2021/03/16 by Ajinkya Gote, Andreas Fischer, Gote, Ajinkya +5
Computer Science · Earth and Planetary Sciences · Engineering · #74B05 #74Q15 #74Q20 #Computational Engineering #Enhanced Oil Recovery Techniques #FOS: Computer and information sciences #Finance #Medical Image Segmentation Techniques #Seismic Imaging and Inversion Techniques #and Science (cs.CE)
paper · pdf · doi:10.48550/arxiv.2103.08957
openalex publication_date 2021/03/16 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Micro- and mesostructures of multiphase materials obtained from tomography\nand image acquisition are an ever more important database for simulation\nanalyses. Huge data sets for reconstructed 3d volumes typically as voxel grids\ncall for criteria and measures to find an affordable balance of accuracy and\nefficiency. The present work shows for a 3d mesostructure of concrete in the\nelastic deformation range, how the computational complexity in analyses of\nnumerical homogenization can be reduced at controlled errors. Reduction is\nsystematically applied to specimen size S, resolution R, and discretization D,\nwhich span the newly introduced SRD parameter space. Key indicators for\naccuracy are (i) the phase fractions, (ii) the homogenized elasticity tensor,\n(iii) its invariance with respect to the applied boundary conditions and (iv)\nthe total error as well as spatial error distributions, which are computed and\nestimated. Pre-analyses in the 2d SRD parameter sub-space explore the\ntransferability to the 3d case. Beyond the concrete specimen undergoing elastic\ndeformations in the present work, the proposed concept enables\naccuracy-efficiency balances for various classes of heterogeneous materials in\ndifferent deformation regimes and thus contributes to build comprehensive\ndigital twins of materials with validated attributes.\n