Numerical Studies of Flow Between Rotating Coaxial Disks

A new algorithm, which is exceptionally fast for certain choicesof numerical parameters, is described for the study of nonlinear,incompressible flow between two rotating disks. Typical examplesfor Reynolds number R in the range 10 R 2000 are describedand discussed. Comparisons are made with the limited availableresults generated by other methods.     

微极液体在两个多孔圆盘间的MHD流动及其热传导

两个平行的无限大多孔圆盘,圆盘表面有均匀注入时,数值地研究圆盘间不可压缩导电微极流体,在横向外加磁场作用下的轴对称稳定层流.运用von Krmn的相似变换,将非线性运动的控制方程转化为无量纲形式.使用基于有限差分格式的算法,在相应的边界条件下,求解简化后耦合的常微分方程组.讨论Reynolds数、磁场参数、微极参数和Prandtl数,对流动速度和温度分布的影响.在特殊情况下,所得结果与已有文献的工作有着很好的一致性.研究表明,圆盘表面的传热率随着Rynolds数、磁场参数和Prandtl数的增加而增加;剪切应力随着注入的增加而减少,但它随着外部磁场的加强而增加.和Newton流体相比较,微极流体的剪切应力因素较弱,有利于聚合体加工过程中流动和温度的控制.     

热交换多孔圆盘间三阶流体的MHD轴对称流动

在两个具有热交换可渗透的多孔圆盘之间,研究三阶流体的磁流体动力学(MHD)流动.通过适当变换,将偏微分的控制方程转换为常微分方程.采用同伦分析法(HAM)求解转换后的方程.定义了均方残余误差的表达式,并选择了最佳的、收敛的控制参数值.检测了无量纲参数变化时的无量纲速度和温度场.列表显示表面摩擦因数和Nusselt数,并分析了无量纲参数的影响.     

Clustering Nonlinear,Nonstationary Time Series Using BSLEX

Accurate clustering of time series is a challenging problem for data arising from areas such as financial markets, biomedical studies, and environmental sciences, especially when some, or all, of the series exhibit nonlinearity and nonstationarity. When a subset of the series exhibits nonlinear characteristics, frequency domain clustering methods based on higher-order spectral properties, such as the bispectra or trispectra are useful. While these methods address nonlinearity, they rely on the assumption of series stationarity. We propose the Bispectral Smooth Localized Complex EXponential (BSLEX) approach for clustering nonlinear and nonstationary time series. BSLEX is an extension of the SLEX approach for linear, nonstationary series, and overcomes the challenges of both nonlinearity and nonstationarity through smooth partitions of the nonstationary time series into stationary subsets in a dyadic fashion. The performance of the BSLEX approach is illustrated via simulation where several nonstationary or nonlinear time series are clustered, as well as via accurate clustering of the records of 16 seismic events, eight of which are earthquakes and eight are explosions. We illustrate the utility of the approach by clustering S&P 100 financial returns.     

通过可渗透近球体的轴对称流动

提出了可渗透近球体轴对称流动的分析方法.用修正边界条件的办法反映可渗透性.用正规摄动法求解了Stokes方程,达到ε的2阶修正.ε是描述不变形球体半径偏差的小参数.计算了阻力和流量,并从几何方面和表面渗透性方面考查了计算结果.还尝试将此理论应用于过滤供水问题.小型的生态学上重要的水生生物体的过滤器,被模型化为轴对称可渗透物体,用扁球体或近球体建立了该问题的初级模型.     

