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arXiv 1603.08893math.NAcs.NA
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有限变形基于FFT的非线性求解器的简化

Finite strain FFT-based non-linear solvers made simple

Materials Innovation Institute (M2i)(材料创新研究所);Eindhoven University of Technology(埃因霍温理工大学);Technische Universität Braunschweig(布伦瑞克工业大学);Czech Technical University in Prague(布拉格捷克理工大学)

T. W. J. de Geus, J. Vondrejc, J. Zeman, R. H. J. Peerlings, M. G. D. Geers

AI总结:

本文提出了一种基于FFT的非线性求解器,通过变分形式实现无条件稳定方案,结合牛顿迭代与迭代线性求解器,实现鲁棒性和二次收敛性,简化了实现过程并展示了两种不同材料模型的应用。

摘要:

计算微力学和均质化需要求解包含复杂微观结构的周期单元的机械平衡。应用快速傅里叶变换的技术因其在速度和内存占用方面优于其他方法而受到关注。在原始形式中,处理几何非线性问题是主要挑战之一,部分原因是需要统一的线性参考问题。在几何线性设置中,最近通过变分形式处理问题,产生无条件稳定的方案,结合牛顿迭代与迭代线性求解器,从而表现出鲁棒性和二次收敛性。通过这种方法,恢复了离散化、数值积分、材料模型的一致线性化以及由此产生的线性系统迭代求解等关键要素。因此,扩展到有限变形,使用任意本构模型是可行的。由于应用了快速傅里叶变换,实现比其他(有限元)方法要简单得多。本文通过一篇仅59行(无注释)的Python代码展示了这两个主张,并用两种不同材料模型的例子证明了该方法的潜力。

英文摘要:

Computational micromechanics and homogenization require the solution of the mechanical equilibrium of a periodic cell that comprises a (generally complex) microstructure. Techniques that apply the Fast Fourier Transform have attracted much attention as they outperform other methods in terms of speed and memory footprint. Moreover, the Fast Fourier Transform is a natural companion of pixel-based digital images which often serve as input. In its original form, one of the biggest challenges for the method is the treatment of (geometrically) non-linear problems, partially due to the need for a uniform linear reference problem. In a geometrically linear setting, the problem has recently been treated in a variational form resulting in an unconditionally stable scheme that combines Newton iterations with an iterative linear solver, and therefore exhibits robust and quadratic convergence behavior. Through this approach, well-known key ingredients were recovered in terms of discretization, numerical quadrature, consistent linearization of the material model, and the iterative solution of the resulting linear system. As a result, the extension to finite strains, using arbitrary constitutive models, is at hand. Because of the application of the Fast Fourier Transform, the implementation is substantially easier than that of other (Finite Element) methods. Both claims are demonstrated in this paper and substantiated with a simple code in Python of just 59 lines (without comments). The aim is to render the method transparent and accessible, whereby researchers that are new to this method should be able to implement it efficiently. The potential of this method is demonstrated using two examples, each with a different material model.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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