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首页> 外文期刊>Computer Methods in Applied Mechanics and Engineering >Linearized domain decomposition methods for two-phase porous media flow models involving dynamic capillarity and hysteresis
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Linearized domain decomposition methods for two-phase porous media flow models involving dynamic capillarity and hysteresis

机译:用于涉及动态毛细血管性和滞后的两相多孔介质流动模型的线性化域分解方法

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摘要

We discuss two linearization and domain decomposition methods for mathematical models for two-phase flow in a porous medium. The medium consists of two adjacent regions with possibly different parameterizations. The model accounts for non-equilibrium effects like dynamic capillarity and hysteresis. The theta-scheme is adopted for the temporal discretization of the equations yielding nonlinear time-discrete equations. For these, we propose and analyze two iterative schemes, which combine a stabilized linearization iteration of fixed-point type, the L-scheme, and a non-overlapping domain decomposition method into one iteration. First, we prove the existence of unique solutions to the problems defining the linear iterations. Then, we give the rigorous convergence proof for both iterative schemes towards the solution of the time-discrete equations.The developed schemes are independent of the spatial discretization or the mesh and avoid the use of derivatives as in Newton based iterations. Their convergence holds independently of the initial guess, and under mild constraints on the time step. The numerical examples confirm the theoretical results and demonstrate the robustness of the schemes. In particular, the second scheme is well suited for models incorporating hysteresis. The schemes can be easily implemented for realistic applications. (C) 2020 Elsevier B.V. All rights reserved.
机译:我们讨论了多孔介质中两相流的数学模型的两个线性化和域分解方法。媒体由两个相邻区域组成,其中具有不同的参数化。该模型占据动态毛细血管和滞后等非平衡效果。采用θ-sch案来用于产生非线性时间离散方程的方程的时间离散化。为此,我们提出并分析了两种迭代方案,该方案将定点类型,L方案和非重叠域分解方法的稳定线性化迭代结合到一个迭代中。首先,我们证明了定义线性迭代的问题的唯一解决方案。然后,我们为迭代方案提供严格的融合证据,朝向时间离散方程的解决方案。开发方案独立于空间离散化或网格,并避免使用衍生物作为基于牛顿的迭代。他们的融合独立于初始猜测,并在时间步骤中的温和约束下。数值例子证实了理论结果并展示了方案的稳健性。特别地,第二种方案非常适合于包含滞后的模型。可以轻松实现方案以用于现实应用。 (c)2020 Elsevier B.v.保留所有权利。

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