永磁同步风力发电机随机分岔现象的全局分析

永磁同步风力发电机在运行过程中不可避免地会受到风能的随机干扰,本文建立了在输入机械转矩存在随机干扰情况下永磁同步风力发电机的数学模型,采用胞映射方法分析了随机干扰强度变化时系统全局结构的演化行为,并通过数值模拟对理论分析进行验证.研究结果表明,随着随机干扰强度的增大,系统中会出现随机内部激变和随机边界激变,即由于随机吸引子与其吸引域内的随机鞍发生碰撞而产生的随机分岔现象和由于随机吸引子与其吸引域边界发生碰撞而产生的随机分岔现象.研究结果揭示了随机干扰对永磁同步风力发电机运行性能影响的机理,为永磁同步风力发电系统的运行和设计提供了理论依据.     

Modulated noisy biological dynamics: Three examples

Three examples of noisy biological dynamics modulated by a periodic signal are discussed. A minimal neuron model driven by stochastic noise and small periodic force show a firing statistic comparable with stochastic resonance as demonstrated in bistable systems. Similar results are obtained from responses to periodic vibrotactile stimulation on higher-order neuronal units of the somatosensory pathway. Finally, results from a bistable visual perception task exhibiting stochastic resonance are reported.     

A stochastic mixed finite element heterogeneous multiscale method for flow in porous media

A computational methodology is developed to efficiently perform uncertainty quantification for fluid transport in porous media in the presence of both stochastic permeability and multiple scales. In order to capture the small scale heterogeneity, a new mixed multiscale finite element method is developed within the framework of the heterogeneous multiscale method (HMM) in the spatial domain. This new method ensures both local and global mass conservation. Starting from a specified covariance function, the stochastic log-permeability is discretized in the stochastic space using a truncated Karhunen–Loève expansion with several random variables. Due to the small correlation length of the covariance function, this often results in a high stochastic dimensionality. Therefore, a newly developed adaptive high dimensional stochastic model representation technique (HDMR) is used in the stochastic space. This results in a set of low stochastic dimensional subproblems which are efficiently solved using the adaptive sparse grid collocation method (ASGC). Numerical examples are presented for both deterministic and stochastic permeability to show the accuracy and efficiency of the developed stochastic multiscale method.     

一类线性阻尼振子的随机共振研究

针对随机有色噪声参数激励和周期调制噪声外激励联合作用下的线性阻尼振子,利用Shapiro-Loginov公式推导了系统响应的一、二阶稳态矩的解析表达式.发现这类系统存在传统的随机共振、广义的随机共振和“真正”的随机共振;当乘性噪声强度和调制噪声强度的比值大于等于1时,系统出现随机多共振现象.通过数值计算的系统响应功率谱,验证了理论分析结果. 关键词： 随机共振 周期调制的噪声 线性阻尼振子     

具有固有频率涨落的记忆阻尼线性系统的随机共振

研究了在内噪声、外噪声(固有频率涨落噪声)及周期激励信号共同作用下具有指数型记忆阻尼的广义Langevin方程的共振行为.首先将其转化为等价的三维马尔可夫线性系统,再利用Shapiro-Loginov公式和Laplace变换导出系统响应一阶矩和稳态响应振幅的解析表达式.研究发现,当系统参数满足Routh-Hurwitz稳定条件时,稳态响应振幅随周期激励信号频率、记忆阻尼及外噪声参数的变化存在"真正"随机共振、传统随机共振和广义随机共振,且随机共振随着系统记忆时间的增加而减弱.数值模拟计算结果表明系统响应功率谱与理论结果相符.     

Stochastic stability of a gyropendulum under random vertical support excitation

The mean square stability of a gyropendulum under random vertical support excitation is considered. The intensity and the correlation time of the stochastic excitations are assumed to be small in order to obtain approximate analytical results. The stochastic averaging procedure of Stratonovich and Khasminskii is used to establish the drift and diffusion coefficients in the corresponding Itô equation. Explicit results are obtained for stochastic stability boundaries.     

