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Random walk particle tracking simulations of non-Fickian transport in heterogeneous media

机译:异构介质中非菲克运量的随机游动粒子跟踪模拟

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摘要

Derivations of continuum nonlocal models of non-Fickian (anomalous) transport require assumptions that might limit their applicability. We present a particle-based algorithm, which obviates the need for many of these assumptions by allowing stochastic processes that represent spatial and temporal random increments to be correlated in space and time, be stationary or non-stationary, and to have arbitrary distributions. The approach treats a particle trajectory as a subordinated stochastic process that is described by a set of Langevin equations, which represent a continuous time random walk (CTRW). Convolution-based particle tracking (CBPT) is used to increase the computational efficiency and accuracy of these particle-based simulations. The combined CTRW-CBPT approach enables one to convert any particle tracking legacy code into a simulator capable of handling non-Fickian transport.
机译:非菲克(异常)运输的连续非局部连续模型的推导需要假设,可能会限制其适用性。我们提出了一种基于粒子的算法,该算法通过允许表示空间和时间随机增量的随机过程在空间和时间上相关,固定或不固定以及具有任意分布,从而消除了对这些假设的要求。该方法将粒子轨迹视为由一组Langevin方程描述的从属随机过程,该方程代表连续时间随机游走(CTRW)。基于卷积的粒子跟踪(CBPT)用于提高这些基于粒子的模拟的计算效率和准确性。结合使用CTRW-CBPT的方法,可以将任何跟踪粒子的遗留代码转换成能够处理非费克式传输的模拟器。

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