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首页> 外文期刊>Advances in Water Resources >Anisotropic potential of velocity fields in real fluids: Application to the MAST solution of shallow water equations
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Anisotropic potential of velocity fields in real fluids: Application to the MAST solution of shallow water equations

机译:真实流体中速度场的各向异性势:在浅水方程组的MAST解中的应用

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In the present paper it is first shown that, due to their structure, the general governing equations of uncompressible real fluids can be regarded as an "anisotropic" potential flow problem and closed streamlines cannot occur at any time. For a discretized velocity field, a fast iterative procedure is proposed to order the computational elements at the beginning of each time level, allowing a sequential solution element by element of the advection problem. Some closed circuits could appear due to the discretization error and the elements involved in these circuits could not be ordered. We prove in the paper that the total flux of these not ordered elements goes to zero by refining the computational mesh and that it is possible to order all the remaining elements by neglecting the minimum inter-element flux inside each circuit, with a very small resulting error. The methodology is then applied to the solution of the 2D shallow water equations. The governing Partial Differential Equations are discretized over a generally unstructured triangular mesh, which attains the generalised Delaunay property. Solution is obtained applying a prediction-correction time step procedure. The prediction problem is solved applying a MArching in Space and Time (MAST) procedure, where the computational elements are required to be ordered and explicitly solved. In the correction step, a large linear well-conditioned system is solved. Model results are compared with experimental data and other numerical literature results. Computational costs have been estimated and the convergence order has been investigated according to a known exact solution.
机译:在本文中,首先表明,由于其结构的原因,不可压缩的真实流体的一般控制方程可被视为“各向异性”势流问题,并且封闭流线不会在任何时间发生。对于离散速度场,提出了一种快速迭代过程来在每个时间级别的开始对计算元素进行排序,从而允许对流问题逐个逐个求解。由于离散误差,可能会出现一些闭合电路,并且这些电路中涉及的元素无法排序。我们在论文中证明,通过优化计算网格,这些无序元素的总通量变为零,并且可以通过忽略每个电路内部的最小元素间通量来对所有其余元素进行排序,结果非常小错误。然后将该方法应用于二维浅水方程的解。控制的偏微分方程在一般非结构化的三角形网格上离散化,从而获得了广义的Delaunay性质。应用预测校正时间步长过程获得解决方案。应用时空匹配(MAST)过程解决了预测问题,其中要求对计算元素进行排序和明确求解。在校正步骤中,解决了大型线性条件良好的系统。将模型结果与实验数据和其他数字文献结果进行比较。已经根据已知的精确解估计了计算成本并研究了收敛阶数。

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