arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2001.11536math.NAcs.NA
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ALE流体动力学中高阶网格的仿真驱动Optimization

Simulation-Driven Optimization of High-Order Meshes in ALE Hydrodynamics

Veselin Dobrev, Patrick Knupp, Tzanio Kolev, Ketan Mittal, Robert Rieben, Vladimir Tomov

摘要:

在本文中,我们提出了高阶网格优化的工具,并证明了它们的好处,在多材料的任意拉格朗日-欧拉(ALE)可压缩冲击流体动力学应用的背景下。网格优化过程由使用优化网格的模拟提供的信息驱动,例如冲击位置、材料区域、已知误差估计等。这些模拟特征通常离散地表示,例如,作为拉格朗日网格上的有限元函数。输入的离散性对于我们提出的算法的实际适用性至关重要,并将这项工作与严格需要分析信息的方法区分开来。我们的方法是基于节点移动通过高阶扩展的目标矩阵优化范式(TMOP)的克努普。所提出的公式是完全代数的,并且仅依赖于局部雅可比矩阵,因此它适用于所有类型的网格单元,在2D和3D中,以及任何阶的网格。我们讨论的概念,构建自适应目标矩阵,并获得其衍生物,重建离散数据在中间网格,节点限制,使全球网格质量的改善,同时保持空间相关的局部网格功能,和适当的规范化的目标函数。自适应方法与自动ALE触发器相结合,可以提供网格演化的鲁棒性并避免过多的重映射过程。新的高阶TMOP技术的好处说明在高阶ALE应用程序BLAST中进行的几个模拟。

英文摘要:

In this paper we propose tools for high-order mesh optimization and demonstrate their benefits in the context of multi-material Arbitrary Lagrangian-Eulerian (ALE) compressible shock hydrodynamic applications. The mesh optimization process is driven by information provided by the simulation which uses the optimized mesh, such as shock positions, material regions, known error estimates, etc. These simulation features are usually represented discretely, for instance, as finite element functions on the Lagrangian mesh. The discrete nature of the input is critical for the practical applicability of the algorithms we propose and distinguishes this work from approaches that strictly require analytical information. Our methods are based on node movement through a high-order extension of the Target-Matrix Optimization Paradigm (TMOP) of Knupp. The proposed formulation is fully algebraic and relies only on local Jacobian matrices, so it is applicable to all types of mesh elements, in 2D and 3D, and any order of the mesh. We discuss the notions of constructing adaptive target matrices and obtaining their derivatives, reconstructing discrete data in intermediate meshes, node limiting that enables improvement of global mesh quality while preserving space-dependent local mesh features, and appropriate normalization of the objective function. The adaptivity methods are combined with automatic ALE triggers that can provide robustness of the mesh evolution and avoid excessive remap procedures. The benefits of the new high-order TMOP technology are illustrated on several simulations performed in the high-order ALE application BLAST.

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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