摘要翻译：
我们提出了一种对粘性牛顿流体中自推进粒子集合进行动力学模拟的方法。我们将注意力限制在尺寸和速度足够小以至于流体运动处于蠕动流动状态的颗粒上。我们提出了一个简单的自推进粒子模型，并将斯托克动力学方法推广到对此类粒子集合进行动力学模拟。在我们的描述中，每个粒子被视为一个具有定向矢量$\te{p}$的球体，它的运动是由一个力偶极子的作用驱动的，该力偶极子位于离其中心略微偏移的一点上。孤立地说，一个自推进粒子在$\te{p}$的方向上以恒定的速度运动。当它与许多这样的粒子共存时，它与其他粒子的流体动力相互作用改变了它的速度，更重要的是改变了它的取向。结果，粒子的运动是混沌的。我们的模拟并不局限于低粒子浓度，因为我们实现了粒子之间的完全流体动力学相互作用，但我们将粒子的运动限制在二维，以减少计算量。本文报道了在一定浓度范围内，自推进粒子悬浮液的统计特性，如粒子速度分布、对相关函数和取向相关函数。
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英文标题：
《The collective dynamics of self-propelled particles》
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作者：
Vishwajeet Mehandia and Prabhu R. Nott
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最新提交年份：
2007
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分类信息：

一级分类：Physics        物理学
二级分类：Soft Condensed Matter        软凝聚态物质
分类描述：Membranes, polymers, liquid crystals, glasses, colloids, granular matter
膜，聚合物，液晶，玻璃，胶体，颗粒物质
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一级分类：Physics        物理学
二级分类：Statistical Mechanics        统计力学
分类描述：Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变，热力学，场论，非平衡现象，重整化群和标度，可积模型，湍流
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英文摘要：
  We have proposed a method for the dynamic simulation of a collection of self-propelled particles in a viscous Newtonian fluid. We restrict attention to particles whose size and velocity are small enough that the fluid motion is in the creeping flow regime. We have proposed a simple model for a self-propelled particle, and extended the Stokesian Dynamics method to conduct dynamic simulations of a collection of such particles. In our description, each particle is treated as a sphere with an orientation vector $\te{p}$, whose locomotion is driven by the action of a force dipole at a point slightly displaced from its centre. In isolation, a self-propelled particle moves at a constant speed in the direction of $\te{p}$. When it coexists with many such particles, its hydrodynamic interaction with the other particles alters its velocity and, more importantly, its orientation. As a result, the motion of the particle is chaotic. Our simulations are not restricted to low particle concentration, as we implement the full hydrodynamic interactions between the particles, but we restrict the motion of particles to two dimensions to reduce computation. We report the statistical properties of a suspension of self-propelled particles, such as the distribution of particle velocity, the pair correlation function and the orientation correlation function, for a range of the particle concentration.
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PDF链接：
https://arxiv.org/pdf/707.1436