1. Integration efficiency for model reduction in micro-mechanical analyses
- Author
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Jjc Joris Remmers, Mgd Marc Geers, Rody A. van Tuijl, Mechanics of Materials, and Group Geers
- Subjects
Empirical cubature method ,Speedup ,Computer science ,Computational Mechanics ,Ocean Engineering ,010103 numerical & computational mathematics ,01 natural sciences ,Homogenization (chemistry) ,Reduced order ,Applied mathematics ,Micro-mechanics ,0101 mathematics ,Volume element ,Original Paper ,Homogenization ,Model reduction ,Applied Mathematics ,Mechanical Engineering ,Micromechanics ,010101 applied mathematics ,Computational Mathematics ,Computational Theory and Mathematics ,Macroscopic scale ,Representative elementary volume ,Empirical interpolation method ,Interpolation - Abstract
Micro-structural analyses are an important tool to understand material behavior on a macroscopic scale. The analysis of a microstructure is usually computationally very demanding and there are several reduced order modeling techniques available in literature to limit the computational costs of repetitive analyses of a single representative volume element. These techniques to speed up the integration at the micro-scale can be roughly divided into two classes; methods interpolating the integrand and cubature methods. The empirical interpolation method (high-performance reduced order modeling) and the empirical cubature method are assessed in terms of their accuracy in approximating the full-order result. A micro-structural volume element is therefore considered, subjected to four load-cases, including cyclic and path-dependent loading. The differences in approximating the micro- and macroscopic quantities of interest are highlighted, e.g. micro-fluctuations and stresses. Algorithmic speed-ups for both methods with respect to the full-order micro-structural model are quantified. The pros and cons of both classes are thereby clearly identified.
- Published
- 2018