Generalized balanced power diagrams for 3D representations of polycrystals
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Abstract (arXiv)
Characterizing the grain structure of polycrystalline material is an important task in material science. The present paper introduces the concept of generalized balanced power diagrams as a concise alternative to voxelated mappings. Here, each grain is represented by (measured approximations of) its center-of-mass position, its volume and, if available, by its second-order moments (in the non-equiaxed case). Such parameters may be obtained from 3D x-ray diffraction. As the exact global optimum of our model results from the solution of a suitable linear program it can be computed quite efficiently. Based on verified real-world measurements we show that from the few parameters per grain (3, respectively 6 in 2D and 4, respectively 10 in 3D) we obtain excellent representations of both equiaxed and non-equiaxed structures. Hence our approach seems to capture the physical principles governing the forming of such polycrystals in the underlying process quite well.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Nov 2014.
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Citing papers per year: 2024: 1; 2025: 1; 2026: 1.
3 papers.
- 2024Generating multi-scale NMC particles with radial grain architectures using spatial stochastics and GANscited by 0
- 2025Fitting Generalized Power Diagrams to 3D Image Data: A Prerequisite for Virtual Materials Testingcited by 0
- 2026Superpixel-Based Image Segmentation Using Squared 2-Wasserstein Distancescited by 0
- 2026Superpixel-Based Image Segmentation Using Squared 2-Wasserstein Distances22 Jan 2026
- 2025Fitting Generalized Power Diagrams to 3D Image Data: A Prerequisite for Virtual Materials Testing18 Jul 2025
- 2024Generating multi-scale NMC particles with radial grain architectures using spatial stochastics and GANs7 Jul 2024