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A deterministic Lagrangian particle separation-based method for advective-diffusion problems

机译:对流扩散问题的基于确定性拉格朗日粒子分离的方法

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A simple and robust Lagrangian particle scheme is proposed to solve the advective-diffusion transport problem. The scheme is based on relative diffusion concepts and simulates diffusion by regulating particle separation. This new approach generates a deterministic result and requires far less number of particles than the random walk method. For the advection process, particles are simply moved according to their velocity. The general scheme is mass conservative and is free from numerical diffusion. It can be applied to a wide variety of advective-diffusion problems, but is particularly suited for ecological and water quality modelling when definition of particle attributes (e.g., cell status for modelling algal blooms or red tides) is a necessity. The basic derivation, numerical stability and practical implementation of the NEighborhood Separation Technique (NEST) are presented. The accuracy of the method is demonstrated through a series of test cases which embrace realistic features of coastal environmental transport problems. Two field application examples on the tidal flushing of a fish farm and the dynamics of vertically migrating marine algae are also presented.
机译:为了解决对流扩散输运问题,提出了一种简单而鲁棒的拉格朗日粒子方案。该方案基于相对扩散概念,并通过调节颗粒分离来模拟扩散。与随机游走方法相比,这种新方法可产生确定性的结果,并且所需的粒子数量要少得多。对于平流过程,仅根据粒子的速度移动它们。一般方案是质量保守的,没有数值扩散。它可以应用于各种对流扩散问题,但是当需要定义粒子属性(例如,用于模拟藻华或赤潮的细胞状态)时,它尤其适用于生态和水质建模。介绍了近邻分离技术(NEST)的基本推导,数值稳定性和实际实现。通过一系列包含沿海环境运输问题现实特征的测试案例,证明了该方法的准确性。还提供了两个关于养鱼场潮汐冲洗和垂直迁移海藻动力学的现场应用实例。

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