Dynamic grain models via fast heuristics for diagram representations

Abstract

The present paper introduces a mathematical model for studying dynamic grain growth. In particular, we show how characteristic measurements, grain volumes, centroids, and central second-order moments at discrete moments in time can be turned quickly into a continuous description of the grain growth process in terms of geometric diagrams (which largely generalize the well-known Voronoi and Laguerre tessellations). We evaluate the computational behavior of our algorithm on real-world data.

arXiv comment21 pages, 4 tables, 6 figures

References in corpus (5)

• Grain-Boundary Kinetics: A Unified Approach
• A unified theory of grain growth in polycrystalline materials
• Generalized balanced power diagrams for 3D representations of polycrystals
• Laguerre tessellations and polycrystalline microstructures: A fast algorithm for generating grains of given volumes
• Fitting Laguerre tessellation approximations to tomographic image data