基于Copula函数的非线性时间序列聚类

时间序列数据的聚类是对面板数据或多维时间序列根据序列相似度进行分组。聚在同一组的时间序列具有相近的模型参数,尤其是当序列较短时聚类后能够得到更精确的参数估计。现存的时间序列聚类方法的距离度量大都基于时间序列的线性假设,但是现实中时间序列通常是非线性的。本文提出了一种基于Copula距离测度的非线性时间序列数据的聚类方法,它利用了Copula函数获取时间序列的非线性相依结构。作为一种非参数的距离度量,基于Copula函数的距离度量能够识别动态相关结构的相似性。大量的模拟实验和实证研究验证了我们所提方法的有效性。     

应用逐次Taylor级数线性化法在多孔伸展界面上求解高对流Maxwell流体的磁流体动力学流动

研究不可压缩的高对流Maxwell(UCM)流体,在多孔伸展界面上作磁流体动力学(MHD)的边界层流动.利用相似变换将控制的偏微分方程,变换为非线性常微分方程.采用逐次Taylor级数线性化方法(STLM)求解该非线性问题.对所显现的参数完成速度分量的计算,介绍了表面摩擦因数的数值结果,并分析了问题所显现参数的变化.     

非牛顿幂级数流体平面泊肃叶流的非线性稳定性*

非牛顿流体在现代工业生产中,广泛地作为加工的对象,因此非牛顿流体的流动稳定性问题有着重要的生产实际背景。本文选择在聚合物加工时将熔体压入成板口模时形成平面泊肃叶流这一生产背景,研究其非线性稳定性问题,计算其亚临界阈值。     

基于摄动法的压敏储层非线性渗流问题研究

研究地层压力变化对渗流特征的影响,对低渗透储层、碳酸盐岩储层,或其他致密性储层的油气开采和储层改造都具有重要意义.在考虑渗流压力梯度平方项存在的前提下,运用摄动法求解的相关理论,将渗透率随压力的变化融入到渗流问题的求解过程中,有效地求解了该类压敏型储层的非线性渗流问题.结果表明,在实际应用中,尤其是在储层压敏性较弱的情况下,可考虑直接用0阶摄动解即可满足较好的计算精度;储层的压敏性越强,越适宜通过用摄动解的修正,来达到精确求解的目的.     

Nonlinear Markov Operators,Discrete Heat Flow,and Harmonic Maps Between Singular Spaces

We develop a theory of harmonic maps f:MN between singular spaces M and N. The target will be a complete metric space (N,d) of nonpositive curvature in the sense of A. D. Alexandrov. The domain will be a measurable space (M,) with a given Markov kernel p(x,dy) on it. Given a measurable map f:MN, we define a new map Pf:MN in the following way: for each xM, the point Pf(x)N is the barycenter of the probability measure p(x,f ^–1(dy)) on N. The map f is called harmonic on DM if Pf=f on D. Our theory is a nonlinear generalization of the theory of Markov kernels and Markov chains on M. It allows to construct harmonic maps by an explicit nonlinear Markov chain algorithm (which under suitable conditions converges exponentially fast). Many smoothing and contraction properties of the linear Markov operator P _M,R carry over to the nonlinear Markov operator P=P _M,N . For instance, if the underlying Markov kernel has the strong Lipschitz Feller property then all harmonic maps will be Lipschitz continuous.     

Global Convergence of a Nonlinear Programming Method Using Convex Approximations

The method of moving asymptotes (MMA) and its globally convergent extension SCP (sequential convex programming) are known to work well for certain problems arising in structural optimization. In this paper, the methods are extended for a general mathematical programming framework and a new scheme to update certain penalty parameters is defined, which leads to a considerable improvement in the performance. Properties of the approximation functions are outlined in detail. All convergence results of the traditional methods are preserved.     

可渗透收缩薄膜引起的三维

研究可渗透收缩薄膜上的不稳定粘性流动.通过相似变换得到相似方程.在不同的不稳定参数、质量吸入参数、收缩参数、Prandtl数下,数值地求解相似方程,得到速度和温度的分布,以及表面摩擦因数和Nusselt数等.结果发现,与不稳定的伸展薄膜不同,在质量吸入参数和不稳定参数的某一范围内,可渗透收缩薄膜上的不稳定流动存在双重解.     

应用对称求非线性方程精确解的一种新方法

提出了一种寻找变系数非线性方程精确解的新方法—相容方程法,利用该方法求出了变系数非线性KP方程的精确解,从而证明了这种方法是十分有效的.     

