Stable mesh decimation

C. Bajaj, A. Gillette, Qin Zhang
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引用次数: 3

Abstract

Current mesh reduction techniques, while numerous, all primarily reduce mesh size by successive element deletion (e.g. edge collapses) with the goal of geometric and topological feature preservation. The choice of geometric error used to guide the reduction process is chosen independent of the function the end user aims to calculate, analyze, or adaptively refine. In this paper, we argue that such a decoupling of structure from function modeling is often unwise as small changes in geometry may cause large changes in the associated function. A stable approach to mesh decimation, therefore, ought to be guided primarily by an analysis of functional sensitivity, a property dependent on both the particular application and the equations used for computation (e.g. integrals, derivatives, or integral/partial differential equations). We present a methodology to elucidate the geometric sensitivity of functionals via two major functional discretization techniques: Galerkin finite element and discrete exterior calculus. A number of examples are given to illustrate the methodology and provide numerical examples to further substantiate our choices.
稳定网格抽取
目前的网格缩减技术虽然众多,但都主要是通过连续删除元素(例如边缘坍塌)来减少网格尺寸,目的是保持几何和拓扑特征。用于指导简化过程的几何误差的选择与最终用户要计算、分析或自适应改进的功能无关。在本文中,我们认为这种结构与功能建模的解耦通常是不明智的,因为几何形状的微小变化可能导致相关功能的巨大变化。因此,一种稳定的网格抽取方法应该主要由函数敏感性分析来指导,函数敏感性是一种依赖于特定应用和用于计算的方程(例如积分、导数或积分/偏微分方程)的性质。我们提出了一种通过两种主要的函数离散化技术来阐明泛函的几何灵敏度的方法:伽辽金有限元和离散外部微积分。给出了一些例子来说明方法,并提供了数值例子来进一步证实我们的选择。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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