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微机械分析中模型简化的集成效率。

Integration efficiency for model reduction in micro-mechanical analyses.

作者信息

van Tuijl Rody A, Remmers Joris J C, Geers Marc G D

机构信息

Eindhoven University of Technology, P.O. Box 513, Eindhoven, The Netherlands.

出版信息

Comput Mech. 2018;62(2):151-169. doi: 10.1007/s00466-017-1490-4. Epub 2017 Nov 10.

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.

摘要

微观结构分析是在宏观尺度上理解材料行为的重要工具。微观结构分析通常在计算上要求很高,文献中有几种降阶建模技术可用于限制对单个代表性体积单元进行重复分析的计算成本。这些在微观尺度上加速积分的技术大致可分为两类:被积函数插值方法和求积方法。从逼近全阶结果的准确性方面评估了经验插值方法(高性能降阶建模)和经验求积方法。因此,考虑了一个微观结构体积单元,它承受四种载荷工况,包括循环载荷和与路径相关的载荷。突出了在逼近感兴趣的微观和宏观量方面的差异,例如微观波动和应力。量化了这两种方法相对于全阶微观结构模型的算法加速。从而明确确定了这两类方法的优缺点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fdbf/6432970/1c790a0345b1/466_2017_1490_Fig1_HTML.jpg

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