Observing Pattern Dynamics in Nonlinear Optical Systems Using the Video-sampling Method

We present a method of synchronizing a shutter for a video camera that allows an instantaneous slow-motion visualization of fast repetitive processes with a time scaling factor of up to 1,000,000 or more. The method uses standard, unmodified CCIR or EIA video equipment, including video cassette recorders for low-cost recording. A number of examples showing spatio-temporal dynamics in nonlinear optical systems is shown, including magneto-optical beam-splitting, drifting hexagons and phase synchronization of coupled solid-state lasers.     

A Hessian Regularized Nonlinear Time Series Model

We introduce a nonparametric nonlinear time series model. The novel idea is to fit a model via penalization, where the penalty term is an unbiased estimator of the integrated Hessian of the underlying function. The underlying model assumption is very general: it has Hessian almost everywhere in its domain. Numerical experiments demonstrate that our model has better predictive power: if the underlying model complies with an existing parametric/semiparametric form (e.g., a threshold autoregressive model (TAR), an additive autoregressive model (AAR), or a functional coefficient autoregressive model (FAR)), our model performs comparably; if the underlying model does not comply with any preexisting form, our model outperforms in nearly all simulations. We name our model a Hessian regularized nonlinear model for time series (HRM). We conjecture on theoretical properties and use simulations to verify. Our method can be viewed as a way to generalize splines to high dimensions (when the number of variates is more than three), under which an analogous analytical derivation cannot work due to the curse of dimensionality. Supplemental materials are provided, and will help readers reproduce all results in the article.     

Estimating Functions for Nonlinear Time Series Models

This paper discusses the problem of estimation for two classes of nonlinear models, namely random coefficient autoregressive (RCA) and autoregressive conditional heteroskedasticity (ARCH) models. For the RCA model, first assuming that the nuisance parameters are known we construct an estimator for parameters of interest based on Godambe's asymptotically optimal estimating function. Then, using the conditional least squares (CLS) estimator given by Tjøstheim (1986, Stochastic Process. Appl., 21, 251–273) and classical moment estimators for the nuisance parameters, we propose an estimated version of this estimator. These results are extended to the case of vector parameter. Next, we turn to discuss the problem of estimating the ARCH model with unknown parameter vector. We construct an estimator for parameters of interest based on Godambe's optimal estimator allowing that a part of the estimator depends on unknown parameters. Then, substituting the CLS estimators for the unknown parameters, the estimated version is proposed. Comparisons between the CLS and estimated optimal estimator of the RCA model and between the CLS and estimated version of the ARCH model are given via simulation studies.     

分数阶SEIR传染病模型的残差幂级数解法

SEIR传染病模型在研究传染病和社交网络的信息传播等方面具有重要的应用背景,分数阶SEIR传染病模型对于这些动态系统的传播过程描述更加确切,但是分数阶SEIR模型难于求解.给出一种求解该模型的残差幂级数方法.首先,将分数阶SEIR模型中的S(t)、E(t)、I(t)和R(t)分别用广义泰勒级数展开至k项;再将展开后的表达式带入到分数阶SEIR模型中;利用残差为0来求解未知的系数a_k、b_k、c_k、d_k,得到分数阶SEIR模型的一种级数形式的近似解析解.通过与同伦分析变换法得到的解进行对比,结果表明,残差幂级数法在求解分数阶SEIR模型更有效,其误差更小.     

非线性系统双模鲁棒预测控制: 不变集切换方法

提出了一种基于不变集切换的非线性系统鲁棒预测控制算法.采用分段蕴含方法将非线性系统动态用一组线性变参数(LPV)系统动态包裹;计算出非线性系统的平衡面,对于每个LPV蕴含模型,针对相应的平衡点构造多面体不变集,得到覆盖非线性系统平衡面的一组相互重叠的不变集;在线根据系统当前状态所处的不变集和LPV区间切换控制律,最终保证闭环系统的稳定性.与传统的非线性预测控制相比,这种方法在构造不变集和确定控制律的计算都是离线进行,而在线只需根据当前状态切换控制律即可,从而避免了求解复杂的非凸非线性规划,在很大程度上降低了在线计算量.