耦合Duffing-van der Pol系统的随机稳定性及控制

应用拟Hamilton系统的随机平均法和随机稳定化策略，研究了高斯白噪声激励下耦合Duffing-van der Pol系统的随机稳定性及其在半无限长时间内的稳定性控制问题.结果表明，适当地控制参数可有效实现随机稳定化. 关键词： 随机平均法 拟Hamilton系统 Lyapunov指数 随机最优控制     

Stochastic processes in rheology

Various stochastic differential equations arising in rheology are presented. Their phenomenological derivation and some of their results are outlined. Rheology appears as a source of stochastic problems and as a test for the applicability of methods developed in the theory of stochastic processes.Dedicated to Professor Harry Thomas on the occasion of his 60th birthday     

Noise-induced synchronous stochastic oscillations in small scale cultured heart-cell networks

This paper reports that the synchronous integer multiple oscillations of heart-cell networks or clusters are observed in the biology experiment.The behaviour of the integer multiple rhythm is a transition between super-and subthreshold oscillations,the stochastic mechanism of the transition is identified.The similar synchronized oscillations are theoretically reproduced in the stochastic network composed of heterogeneous cells whose behaviours are chosen as excitable or oscillatory states near a Hopf bifurcation point.The parameter regions of coupling strength and noise density that the complex oscillatory rhythms can be simulated are identified.The results show that the rhythm results from a simple stochastic alternating process between super-and sub-threshold oscillations.Studies on single heart cells forming these clusters reveal excitable or oscillatory state nearby a Hopf bifurcation point underpinning the stochastic alternation.In discussion,the results are related to some abnormal heartbeat rhythms such as the sinus arrest.     

Stochastic resonance and chaotic resonance in bimodal maps: A case study

We present the results of an extensive numerical study on the phenomenon of stochastic resonance in a bimodal cubic map. Both Gaussian random noise as well as deterministic chaos are used as input to drive the system between the basins. Our main result is that when two identical systems capable of stochastic resonance are coupled, the SNR of either system is enhanced at an optimum coupling strength. Our results may be relevant for the study of stochastic resonance in biological systems.     

Stochastic synchronization of coupled neural networks with intermittent control

In this Letter, we study the exponential stochastic synchronization problem for coupled neural networks with stochastic noise perturbations. Based on Lyapunov stability theory, inequality techniques, the properties of Weiner process, and adding different intermittent controllers, several sufficient conditions are obtained to ensure exponential stochastic synchronization of coupled neural networks with or without coupling delays under stochastic perturbations. These stochastic synchronization criteria are expressed in terms of several lower-dimensional linear matrix inequalities (LMIs) and can be easily verified. Moreover, the results of this Letter are applicable to both directed and undirected weighted networks. A numerical example and its simulations are offered to show the effectiveness of our new results.     

Discrete-time movement model of a group of trains on a rail line with stochastic disturbance

This paper presents a discrete-time model to describe the movements of a group of trains, in which some operational strategies, including traction operation, braking operation and impact of stochastic disturbance, are defined. To show the dynamic characteristics of train traffic flow with stochastic disturbance, some numerical experiments on a railway line are simulated. The computational results show that the discrete-time movement model can well describe the movements of trains on a rail line with the moving-block signalling system. Comparing with the results of no disturbance, it finds that the traffic capacity of the rail line will decrease with the influence of stochastic disturbance. Additionally, the delays incurred by stochastic disturbance can be propagated to the subsequent trains, and then prolong their traversing time on the rail line. It can provide auxiliary information for rescheduling trains when the stochastic disturbance occurs on the railway.     

Does quantum mechanics accept a stochastic support?

Arguments are given in favor of a stochastic theory of quantum mechanics, clearly distinguishable from Brownian motion theory. A brief exposition of the phenomenological theory of stochastic quantum mechanics is presented, followed by a list of its main results and perspectives. A possible answer to the question about the origin of stochasticity is given in stochastic electrodynamics by assigning a real character to the vacuum radiation field. This theory is shown to reproduce important quantum mechanical results, some of which are presented explicitly to illustrate its potentialities. Finally the main problems and some perspectives of research within stochastic electrodynamics are discussed.     

