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Pointwise dual weighted residual based goal-oriented a posteriori error estimation and adaptive mesh refinement in 2D/3D thermo-mechanical multifield problems

机译:基于点加权双重加权残差的目标后验误差估计和自适应网格细化在2D / 3D热机械多场问题中的应用

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In this article, we present a 3D adaptive method for thermoelastic problems based on goal-oriented error estimation where the error is measured with respect to a pointwise quantity of interest. We developed a method for a posteriori error estimation and mesh adaptation based on dual weighted residual (DWR) method relying on the duality principles and consisting of an adjoint problem solution. Here, we consider the application of the derived estimator and mesh refinement to two-/three dimensional (2D/3D) thermo-mechanical multifield problems. In this study, the goal is considered to be given by singular pointwise functions, such as the point value or point value derivative at a specific point of interest (PoI). An adaptive algorithm has been adopted to refine the mesh to minimize the goal in the quantity of interest.The mesh adaptivity procedure based on the DWR method is performed by adaptive local h-refinement/coarsening with allowed hanging nodes. According to the proposed DWR method, the error contribution of each element is evaluated. In the refinement process, the contribution of each element to the goal error is considered as the mesh refinement criterion.In this study, we substantiate the accuracy and performance of this method by several numerical examples with available analytical solutions. Here, 2D and 3D problems under thermo-mechanical loadings are considered as benchmark problems. To show how accurately the derived estimator captures the exact error in the evaluation of the pointwise quantity of interest, in all examples, considering the analytical solutions, the goal error effectivity index as a standard measure of the quality of an estimator is calculated. Moreover, in order to demonstrate the efficiency of the proposed method and show the optimal behavior of the employed refinement method, the results of different conventional error estimators and refinement techniques (e.g., global uniform refinement, Kelly, and weighted Kelly techniques) are used for comparison. (C) 2019 Elsevier B.V. All rights reserved.
机译:在本文中,我们提出了一种基于面向目标的误差估计的热弹性问题3D自适应方法,其中误差是相对于目标点的量进行测量的。我们开发了一种基于对偶原理并由伴随问题解决方案组成的基于双重加权残差(DWR)方法的后验误差估计和网格自适应方法。在这里,我们考虑将导出的估计量和网格细化应用于二维/三维(2D / 3D)热机械多场问题。在这项研究中,该目标被认为是由奇异的点函数给出的,例如特定兴趣点(PoI)上的点值或点值导数。采用自适应算法对网格进行细化,以最大程度地减少目标数量。基于DWR方法的网格自适应过程是通过对允许的悬挂节点进行自适应局部h细化/粗化来执行的。根据提出的DWR方法,评估每个元素的误差贡献。在细化过程中,将每个元素对目标误差的贡献视为网格细化准则。在本研究中,我们通过几个数值示例并使用可用的解析解来证实该方法的准确性和性能。在这里,热机械载荷下的2D和3D问题被视为基准问题。为了显示派生的估算器在评估逐点关注量时如何准确地捕获准确的误差,在所有示例中,考虑分析解决方案,计算目标误差有效指数作为估算器质量的标准度量。此外,为了证明所提方法的效率并显示所采用细化方法的最佳性能,使用了不同的常规误差估计器和细化技术(例如,全局均匀细化,凯利和加权凯利技术)的结果。比较。 (C)2019 Elsevier B.V.保留所有权利。

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