基于MATLAB的布朗运动数值模拟

运用MATLAB软件平台模拟T--维布朗运动的动态画面。并定义了粒子群分布离散度尺,研究迭代步数后,噪声强度系数。与粒子群分布离散度R的关系,通过曲线拟合得到关系式R∝√k与R∝Cs。     

纳米流体的聚集结构和导热系数模拟

本文根据布朗运动理论模拟纳米粒子在流体中的聚集过程，运用分形理论描述纳米粒子团的结构．考虑纳米粒子的运动传热，建立纳米流体的导热系数模型，理论预测值与实验结果显现了良好的一致性。     

基于自回归模型的光阱中粒子运动模拟

通过分析光阱中颗粒位移信号特性, 建立描述粒子受限布朗运动过程的自回归模型, 进而提出了一种基于自回归模型的光阱中颗粒运动信号模拟的新方法. 对半径为1 μm的粒子处于光阱刚度分别为10, 20, 50 pN/μm 光阱时的位移信号进行了模拟, 得到的模拟位移信号的自相关函数与理论值相一致. 为了进一步阐明自回归模型的有效性, 在相同光阱参数下, 分别采用自回归模型与蒙特卡罗方法模拟光阱中微粒的位移信号, 采用功率谱法分别对两种模拟方法所得的微粒位移标定光阱刚度, 结果表明自回归模型方法能够取得和蒙特卡洛法相同的精度. 因此, 本文为分析光阱中粒子的随机运动提出了一种新的模拟方法, 可以用来对光阱中的噪声及特性进行分析. 关键词： 光阱 布朗运动 信号模拟 自回归模型     

一种根据布朗运动测量玻尔兹曼常量的新方法

利用显微镜和CCD图像采集工具对聚丙烯小球的布朗运动进行了研究,通过拍摄粒子运动图像并利用MATLAB程序进行图片处理,读取每一时刻布朗粒子的坐标.基于对大量数据的统计分析,计算出了玻尔兹曼常量,与理论值的相对误差约为4%.同时,验证了布朗运动位移服从正态分布以及粒子位移均方值与时间成正比的关系.     

电流变液中悬浮粒子的布朗运动与其聚集之间关系

在外电场作用下,电流变液中粒子链的聚集与其布朗运动密切相关。为了具体分析这种关系,采用不分离但有相互运动的双球构成的系统去简化粒子链。通过分析双球系统布朗运动特性,得到其无规运动轨迹维数小于2,大量这样的系统在平面中就不可能均匀分布。这说明由于存在布朗运动,在外电场中电流变液中粒子链必然相互聚集,即形成高密度区与低密度区。 关键词：     

分形多孔介质的粒子扩散特点(Ⅱ)

本文进一步讨论了粒子在分形结构中的扩散,首先计算测定了各分形结构的谱维数,然后对其布朗运动特点进 行了分析讨论,最后模拟得到了粒子扩散概率分布,它们表现出很多有趣的特征:不均匀性,内含空洞和标度性等.这些 结果可以更好地了解气体在分形结构中的扩散。     

光滑粒子动力学SPH方法应力不稳定性的一种改进方案

光滑粒子动力学方法是一种拉格朗日型无网格粒子方法,在模拟大变形和自由表面流方面具有特殊的优势,已经在工程和科学领域得到了广泛的应用．然而,长期以来,传统光滑粒子动力学方法一直受到应力不稳定性的困扰,从而限制了它的进一步发展和应用．应力不稳定性的根本原因在于应力状态与核函数的不匹配：负压状态下粒子间产生吸引力,吸引力随着粒子间距的减小而增大,导致拉伸不稳定性;正压状态下粒子间产生排斥力,排斥力随着粒子间距的减小而先增大后减小,导致压缩不稳定性．本文通过改进光滑粒子动力学方法的核函数和离散格式,使得无论在正压还是负压状态下粒子间的作用力恒为排斥力,且排斥力随着粒子间距的减小而增大,从而防止粒子聚集等现象,解决应力不稳定问题．分别使用改进前后的光滑粒子动力学方法模拟两个典型的应力不稳定算例,结果表明本文的改进方法能够有效地消除应力不稳定性．     

