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Adjoint-based error estimation and mesh adaptation for the correction procedure via reconstruction method

机译:重建方法的基于伴随的误差估计和网格自适应

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Adjoint-based mesh adaptive methods are capable of distributing computational resources to areas which are important for predicting an engineering output. In this paper, we develop an adjoint-based h-adaptation approach based on the high-order correction procedure via reconstruction formulation (CPR) to minimize the output or functional error. A dual-consistent CPR formulation of hyperbolic conservation laws is developed and its dual consistency is analyzed. Super-convergent functional and error estimate for the output with the CPR method are obtained. Factors affecting the dual consistency, such as the solution point distribution, correction functions, boundary conditions and the discretization approach for the non-linear flux divergence term, are studied. The presented method is then used to perform simulations for the 2D Euler and Navier-Stokes equations with mesh adaptation driven by the adjoint-based error estimate. Several numerical examples demonstrate the ability of the presented method to dramatically reduce the computational cost comparing with uniform grid refinement. Published by Elsevier Inc.
机译:基于伴随的网格自适应方法能够将计算资源分配到对预测工程输出很重要的区域。在本文中,我们通过重构公式(CPR)开发了一种基于高阶校正程序的基于伴随的h自适应方法,以最大程度地减少输出或功能误差。提出了双曲线守恒律的双一致性CPR公式,并分析了其双重一致性。使用CPR方法获得了输出的超收敛功能和误差估计。研究了影响非线性对偶一致性的因素,例如解点分布,校正函数,边界条件和非线性通量发散项的离散化方法。然后,将所提出的方法用于对二维Euler和Navier-Stokes方程进行仿真,其中网格自适应由基于伴随的误差估计驱动。几个数值算例证明了与统一网格细化相比,所提出的方法能够显着降低计算成本。由Elsevier Inc.发布

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