液浮转子微陀螺筒间流动阻力矩参数影响

建立简化计算模型,将一种具有空间指数收敛特性的谱元-Fourier法引入复杂的液浮转子微陀螺筒间流动的直接数值模拟。对于柱坐标系下不可压缩Navier-Stokes方程,在子午面的径向和轴向采用Galerkin谱元法,进行标准化的Gauss-Lobatto-Legendre节点展开,在周向采用Fourier级数展开法。设定基准算例,计算分析了高径比、旋转速度和黏性系数等参数对内筒侧面和内筒端面阻力矩的影响。结果表明,两种阻力矩都随这些参数的增大而增大,且对总阻力矩的贡献量级相当。     

Adaptive selection of parameters for precise computation of matrix exponential based on padé approximation

讨论了基于Pad\'{e}逼近的矩阵指数精细积分方法中加权系数N 和展开项数q的自适应选择问题. 参数(N,q)的选择直接影响到矩阵指数计算的精度和效 率. 采用矩阵函数逼近理论，研究了参数N和q的增加对精度的影响程度，据此，提出了 参数(N,q)优化组合的递推自适应选择方法. 该方法可以根据矩阵本身的性态选择合适的参 数(N,q),而参数选择的计算量与矩阵指数的计算量相比几乎可以忽略，这对于增强矩阵指 数精细积分方法的适应性和提高计算效率是很有益处的. 算例验证了该方法的正确性和有效性.     

OGY法实现混沌控制的参数辩识研究

给出了在系统方程未知情况下，采用OGY控制策略，通过混沌的部分测试信息辩识控制参数的方法，并对Duffing方程及强迫Brusselator振子方程的参数辩识及混沌控制进行了数值计算；讨论了使用这一方法实现控制时的一些关键问题，给出了实现控制的一些重要参数；发现了对Duffing方程使用同一参数辩识值，可将混沌控制到不同的一倍周期轨道及高倍周期轨道上的新现象。     

多自由度参激系统稳定性的数值分析

提出多自由度周期参激系统稳定性的数值直接法。通过将扰动方程表示成状态方程形式,再根据Flo-quet理论将扰动解表示成指数特征分量与周期分量之积,并将其周期分量与系统周期系数展成Fourier级数,导出一系列代数方程,建立矩阵特征值问题,从而由数值求解特征值可直接确定参激系统的稳定性。该方法可用于一般周期参激阻尼系统,特征值矩阵不含逆子阵。应用于斜拉索在支座周期运动激励下的参激振动不稳定性分析,数值结果表明该方法的有效性。     

Unnatural selection: talent identification and development in sport

The early identification of talented individuals has become increasingly important across many performance domains. Current talent identification (TI) schemes in sport typically select on the basis of discrete, unidimensional measures at unstable periods in the athlete's development. In this article, the concept of talent is revised as a complex, dynamical system in which future behaviors emerge from an interaction of key performance determinants such as psychological behaviors, motor abilities, and physical characteristics. Key nonlinear dynamics concepts are related to TI approaches such as sensitivity to initial conditions, transitions, and exponential behavioral distributions. It is concluded that many TI models place an overemphasis on early identification rather than the development of potentially talented performers. A generic model of talent identification and development is proposed that addresses these issues and provides direction for future research.     

On the redundancy of complex modal parameters

Generating the simulation transfer function ( TF ) is indispensable to modal analysis, such as examining modal parameters identification algorithm, and assessing modal analysis software. Comparing 3 feasible algorithms to simulate TF shows that, one of them is preperable, which is expressing the TF as the function of the complex modal parameters(CMPs), because the deliberate behaviors of CMPs can be implemented easily, such as, dense modals, large damping, and complex modal shape, etc. Nonetheless, even this preferable algorithms is elected, the complex modal shapes cannot be specified arbitrarily, because the number of CMPs far more exceeds that in physical coordinate. So for physical realizable system, there are redundant constraints in CMPs. By analyzing the eigenvalue problem of a complex modal system, and the inversion equations from CMPs to physical parameters, the explicit redundancy constraints were presented. For the special cases, such as the real modal, the damping free modal, and non-complete identification, the specific forms of the redundancy constraints were discussed, along with the number of independent parameters. It is worthy of noting that, redundancy constraints are automatically satisfied for the real modal case. Their equivalent forms on the transfer matrix and a column of transfer matrix were also provided. These results are applicable to generate TF, to implement identification by optimization and appreciate the identification results, to evaluate residual modal, and to verify the complementary of identified modal orders.     