布朗运动的观察

布朗运动的观察宫建平（山西榆次晋中师专物理系０３０６００）布朗运动现象是否明显主要与两个因素有关，一是液体分子热运动的剧烈程度，一是做布朗运动的粒子的大小和形状等．文献［１—２］提出的改进方法效果要好一些．这些方法中选用的做布朗运动粒子是花粉、碳素墨...     

用于层析粒子图像测速的模拟粒子场成像

对层析粒子图像测速(PIV)技术中示踪粒子成像部分进行理论分析,并结合真实风洞的相应参数,通过搭建模拟粒子成像平台的方法来进行研究。设计了一套体积为80 mm×100 mm×100 mm的激光照明系统,以提供粒子场的入射光强。建立了示踪粒子的三维成像模型,从而得到层析PIV系统的模拟图像。分析了影响PIV系统成像质量的相关因素。在单像素粒子数为0.007 7的情况下,通过真实粒子图像和模拟粒子图像比较,验证了该方法的正确性。     

弱噪声极限下二维布朗运动的随机共振现象

在弱噪声极限下，应用多维Fokker-Planck方程的与时间有关问题方面的理论，推导了对称双稳势阱中二维布朗粒子的概率跃迁速率，并基于绝热近似理论研究了弱噪声极限下受小幅低频周期力驱动的二维布朗运动的随机共振现象.与以前的结果相比，所得到的信噪比与阻尼系数的大小无关.精确的数值模拟结果进一步说明了所得的信噪比的适用性. 关键词： 二维布朗运动 弱噪声极限 随机共振 信噪比     

A Brownian motion version of the directed polymer problem

Consider a Brownian particle in three dimensions in a random environment. The environment is determined by a potential random in space and time. It is shown that at small noise the large-time behavior of the particle is diffusive. The diffusion constant depends on the environment. This work generalizes previous results for random walk in a random environment. In these results the diffusion constant does not depend on the environment.     

An invariance principle for reversible Markov processes. Applications to random motions in random environments

We present an invariance principle for antisymmetric functions of a reversible Markov process which immediately implies convergence to Brownian motion for a wide class of random motions in random environments. We apply it to establish convergence to Brownian motion (i) for a walker moving in the infinite cluster of the two-dimensional bond percolation model, (ii) for ad-dimensional walker moving in a symmetric random environment under very mild assumptions on the distribution of the environment, (iii) for a tagged particle in ad-dimensional symmetric lattice gas which allows interchanges, (iv) for a tagged particle in ad-dimensional system of interacting Brownian particles. Our formulation also leads naturally to bounds on the diffusion constant.     

Mean first passage time of active Brownian particle in one dimension

We investigate the mean first passage time of an active Brownian particle in one dimension using numerical simulations. The activity in one dimension is modelled as a two state model; the particle moves with a constant propulsion strength but its orientation switches from one state to other as in a random telegraphic process. We study the influence of a finite resetting rate r on the mean first passage time to a fixed target of a single free active Brownian particle and map this result using an effective diffusion process. As in the case of a passive Brownian particle, we can find an optimal resetting rate r* for an active Brownian particle for which the target is found with the minimum average time. In the case of the presence of an external potential, we find good agreement between the theory and numerical simulations using an effective potential approach.     

Spherical particle Brownian motion in viscous medium as non-Markovian random process

The Brownian motion of a spherical particle in an infinite medium is described by the conventional methods and integral transforms considering the entrainment of surrounding particles of the medium by the Brownian particle. It is demonstrated that fluctuations of the Brownian particle velocity represent a non-Markovian random process. The features of Brownian motion in short time intervals and in small displacements are considered.     

