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KRYLOV IMPLICIT INTEGRATION FACTOR METHOD FOR A CLASS OF STIFF REACTION-DIFFUSION SYSTEMS WITH MOVING BOUNDARIES

机译:Krylov隐式集成因子方法,用于具有移动边界的一类硬反应扩散系统

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The systems of reaction-diffusion equations coupled with moving boundaries defined by Stefan condition have been widely used to describe the dynamics of spreading population. There are several numerical difficulties to efficiently handle such systems. Firstly extremely small time steps are usually demanded due to the stiffness of the system. Secondly it is always difficult to efficiently and accurately handle the moving boundaries. To overcome these difficulties, we first transform the one-dimensional problem with a moving boundary into a system with a fixed computational domain, and then introduce four different temporal schemes: Runge-Kutta, Crank-Nicolson, implicit integration factor (IIF) and Krylov IIF for handling such stiff systems. Numerical examples are examined to illustrate the efficiency, accuracy and consistency for different approaches, and it can be shown that Krylov IIF is superior to other three approaches in terms of stability and efficiency by direct comparison.
机译:耦合的反应扩散方程和由Stefan条件限定的移动边界的系统已被广泛用于描述扩散群体的动态。有效地处理这种系统有几个数值困难。首先,由于系统的刚度,通常需要极小的时间步骤。其次,始终难以高效,准确地处理移动边界。为了克服这些困难,我们首先将移动边界转换为具有固定计算域的系统,然后引入四个不同的时间方案:Runge-Kutta,Crank-Nicolson,隐式集成因子(IIF)和Krylov iif处理如此僵硬的系统。检查数值例子以说明不同方法的效率,准确性和一致性,并且可以通过直接比较来表明Krylov IIF在稳定性和效率方面优于其他三种方法。

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