子结构物理参数的一种识别方法

本文基于复模态综合和优化技术,提出一种子结构物理参数识别方程。该方法利用复模态综合在广义坐标下建立物理参数识别方程,然后将物理参数识别化为优化问题求解。给出了一台钻床的子结构物理参数识别实例来说明方法的有效性.     

静水条件下淡水冰有效导温系数的优化辨识

依据天然河冰垂直温度剖面数据,构造了以拟合函数的系数为参变量的分布参数系统优化辨识模型,并分别用指数函数和线性函数拟合了河冰导温系数。对目标函数的优化采用Newton-Raphson算法,对热传导方程和灵敏度方程采用半隐式差分格式迭代求解。利用太原汾河二库天然冰垂直温度剖面数据进行了参数辨识和数值模拟,模拟结果与实测数据相吻合,表明所构造的参数辨识模型和优化算法是有效的。     

Impact of node dynamics parameters on topology identification of complex dynamical networks

This paper aims at investigating the topology identification problem of complex dynamical networks with varying node dynamics parameters and fixed inner coupling matrices. In particular, by employing the unified chaotic system as node dynamics, this work further explores the influence of continuously changing node dynamics parameters on topology identification of complex dynamical networks with different coupling strengths. Results show that for sufficiently small or large coupling strengths, the performance of topology identification is not affected by the change of node parameters. Specifically, for small enough coupling strengths, the topological structure can be completely identified regardless of the change of node parameters, while for sufficiently large coupling strengths, the connectivity (presence and absence of connections) cannot be successfully identified. Furthermore, for certain coupling strengths, with the increase of node dynamics parameters, the topology identification varies from completely unidentifiable to partially or event completely identifiable. Therefore, the synchronization-based topology identification depends on node dynamics. Even for the same node dynamical model, different parameters can have a significant impact on identification results. Furthermore, for networks consisting of chaotic oscillators defining node dynamics, small coupling strengths are conducive to topology identification. A broader conclusion is that projective synchronization, rather than just complete synchronization, is an obstacle to the network topology identification. The findings in this paper will add to our understanding of conditions for identifying topologies of complex networks.     

Nonlinear systems synchronization for modeling two-phase microfluidics flows

The aim of this work is to identify a class of models that can represent the two-phase microfluidic flow in different experimental conditions. The identification procedure adopted is based on the nonlinear systems synchronization theory. The experimental time series were assumed as the asymptotic behavior of a generic state variable of an unknown Master system, and this information was used to drive a second Slave system, with a known model and undefined parameters. To reach the convergence between the time evolutions of the two systems, so the flow identification, an error was evaluated and optimized by tuning the parameters of the Slave system, through genetic algorithm. The Chua’s oscillator has been chosen as a Slave model, and an optimal parameters set of Chua’s system was identified for each of the 18 experiments. As proof of concept on approach validity, the changes in the parameters set in the different experimental conditions were discussed taking into account the results of the nonlinear time series analysis. The results confirm the possibility with a single model to identify a variety of flow regimes generated in two-phase microfluidic processes, independently of how the processes have been generated, no directed relations with the input flow rate used are in the model.     

