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首页> 外文期刊>Computer Methods in Applied Mechanics and Engineering >Analysis of an augmented pseudostress-based mixed formulation for a nonlinear Brinkman model of porous media flow
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Analysis of an augmented pseudostress-based mixed formulation for a nonlinear Brinkman model of porous media flow

机译:基于多孔介质流非线性Brinkman模型的基于拟应力的混合公式分析

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In this paper we introduce and analyze an augmented mixed finite element method for the two-dimensional nonlinear Brinkman model of porous media flow with mixed boundary conditions. More precisely, we extend a previous approach for the respective linear model to the present nonlinear case, and employ a dual-mixed formulation in which the main unknowns are given by the gradient of the velocity and the pseudostress. In this way, and similarly as before, the original velocity and pressure unknowns are easily recovered through a simple postprocessing. In addition, since the Neumann boundary condition becomes essential, we impose it in a weak sense, which yields the introduction of the trace of the fluid velocity over the Neumann boundary as the associated Lagrange multiplier. We apply known results from nonlinear functional analysis to prove that the corresponding continuous and discrete schemes are well-posed. In particular, a feasible choice of finite element subspaces is given by Raviart-Thomas elements of order k >= 0 for the pseudostress, piecewise polynomials of degree <= k for the gradient of the velocity, and continuous piecewise polynomials of degree <= k + 1 for the Lagrange multiplier. We also derive a reliable and efficient residual-based a posteriori error estimator for this problem. Finally, several numerical results illustrating the performance and the robustness of the method, confirming the theoretical properties of the estimator, and showing the behavior of the associated adaptive algorithm, are provided. (C) 2015 Elsevier B.V. All rights reserved.
机译:本文介绍并分析了带有混合边界条件的多孔介质二维二维Brinkman模型的增强混合有限元方法。更准确地说,我们将用于各个线性模型的先前方法扩展到当前的非线性情况,并采用双重混合公式,其中主要未知数由速度和伪应力的梯度给出。这样,与以前类似,可以通过简单的后处理轻松恢复原始的速度和压力未知数。另外,由于诺伊曼边界条件变得必不可少,因此我们将其强加为弱条件,从而引入了诺伊曼边界上的流体速度轨迹作为相关的拉格朗日乘数。我们应用非线性功能分析的已知结果来证明相应的连续和离散方案是正确的。特别是,对于伪应力,阶数k> = 0的Raviart-Thomas元素给出了有限元子空间的可行选择;对于速度梯度,阶数<= k的分段多项式;阶数<= k的连续分段多项式拉格朗日乘数+1。我们还导出了一个可靠且有效的基于残差的后验误差估计器。最后,提供了一些数值结果,说明了该方法的性能和鲁棒性,证实了估计器的理论特性,并显示了相关自适应算法的行为。 (C)2015 Elsevier B.V.保留所有权利。

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