论文标题
分析多孔介质中不可压缩的可混杂流量的最低级特征混合fems
Analysis of lowest-order characteristics-mixed FEMs for incompressible miscible flow in porous media
论文作者
论文摘要
特征类型的时间离散方案对于对流为主的扩散问题特别有效。该方案已用于在空间方向上具有不同近似值的各种工程区域。最低的混合方法是多孔介质中混溶的流量最受欢迎的方法。该方法基于对浓度的线性拉格近似值,零级raviart-thomas近似与压力/速度的近似。但是,尽管在过去几十年中已经做出了许多努力,但尚未提出最低级特征的最佳误差估计。在所有以前的工作中,仅在特定时间步和网格尺寸限制下证明了在空间方向上的一阶准确性。本文的主要目的是建立最佳误差估计值,即$,$ $ l^2 $ - 浓度的二阶和压力/速度的一阶,而浓度是基础模型的重要物理组件。为此,在我们的分析中引入了椭圆形准反射,以通过非线性分散扩散张量和浓度依赖性粘度来清理数值速度的污染。此外,可以通过在给定时间水平上重新溶解(椭圆)压力方程来获得二阶精度的数值/速度,并具有高阶近似值。提出数值结果以确认我们的理论分析。
The time discrete scheme of characteristics type is especially effective for convection-dominated diffusion problems. The scheme has been used in various engineering areas with different approximations in spatial direction. The lowest-order mixed method is the most popular one for miscible flow in porous media. The method is based on a linear Lagrange approximation to the concentration and the zero-order Raviart-Thomas approximation to the pressure/velocity. However, the optimal error estimate for the lowest-order characteristics-mixed FEM has not been presented although numerous effort has been made in last several decades. In all previous works, only first-order accuracy in spatial direction was proved under certain time-step and mesh size restrictions. The main purpose of this paper is to establish optimal error estimates, $i.e.$, the second-order in $L^2$-norm for the concentration and the first-order for the pressure/velocity, while the concentration is more important physical component for the underlying model. For this purpose, an elliptic quasi-projection is introduced in our analysis to clean up the pollution of the numerical velocity through the nonlinear dispersion-diffusion tensor and the concentration-dependent viscosity. Moreover, the numerical pressure/velocity of the second-order accuracy can be obtained by re-solving the (elliptic) pressure equation at a given time level with a higher-order approximation. Numerical results are presented to confirm our theoretical analysis.