Universality Class in Abelian Sandpile Models with Stochastic Toppling Rules

We present a stochastic critical slope sandpile model, where the amount of grains that fall in an overturning event is stochastic variable. The model is local, conservative, and Abelian. We apply the moment analysis to evaluate critical exponents and finite size scaling method to consistently test the obtained results. Numerical results show that this model, Oslo model, and one-dimensional Abelian Manna model have the same critical behavior although the three models have different stochastic toppling rules, which provides evidences suggesting that Abelian sandpile models with different stochastic toppling rules are in the same universality class.     

Universality Class in Abelian Sandpile Models with Stochastic Toppling Rules

We present a stochastic critical slope sandpile model, where the amount of grains that fall in an overturning event is stochastic variable. The model is local, conservative, and Abelian. We apply the moment analysis to evaluate critical exponents and finite size scaling method to consistently test the obtained results. Numerical results show that this model, Oslo model, and one-dimensional Abelian Manna model have the same critical behavior although the three models have different stochastic toppling rules, which provides evidences suggesting that Abelian sandpile models with different stochastic toppling rules are in the same universality class.     

Laboratory evidence for stochastic plasma-wave growth

The first laboratory confirmation of stochastic growth theory is reported. Floating potential fluctuations are measured in a vacuum arc centrifuge using a Langmuir probe. Statistical analysis of the energy density reveals a lognormal distribution over roughly 2 orders of magnitude, with a high-field nonlinear cutoff whose spatial dependence is consistent with the predicted eigenmode profile. These results are consistent with stochastic growth and nonlinear saturation of a spatially extended eigenmode, the first evidence for stochastic growth of an extended structure.     

改进的随机轨道模型

在随机轨道模型中,由于气相脉动速度对分散相颗粒作用的间歇性,使得井非在控制体内轨道上的每一点都可以代表该轨道参与颗粒相平均特性的统计计算,从而出现随机轨道模型往往低估颗粒相湍流脉动的情况．为此,本文提出了一种改进的随机轨道模型,在该模型中,分散相的时平均量在由其自身湍流脉动所确定的随机轨道上输运．与常用的随机轨道模型相比,其具有计算量小、计算结果合理且易于得到和分散相入口湍流脉动状况易于考虑等特点．对一简单已知流场的预报结果合理正确,克服了常用的随机轨道模型低估颗粒相湍流脉动的困难．     

Stability analysis of nonlinear stochastic differential delay systems under impulsive control

In this Letter, we study the stability of nonlinear stochastic differential delay systems under impulsive control. First, we construct an impulsive control for a nonlinear stochastic differential delay system. Then, the equivalent relation between the stability of the nonlinear stochastic differential delay system under impulsive control and that of a corresponding nonlinear stochastic differential delay system without impulses is established. Third, some sufficient conditions ensuring various stabilities of the nonlinear stochastic differential delay systems under impulsive control are obtained. Finally, an example is also discussed to illustrate the effectiveness of the obtained results.     

动态随机最短路径算法研究

静态最短路径问题已经得到很好解决, 然而现实中的网络大多具有动态性和随机性. 网络弧和节点的状态及耗费不仅具有不确定性且相互关联, 弧和节点的耗费都服从一定的概率分布, 因此把最短路径问题看作是一个动态随机优化问题更具有一般性. 文中分析了网络弧和节点的动态随机特性及其相互关系, 定义了动态随机最短路径; 给出了动态随机最短路径优化数学模型, 提出了一种动态随机最短路径遗传算法; 针对网络的拓扑特性设计了高效合理的遗传算子. 实验结果表明, 文中提出的模型和算法能有效地解决动态随机最短路径问题, 可以运用到交通、通信等网络的网络流随机优化问题中.