脉动流体动力学模拟中耗散粒子动力学的映射
Mapping of dissipative particle dynamics in fluctuating hydrodynamics simulations
摘要：
耗散粒子动力学（DPD）是一种新的用于复杂流体细观模拟的粒子方法。DPD粒子通常被认为代表真实原子的包，并且DPD模型中探测的物理尺度由DPD变量到对应的物理量的映射确定。然而，这种映射的非唯一性导致了在设置模拟以模仿真实系统和解释结果方面的困难。对于模拟热波动很重要的传输现象（例如，波动流体动力学），一个特别适合于DPD方法的领域，我们建议DPD流体颗粒应被视为仅1）提供一种介质，在该介质中，根据流体动力学定律传递动量和能量，以及2）为浸入DPD流体中的物体提供适当的随机“反冲”，使得这些物体在宏观尺度上表现出正确的波动行为。我们表明，在这种情况下，系统温度的选择和DPD尺度到物理尺度的映射是由粗粒化水平和DPD流体的性质唯一决定的。我们还验证了DPD模拟可以再现颗粒悬浮液中的热波动的宏观效应，通过显示固体颗粒的布朗扩散可以在DPD模拟中以良好的精度计算。
英文摘要：
Dissipative particle dynamics (DPD) is a novel particle method for mesoscale modeling of complex fluids. DPD particles are often thought to represent packets of real atoms, and the physical scale probed in DPD models are determined by the mapping of DPD variables to the corresponding physical quantities. However, the non-uniqueness of such mapping has led to difficulties in setting up simulations to mimic real systems and in interpreting results. For modeling transport phenomena where thermal fluctuations are important (e.g., fluctuating hydrodynamics), an area particularly suited for DPD method, we propose that DPD fluid particles should be viewed as only 1) to provide a medium in which the momentum and energy are transferred according to the hydrodynamic laws and 2) to provide objects immersed in the DPD fluids the proper random "kicks" such that these objects exhibit correct fluctuation behaviors at the macroscopic scale. We show that, in such a case, the choice of system temperature and mapping of DPD scales to physical scales are uniquely determined by the level of coarse-graining and properties of DPD fluids. We also verified that DPD simulation can reproduce the macroscopic effects of thermal fluctuation in particulate suspension by showing that the Brownian diffusion of solid particles can be computed in DPD simulations with good accuracy.
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