Sharp volumetric billboard based characterization and modeling of complex 3D Ni/Al high energy ball milled composites

Abstract

We present an innovative image-based modeling technique, based on Google Earth like algorithms, to effectively resolve intricate material morphology and address the computational complexity associated with heterogeneous materials. This sharp volumetric billboard algorithm stems from a volumetric billboard method, a multi-resolution modeling strategy in computer graphics. In this work, we enhance volumetric billboards through a sharpening filter to reconstruct the statistical information of heterogeneous systems. A hierarchy of microstructures is created for high energy ball milled Ni/Al composites. We analyze the first-and second-order statistics of microstructures, and characterize both macro-and micro-mechanical material responses. Furthermore, we conduct a convergence study of the associated computational results. The statistical and mechanical robustness of data compression is demonstrated through the corresponding error analysis.

Data‐driven modeling of heterogeneous viscoelastic biofilms

“…H. Lee et al (2011) and Gillman and Matouš (2014) used microtomographic data to compute mechanical and thermal properties of particulate systems. Yushu et al (2017) used sharp volumetric billboards (SVB) to study complex 3D Ni/Al high energy ball-milled composites. Gillman et al (2017) developed microstructure statistics-property relations of silver paste interconnects using the combination of focused ion beam (FIB) milling and scanning electron microscopy (SEM) imaging.…”