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Variational multiscale error estimators for the adaptive mesh refinement of compressible flow simulations

机译:可变多尺度误差估计器,用于可压缩流模拟的自适应网格细化

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This article investigates an explicit a-posteriori error estimator for the finite element approximation of the compressible Navier-Stokes equations. The proposed methodology employs the Variational Multi-Scale framework, and specifically, the idea is to use the variational subscales to estimate the error. These subscales are defined to be orthogonal to the finite element space, dynamic and non-linear, and both the subscales in the interior of the element and on the element boundaries are considered. Another particularity of the model is that we define some norms that lead to a dimensionally consistent measure of the compressible flow solution error inside each element; a scaled L-2-norm, and the calculation of a physical entropy measure, are both studied in this work. The estimation of the error is used to drive the adaptive mesh refinement of several compressible flow simulations. Numerical results demonstrate good accuracy of the local error estimate and the ability to drive the adaptative mesh refinement to minimize the error through the computational domain. (C) 2018 Elsevier B.V. All rights reserved.
机译:本文研究了可压缩Navier-Stokes方程的有限元逼近的显式后验误差估计器。所提出的方法采用了变分多尺度框架,具体地说,其思想是使用变分子尺度来估计误差。这些子尺度被定义为与有限元素空间正交(动态和非线性),并且考虑了元素内部和元素边界上的子尺度。该模型的另一个特殊之处是,我们定义了一些规范,这些规范导致了每个元素内部可压缩流动解决方案误差的尺寸一致性度量。在这项工作中,我们都研究了缩放的L-2-范数和物理熵测度的计算。误差的估计用于驱动几种可压缩流模拟的自适应网格细化。数值结果表明,局部误差估计具有良好的准确性,并且具有驱动自适应网格细化以通过计算域使误差最小化的能力。 (C)2018 Elsevier B.V.保留所有权利。

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