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A Reduced Order Model for Geometrically Parameterized Two-scale Simulations of Elasto-plastic Microstructures Under Large Deformations by Guo, Theron; Rokoš, Ondřej; Veroy, Karen is a scholarly article available to read on EtoBox.

What is A Reduced Order Model for Geometrically Parameterized Two-scale Simulations of Elasto-plastic Microstructures Under Large Deformations about?

In recent years, there has been a growing interest in understanding complex microstructures and their effect on macroscopic properties. In general, it is difficult to derive an effective constitutive law for such microstructures with reasonable accuracy and meaningful parameters. One numerical approach to bridge the scales is computational homogenization, in which a microscopic problem is solved at every macroscopic point, essentially replacing the effective constitutive model. Such approaches are, however, computationally expensive and typically infeasible in multi-query contexts such as optimization and material design. To render these analyses tractable, surrogate models that can accurately approximate and accelerate the microscopic problem over a large design space of shapes, material and loading parameters are required. In this work, we develop a reduced order model based on Proper Orthogonal Decomposition (POD), Empirical Cubature Method (ECM) and a geometrical transformation method with the following key features: (i) large shape variations of the microstructure are captured, (ii) only relatively small amounts of training data are necessary, and (iii) highly non-linear histo

Author

Guo, Theron; Rokoš, Ondřej; Veroy, Karen

Published

2023

Language

EN