Reduced-order multiscale modeling of plastic deformations in 3D alloys with spatially varying porosity by deflated clustering analysis
Reduced-order multiscale modeling of plastic deformations in 3D alloys with spatially varying porosity by deflated clustering analysis
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DOI：
10.1007/s00466-022-02177-8
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发表时间：
2021-08
影响因子：
4.1
通讯作者：
Shiguang Deng;Carl Soderhjelm;D. Apelian;R. Bostanabad
中科院分区：
文献类型：
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作者：
Shiguang Deng;Carl Soderhjelm;D. Apelian;R. Bostanabad
铝合金因其在高机械负荷下的优异性能，在汽车工业中作为轻质材料得到了越来越多的应用。阻碍这些合金在高性能应用中大规模使用的一个重大挑战是存在由制造引起的空间变化的孔隙率缺陷。为了了解这些缺陷对铸造合金宏观力学性能的影响，通常需要进行多尺度模拟。本文介绍了一种计算高效的降阶多尺度框架，用于模拟含有过程诱导孔洞的金属构件在不可逆非线性变形下的行为。在我们的方法中，我们从一种数据压缩方案开始，该方案通过将邻近的有限元节点聚集到有限数量的簇中来显著减少未知的宏观和微观变量的数量。然后，我们使用收缩方法将这些变量投影到低维空间，在那里材料的弹塑性行为是近似的。最后，我们求解未知变量，并将它们映射回原始的高维空间。我们称我们的方法为收缩聚类分析，通过与直接数值模拟的比较，我们证明了它准确地捕捉到了宏观尺度的变形和微观的有效响应。为了说明微尺度气孔对铸件宏观响应的影响，我们对空间变化的局部异质性进行了多尺度模拟，并用微结构表征和重建算法对其进行了建模。
Aluminum alloys are increasingly utilized as lightweight materials in the automobile industry due to their superior capability in withstanding high mechanical loads. A significant challenge impeding the large-scale use of these alloys in high-performance applications is the presence of manufacturing-induced, spatially varying porosity defects. In order to understand the impacts of these defects on the macro-mechanical properties of cast alloys, multiscale simulations are often required. In this paper, we introduce a computationally efficient reduced-order multiscale framework to simulate the behavior of metallic components containing process-induced porosity under irreversible nonlinear deformations. In our approach, we start with a data compression scheme that significantly reduces the number of unknown macroscale and microscale variables by agglomerating close-by finite element nodes into a limited number of clusters. Then, we use deflation methods to project these variables into a lower-dimensional space where the material’s elastoplastic behaviors are approximated. Finally, we solve for the unknown variables and map them back to the original, high-dimensional space. We call our method deflated clustering analysis and by comparing it to direct numerical simulations we demonstrate that it accurately captures macroscale deformations and microscopic effective responses. To illustrate the effect of microscale pores on the macroscopic response of a cast component, we conduct multi-scale simulations with spatially varying local heterogeneities that are modeled with a microstructure characterization and reconstruction algorithm.