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A robust and scalable unfitted adaptive finite element framework for nonlinear solid mechanics
arXiv - CS - Mathematical Software Pub Date : 2020-12-01 , DOI: arxiv-2012.00280
Santiago Badia, Manuel Caicedo, Alberto F. Martín, Javier Principe

We extend the unfitted $h$-adaptive Finite Element Method ($h$-AgFEM) on parallel tree-based adaptive meshes, recently developed for linear scalar elliptic problems, to handle nonlinear problems in solid mechanics. Leveraging $h$-AgFEM on locally-adapted, non-conforming, tree-based meshes, and its parallel distributed-memory implementation, we can tackle large-, multi-scale problems posed on complex geometries. On top of that, in order to accurately and efficiently capture localized phenomena that frequently occur in nonlinear solid mechanics problems, we propose an algorithm to perform pseudo time-stepping in combination with $h$-adaptive dynamic mesh refinement and re-balancing driven by a-posteriori error estimators. The method is implemented considering both irreducible and mixed (u/p) formulations and thus it is able to robustly face problems involving incompressible materials. In the numerical experiments, both formulations are used to model the inelastic behavior of a wide range of compressible and incompressible materials. First, a selected set of state-of-the-art benchmarks are reproduced as a verification step. Second, a set of experiments is presented with problems involving complex geometries. Among them, we model a cantilever beam problem with spherical voids whose distribution is based on a Cube Closest Packing (CCP). This test involves a discrete domain with up to 11.7M Degrees Of Freedom (DOFs) solved in less than two hours on 3072 cores of a parallel supercomputer.

中文翻译:

用于非线性固体力学的健壮且可扩展的不拟合自适应有限元框架

我们在最近针对线性标量椭圆问题开发的基于并行树的自适应网格上扩展了未拟合的$ h $自适应有限元方法($ h $ -AgFEM),以处理实体力学中的非线性问题。利用$ h $ -AgFEM在本地适应的,不合格的,基于树的网格上及其并行的分布式内存实现,我们可以解决复杂几何结构带来的大规模,多尺度问题。最重要的是,为了准确,有效地捕获非线性固体力学问题中经常发生的局部现象,我们提出了一种算法,该算法结合由$ h $支持的动态网格细化和由驱动的重新平衡来执行伪时间步长后验误差估计量。该方法是在考虑不可还原和混合(u / p)配方的情况下实施的,因此它能够可靠地解决涉及不可压缩材料的问题。在数值实验中,两种公式都用于模拟各种可压缩和不可压缩材料的非弹性行为。首先,将复制一组选定的最新基准作为验证步骤。其次,提出了一组涉及复杂几何问题的实验。其中,我们对具有球形空隙的悬臂梁模型进行建模,其分布基于立方最近堆积(CCP)。该测试涉及一个离散域,该域在不到两小时的时间内就可以在并行超级计算机的3072个内核上解决多达11.7M个自由度(DOF)。两种公式均用于模拟各种可压缩和不可压缩材料的非弹性行为。首先,将复制一组选定的最新基准作为验证步骤。其次,提出了一组涉及复杂几何问题的实验。其中,我们对具有球形空隙的悬臂梁模型进行建模,其分布基于立方最近堆积(CCP)。该测试涉及一个离散域,该域在不到两小时的时间内就可以在并行超级计算机的3072个内核上解决多达11.7M个自由度(DOF)。两种公式均用于模拟各种可压缩和不可压缩材料的非弹性行为。首先,将复制一组选定的最新基准作为验证步骤。其次,提出了一组涉及复杂几何问题的实验。其中,我们对具有球形空隙的悬臂梁模型进行建模,其分布基于立方最近堆积(CCP)。该测试涉及一个离散域,该域在不到两小时的时间内就可以在并行超级计算机的3072个内核上解决多达11.7M个自由度(DOF)。提出了一组涉及复杂几何问题的实验。其中,我们对具有球形空隙的悬臂梁模型进行建模,其分布基于立方最近堆积(CCP)。该测试涉及一个离散域,该域在不到两小时的时间内就可以在并行超级计算机的3072个内核上解决多达11.7M个自由度(DOF)。提出了一组涉及复杂几何问题的实验。其中,我们对具有球形空隙的悬臂梁模型进行建模,其分布基于立方最近堆积(CCP)。该测试涉及一个离散域,该域在不到两小时的时间内就可以在并行超级计算机的3072个内核上解决多达11.7M个自由度(DOF)。
更新日期:2020-12-03
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