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Solving Partial Differential Algebraic Equations and Reactive Transport Models

机译:求解局部差分代数方程和反应运输模型

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In some scientific applications, such as groundwater studies, several processes are represented by coupled models. For example, a density-driven flow model couples the flow equations with the transport of salt. A reactive transport model couples transport equations of pollutants with chemical equations. The coupled model can combine partial differential equations with algebraic equations, in a so-called PDAE system, which is in general nonlinear. A classical approach is to follow a method of lines, where space is first discretized, leading to a semi-discrete differential algebraic system (DAE). Then time is discretized by a scheme tuned for DAE, such that each time step requires the solving of a nonlinear system of equations. In some decoupled approaches, a fixed-point technique is used. However, a Newton method converges faster in general and is more efficient, even though each iteration is more CPU-intensive. In this chapter, we deal with reactive transport models and show how a Newton method can be used efficiently. Numerical experiments illustrate the efficiency of a substitution technique. Moreover, it appears that using logarithms in the chemistry equations lead to ill conditioned matrices and increase the computational cost.
机译:在一些科学应用中,例如地下水研究,耦合模型代表了几个过程。例如,密度驱动的流动模型与盐的传输耦合流动方程。反应运输模型与化学方程的污染物传输方程耦合。耦合模型可以将部分微分方程与代数方程组合在一起,所谓的PDAE系统中,这是一般非线性的。经典方法是遵循一种线的方法,其中首先离散地是空间,导致半离散差分代数系统(DAE)。然后通过针对DAE调谐的方案离散时间,使得每个时间步骤要求求解方程的非线性系统。在一些解耦方法中,使用固定点技术。但是,牛顿方法一般地收敛得更快,即使每个迭代都更加CPU密集型,也更有效。在本章中,我们处理反应运输模型,并展示如何有效地使用牛顿方法。数值实验说明了替代技术的效率。此外,似乎在化学方程中使用对数导致不良条件矩阵并增加计算成本。

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