Retainability of canonical distributions for a Brownian particle controlled by a time-dependent harmonic potential

The retainability of canonical distributions for a Brownian particle controlled by a time-dependent harmonic potential is investigated in the overdamped and underdamped situations, respectively. Because of different time scales, the overdamped and underdamped Langevin equations (as well as the corresponding Fokker-Planck equations) lead to distinctive restrictions on protocols maintaining canonical distributions. Two special cases are analyzed in details: First, a Brownian particle is controlled by a time-dependent harmonic potential and embedded in medium with constant temperature; Second, a Brownian particle is controlled by a timedependent harmonic potential and embedded in a medium whose temperature is tuned together with the potential stiffness to keep a constant effective temperature of the Brownian particle. We find that the canonical distributions are usually retainable for both the overdamped and underdamped situations in the former case. However, the canonical distributions are retainable merely for the overdamped situation in the latter case. We also investigate general time-dependent potentials beyond the harmonic form and find that the retainability of canonical distributions depends sensitively on the specific form of potentials.     

Application of integral transforms to a description of the Brownian motion by a non-Markovian random process

The one-dimensional Brownian motion and the Brownian motion of a spherical particle in an infinite medium are described by the conventional methods and integral transforms considering the entrainment of surrounding particles of the medium by the Brownian particle. It is demonstrated that fluctuations of the Brownian particle velocity represent a non-Markovian random process. A harmonic oscillator in a viscous medium is also considered within the framework of the examined model. It is demonstrated that for rheological models, random dynamic processes are also non-Markovian in character. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Fizika, No. 2, pp. 66–74, February, 2009.     

Asymptotic motion of a classical particle in a random potential in two dimensions: Landau model

We consider the motion of a classical particle in a random isotropic potential arising from uniformly distributed scatterers in two dimensions. We prove that in the weak coupling limit the velocity process of the particle converges in distribution to Brownian motion on a surface of constant speed, i.e. on the circle. The resulting equation for the probability density of the particle is related to the Landau equation in plasmas.also: Department of PhysicsWork supported in part by National Science Foundation Grant No. DMS-85-12505 and AFOSR No. C010     

Brownian motion at short time scales

Brownian motion has played important roles in many different fields of science since its origin was first explained by Albert Einstein in 1905. Einstein's theory of Brownian motion, however, is only applicable at long time scales. At short time scales, Brownian motion of a suspended particle is not completely random, due to the inertia of the particle and the surrounding fluid. Moreover, the thermal force exerted on a particle suspended in a liquid is not a white noise, but is colored. Recent experimental developments in optical trapping and detection have made this new regime of Brownian motion accessible. This review summarizes related theories and recent experiments on Brownian motion at short time scales, with a focus on the measurement of the instantaneous velocity of a Brownian particle in a gas and the observation of the transition from ballistic to diffusive Brownian motion in a liquid.     

Mean-square displacement of a stochastic oscillator: Linear vs quadratic noise

Using the Langevin equations, we calculated the stationary second-order moment (mean-square displacement) of a stochastic harmonic oscillator subject to an additive random force (Brownian motion in a parabolic potential) and to different types of multiplicative noise (random frequency or random damping or random mass). The latter case describes Brownian motion with adhesion, where the particles of the surrounding medium may adhere to the oscillator for some random time after the collision. Since the mass of the Brownian particle is positive, one has to use quadratic (positive) noise. For all types of multiplicative noise considered, replacing linear noise by quadratic noise leads to an increase in stability.     

Energy losses in a flashing ratchet with different potential well shapes

A flashing ratchet is considered, which involves periodic two-well potentials fluctuating via random shifts of one half-period. Such a Brownian motor exhibits the maximum efficiency tending to unity, provided one of the barriers blocks the reverse movement of a Brownian particle and the potential wells have the same curvatures and the half-period-shifted minima. Analytical expressions are derived for the energy losses arising from a discrepancy between potential well curvatures and a deviation of the inter-well distance from a half-period. The dependences of the energy losses on the parameters of the model are analyzed.