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arXiv 0910.5748cond-mat.softcond-mat.mes-hallcond-mat.stat-mechphysics.flu-dyn
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细观尺度下流体-结构动力学的随机浸没边界方法

A Stochastic Immersed Boundary Method for Fluid-Structure Dynamics at Microscopic Length Scales

P. J. Atzberger, P. R. Kramer, C. S. Peskin

摘要:

在这项工作中,它示出了如何浸没边界法(Peskin 2002)的建模柔性结构浸没在流体中可以扩展到包括热波动。本文提出了一种随机数值方法,它通过系统地处理流体和浸没结构在长时间步长内的最快动力学的统计贡献来处理方程组中的刚度。数值方法的一个重要特征是可以采取时间步长,其中流体的自由度完全欠解析、部分解析或完全解析,同时保持良好的精度水平。在这些制度的误差估计给出的方法。此外,还进行了一些理论和数值检查,以评估其物理保真度。对于一个保守力,该方法被发现模拟粒子与正确的玻尔兹曼平衡统计。三维数值模拟结果表明,该方法模拟的浸没粒子扩散过程具有正确的物理参数标度。该方法还示出,以再现一个众所周知的流体动力学效应的布朗粒子,其中的速度自相关函数表现出代数τ ^(-3/2)衰减很长一段时间。一些初步的结果更复杂系统,展示了一些潜在的应用领域的方法。

英文摘要:

In this work it is shown how the immersed boundary method of (Peskin2002) for modeling flexible structures immersed in a fluid can be extended to include thermal fluctuations. A stochastic numerical method is proposed which deals with stiffness in the system of equations by handling systematically the statistical contributions of the fastest dynamics of the fluid and immersed structures over long time steps. An important feature of the numerical method is that time steps can be taken in which the degrees of freedom of the fluid are completely underresolved, partially resolved, or fully resolved while retaining a good level of accuracy. Error estimates in each of these regimes are given for the method. A number of theoretical and numerical checks are furthermore performed to assess its physical fidelity. For a conservative force, the method is found to simulate particles with the correct Boltzmann equilibrium statistics. It is shown in three dimensions that the diffusion of immersed particles simulated with the method has the correct scaling in the physical parameters. The method is also shown to reproduce a well-known hydrodynamic effect of a Brownian particle in which the velocity autocorrelation function exhibits an algebraic tau^(-3/2) decay for long times. A few preliminary results are presented for more complex systems which demonstrate some potential application areas of the method.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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