretical and machine learning methods. We consider a graph representation where nodes signify fractures and edges denote their intersections. Using random forest and support vector machines, we rapidly identify a subnetwork that captures the flow patterns of the full DFN, based primarily on node centrality features in the graph. Our supervised learning techniques train on particle-tracking backbone paths found by dfnWorks, but run in negligible time compared to those simulations. We find that our predictions can reduce the network to approximately 20% of its original size, while still generating breakthrough curves consistent with those of the original network.

Nano-layered Al:ZnO/ZnO hyperbolic dispersion metamaterial with a large number of layers was fabricated using the atomic layer deposition (ALD) technique. Experimental dielectric functions for Al:ZnO/ZnO structures are obtained by an ellipsometry technique in the visible and near-infrared spectral ranges. The theoretical modeling of the Al:ZnO/ZnO dielectric permittivity is done using effective medium approximation. A method for analysis of spectroscopic ellipsometry data is demonstrated to extract the optical permittivity for this highly anisotropic nano-layered metamaterial. The results of the ellipsometry analysis show that Al:ZnO/ZnO structures with a 1:9 ALD cycle ratio exhibit hyperbolic dispersion transition change near 1.8 μm wavelength.

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