The mode III stress/electric intensity factors and singularities analysis for edge-cracked circular piezoelectric shafts

This paper introduces a new analytical method to determine the stress and electric intensity factors for edge-cracked circular piezoelectric shafts using Hamiltonian formalism. The singularities near the crack tip are represented in terms of exponential series that can show the boundary layer effects effectively. A symplectic system is established directly by introducing dual vectors in terms of the symplectic eigenfunctions. The coefficients of the series are determined from the lateral boundary conditions along the crack faces and the outer boundary conditions along the exterior geometric domain. The intensity factors are determined by the first two coefficients of non-zero eigenvalue solutions. Numerical examples for various boundary conditions are given. The influencing parameters on the intensity factors are investigated.     

计算系统识别与结构模型化

本文提出了利用计算机模拟输出实施系统识别的方法,并把这种概念性方法称之为“计算系统识别”。其基本点是,用计算机仿真模型和方法替代通常系统识别研究中的真实系统(或模拟试验系统)和试验方法那一部分,而实现通常系统识别研究的原定目标。联系结构模型化工作,文中报告了一例安全壳结构弯剪梁模型的识别结果。文章还介绍了一个解有约束极小化问题的修正单纯形法,用以完成结构物理参数的寻优任务。     

Turing patterns of Gierer–Meinhardt model on complex networks

Gierer–Meinhardt (G–M) model is a classical reaction diffusion (RD) model to describe biological and chemical phenomena. Turing patterns of G–M model in continuous space have attracted much attention of researchers. Considering that the RD system defined on discrete network structure is more practical in many aspects than the corresponding system in continuous space, we study Turing patterns of G–M model on complex networks. By numerical simulations, Turing patterns of the G–M model on regular lattice networks and several complex networks are studied, and the influences of system parameters, network types and average degree on pattern formations are discussed. Furthermore, we present an exponential decay of Turing patterns on complex networks, which not only quantitatively depicts the influence of network topology on pattern formations, but also provides the possibility for predict pattern formations.

     

Qualitative behaviors of the continuous-time chaotic dynamical systems describing the interaction of waves in plasma

In this paper, a new Lorenz-like chaotic system describing the interaction of three resonantly coupled waves in plasma is studied. Explicit ultimate boundedness and global attraction domain are derived according to stability theory of dynamical systems. The innovation of the paper is that this paper not only proves this chaotic system is globally bounded for the parameters of this system but also gives a family of mathematical expressions of global exponential attractive sets for this system with respect to the parameters of this system. Furthermore, the exponential rate of the trajectories is also obtained. Finally, numerical localization of attractor is presented.     

New methods of determination of the molar weight distribution from rheological measurements

By assuming simplified hypotheses which result from the molecular analysis of Doi-Edwards, it is possible to propose rheological methods for characterizing molar weight distribution of entangled polymeric liquids. The generalized exponential distribution is especially concerned. Theoretical expressions of rheological parameters are derived, and their numerical values are calculated in special cases. A numerical method of discrimination and identification of these special distributions is proposed.     

计及短周期误差的直齿轮副近周期运动及其辨识

齿轮副中的齿距偏差等短周期误差使系统出现复杂的周期运动, 影响齿轮传动的平稳性. 将该类复杂周期运动定义为近周期运动, 采用多时间尺度Poincaré映射截面对其进行辨识. 为研究齿轮副的近周期运动, 引入含齿距偏差的直齿轮副非线性动力学模型, 并计入齿侧间隙与时变重合度等参数. 采用变步长4阶Runge-Kutta法数值求解动力学方程, 由所提出的辨识方法分析不同参数影响下系统的近周期运动. 根据改进胞映射法计算系统的吸引域, 结合多初值分岔图、吸引域图与分岔树状图等研究了系统随扭矩与啮合频率变化的多稳态近周期运动. 研究结果表明, 齿轮副中的短周期误差导致系统的周期运动变复杂, 在微观时间尺度内, 系统的Poincaré映射点数呈现为点簇形式, 系统的点簇数与实际运动周期数为宏观时间尺度的Poincaré映射点数. 短周期误差导致系统在微观时间尺度内的吸引子数量增多, 使系统运动转迁过程变复杂. 合理的参数范围及初值范围可提高齿轮传动的平稳性. 该辨识与分析方法可为非线性系统中的近周期运动研究奠定理论基础.      

