Automatic Variationally Stable Analysis for FE Computations: An Introduction

Automatic Variationally Stable Analysis for FE Computations: An Introduction
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有限元计算的自动变分稳定分析:简介

DOI:
10.1007/978-3-030-41800-7_2
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发表时间:
2020
期刊:
Lecture Notes in Computational Engineering and Science
影响因子:
--
通讯作者:
Romkes, Albert.
Romkes, Albert.
中科院分区:
--
文献类型:
--
作者:
Calo, Victor.M.;Romkes, Albert.

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介绍了一种用于有限元计算的变分稳定自动分析方法(AVS),该方法适用于具有非常数和高振荡系数的标量对流扩散方程。本着最小二乘FE方法(Bochev和Gunzburger,Least-Squares Finite Element Methods,vol 166,Springer Science & Business Media,柏林,2009)的精神,AVS-FE方法将支配的二阶偏微分方程(PDE)重铸为一阶PDE的系统。然而,在随后的推导等价的弱配方,彼得罗夫-伽辽金技术是通过使用不同的试验和测试函数空间的插值。我们使用标准的FE近似空间的试验空间,这是C 0,和破碎的希尔伯特空间的测试功能。因此,我们寻求计算原始变量及其通量的逐点连续解(如最小二乘有限元方法),而测试函数是分段不连续的。为了确保后续FE离散化的数值稳定性,我们应用Demkowicz和Gopalakrishnan的不连续Petrov-Galerkin(DPG)方法的原理(Comput Methods Appl Mech Eng 199(23):1558-1572,2010; Discontinuous Petrov-Galerkin(DPG)method,Tech.代表,The Institute for Computational Engineering and Sciences,The University of Texas at Austin,2015; SIAM J Numer Anal 49(5):1788-1809,2011; Numer Methods Partial Differ Equ 27(1):70-105,2011; Appl Numer Math 62(4):396- 427,2012; Carstensen et al. SIAM J Numer Anal 52(3):1335-1353,2014),通过调用导致无条件稳定的数值系统的测试函数(如果底层微分算子的核是平凡的)。在AVS-FE方法中,不连续的测试函数是根据DPG方法从局部的、解耦的和适定的变分问题中确定的,这导致了能量范数方面的最佳逼近性质。我们提出了各种二维数值验证,包括对流扩散问题的高振荡系数和极高的Peclet数,高达O(109)。这些结果表明,无条件稳定,而不需要任何迎风格式,也没有任何其他人工数值稳定。结果不是高度扩散的对流为主的问题,也没有表现出任何强烈的振荡,但充分捕捉和表明边界层的存在下,即使是非常粗糙的网格和低多项式的近似度,值得注意的是,我们可以计算测试功能使用samelevel作为试验功能,而不会显着影响数值精度或渐近收敛的数值结果。此外,AVS方法为计算的通量提供了高数值精度。重要的是,AVS的方法提供了最佳的渐近误差收敛速度的orders p + 1和在theL 2和H1范数的原始变量获得。我们的经验表明,对于对流占优的问题,我们经常观察到的通量变量的L2范数的收敛速度为p + 1。
We introduce an automatic variationally stable analysis (AVS) for finite element (FE) computations of scalar-valued convection-diffusion equations with non-constant and highly oscillatory coefficients. In the spirit of least squares FE methods (Bochev and Gunzburger, Least-Squares Finite Element Methods, vol 166, Springer Science & Business Media, Berlin, 2009), the AVS-FE method recasts the governing second order partial differential equation (PDE) into a system of first-order PDEs. However, in the subsequent derivation of the equivalent weak formulation, a Petrov-Galerkin technique is applied by using different regularities for the trial and test function spaces. We use standard FE approximation spaces for the trial spaces, which areC0, and broken Hilbert spaces for the test functions. Thus, we seek to compute pointwise continuous solutions for both the primal variable and its flux (as in least squares FE methods), while the test functions are piecewise discontinuous. To ensure the numerical stability of the subsequent FE discretizations, we apply the philosophy of the discontinuous Petrov-Galerkin (DPG) method by Demkowicz and Gopalakrishnan (Comput Methods Appl Mech Eng 199(23):1558–1572, 2010; Discontinuous Petrov-Galerkin (DPG) method, Tech. rep., The Institute for Computational Engineering and Sciences, The University of Texas at Austin, 2015; SIAM J Numer Anal 49(5):1788–1809, 2011; Numer Methods Partial Differ Equ 27(1):70–105, 2011; Appl Numer Math 62(4):396–427,2012; Carstensen et al., SIAM J Numer Anal 52(3):1335–1353, 2014), by invoking test functions that lead to unconditionally stable numerical systems (if the kernel of the underlying differential operator is trivial). In the AVS-FE method, the discontinuous test functions are ascertained per the DPG approach from local, decoupled, and well-posed variational problems, which lead to best approximation properties in terms of the energy norm. We present various 2D numerical verifications, including convection-diffusion problems with highly oscillatory coefficients and extremely high Peclet numbers, up toO(109). These show the unconditional stability without the need for any upwind schemes nor any other artificial numerical stabilization. The results are not highly diffused for convection-dominated problems nor show any strong oscillations, but adequately capture and indicate the presence of boundary layers, even for very coarse meshes and low polynomial degrees of approximation,p. Remarkably, we can compute the test functions by using the sameplevel as the trial functions without significantly impacting the numerical accuracy or asymptotic convergence of the numerical results. In addition, the AVS method delivers high numerical accuracy for the computed flux. Importantly, the AVS methodology delivers optimal asymptotic error convergence rates of orderp+ 1 andpare obtained in theL2andH1norms for the primal variable. Our experience indicates that for convection-dominated problems we often observe a convergence rate ofp+ 1 for theL2norm of the flux variable.
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