Identifying mode shapes and modal frequencies by operational modal analysis in the presence of harmonic excitation

Operational modal analysis techniques allow us to extract the modal properties of structures based on their response to non-measured stationary white noise, i.e., by considering only the system response to operational excitations. In this paper we outline a procedure to deduce modal parameters from operational response measurements. In particular, we discuss a novel approach to analyze operational responses due to unknown harmonic excitation in addition to noise. Structural eigenfrequencies and modal damping are computed using a modified least-squares complex exponential method. Once the poles of the system are identified, mode shapes are obtained by post-processing. The robustness and accuracy of the approach are illustrated by performing tests on a plate structure.     

OPERATIONAL MODAL ANALYSIS SCHEMES USING CORRELATION TECHNIQUE

For some large-scale engineering structures in operating conditions, modal parameters estimation must base itself on response-only data. This problem has received a considerable amount of attention in the past few years. It is well known that the cross-correlation function between the measured responses is a sum of complex exponential functions of the same form as the impulse response function of the original system. So this paper presents a time-domain operating modal identification global scheme and a frequency-domain scheme from output-only by coupling the cross-correlation function with conventional modal parameter estimation. The outlined techniques are applied to an airplane model to estimate modal parameters from response-only data.     

THEORY AND METHOD OF OPTIMAL CONTROL SOLUTION TODYNAMIC SYSTEM PARAMETERS IDENTIFICATION (Ⅰ)──FUNDAMENTAL CONCEPT AND DETERMINISTIC SYSTEM PARAMETERS IDENTIFICATION

IntroductionDynamicsystemidentificationistheinverseproblemofdynamics.Throughtheuseofexperimentaloroperahonalinput-outputdata,modelofdynaITilcsystemcanbeestablishedbysystemidentificationtechnique,andundetCndnedparametersofmodelcanalsobeidenhfied.Ingeneral,dynamicequahonsofsystemareknownPrior,whilesystemidentificahonisjustanundetendnedparametersidentificationproblem.TheseparametersaremodalparameterssuchasfrequenciesandmodeshapesorstrUctUralparameterssuchasdampingandstiffness.T'hisisatypical"g…     

混合驱动水下滑翔机水动力参数辨识

与传统水下滑翔机相比,混合驱动水下滑翔机可以分别利用头部的浮力驱动单元和机身尾部的螺旋桨推进单元进行驱动从而实现不同形式的运动,具备低功耗、长航程、良好机动性等特点,具有广泛的应用前景. 准确的动力学模型以及精确的水动力参数是实现混合驱动水下滑翔机控制系统设计以及精确导航的基础. 在混合驱动水下滑翔机动力学模型已知的前提下获得准确的水动力参数是本文主要研究的问题. 本文以天津大学研制的混合驱动水下滑翔机“海燕” 作为研究对象,提出一种在有限航行参数条件下,基于大数据统计分析的计算流体力学(computational fluid dynamics, CFD) 和参数辨识相结合来获取混合驱动水下滑翔机的水动力参数的方法. 即首先建立滑翔机的动力学模型,推导出稳态数据与所求水动力参数的关系;然后采用CFD 的方法得到其升力系数,根据大量稳态纯滑翔实验数据,结合大数据统计分析,辨识出其剩余水动力参数;最后,根据混合驱动模式下的实验数据辨识出与螺旋桨相关的参数,从而得到其整套的水动力参数. 该方法不仅结合了CFD 方法具有获取复杂外形结构航行水动力的特点,而且可以有效利用大量现场实验数据,因而能够更加准确地辨识其实际运动. 通过运动仿真与试验对比,验证了该辨识方法的正确性和有效性,对滑翔机的研究具有指导意义.