一类Jacobi矩阵广义特征值反问题

称为n阶Jacobi矩阵,振动反问题讨论由特征值（频率）和特征向量（模态）数据确定振动系统的物理参数,其研究对结构设计和结构物理参数识别具有重要意义,弹簧-质点系统的振动反问题归结为Jacobi矩阵的特征值反问题,这类问题已被许多学者研究[1-3]．     

用试验数据修正振动系统的双对称阻尼矩阵与刚度矩阵

讨论用试验数据修正振动系统的双对称阻尼矩阵与刚度矩阵问题.依据特征方程、阻尼矩阵与刚度矩阵的双对称性,利用代数二次特征值反问题的理论和方法,研究了该问题解的存在性与唯一性,提出了修正阻尼矩阵与刚度矩阵的一个新方法.利用双对称矩阵的性质研究了方程的双对称解.给出了二次特征值反问题双对称解的一般表达式,讨论了对任意给定矩阵的最佳逼近问题,并给出了问题的最佳逼近解.用该方法修正的阻尼矩阵与刚度矩阵不仅满足二次特征方程,而且是唯一的双对称矩阵.     

用自由度不完整的振型数据修正质量矩阵与刚度矩阵

运用代数特征值反问题的理论和方法,研究了一类无阻尼结构系统的模型修正问题.提出了一个新的修正方法.该方法利用自由度不完整的振型数据修正质量矩阵与刚度矩阵,修正过程是保持对称性与无溢出的;同时分析了问题的可解性,并给出了一个求解问题对称解的迭代算法.数值试验表明,提出的算法是有效的.     

一类二次特征值反问题的中心对称解及其最佳逼近

1引言给定n阶实矩阵M,C和K,二次特征值问题:求数λ和非零向量x使得Q(λ)x=0, (1．1)其中Q(λ)=λ2M λC K称为二次束．数λ和相应的非零向量x分别称为二次束Q(λ)的特征值和特征向量．Tisseur和Meerbergen概述了二次特征值问题的各种应用、数学理论和数值方法．在工程技术,特别是结构动力模型修正技术领域经常遇到与二次特征值问题相反的问题(称之为二次特征值反问题)．对阻尼结构进行动力分析时,应用有限元方法可得到系统的质量矩阵M,阻尼矩阵C和刚度矩阵K,从而可求得二次特征值问题的特征值(频率)和特征向量(振型)．但是有限元模型毕竟是实际结构系统的离散化,并且     

用试验数据修正质量矩阵,阻尼矩阵与刚度矩阵

讨论用试验数据修正振动系统的双对称质量矩阵,阻尼矩阵与刚度矩阵的问题.依据特征方程,质量矩阵,阻尼矩阵与刚度矩阵的双对称性,利用代数二次特征值反问题的理论和方法,研究了这个问题解的存在性与惟一性,提出了修正质量矩阵,阻尼矩阵与刚度矩阵的一个新方法.利用矩阵的奇异值分解和矩阵的Kronecker乘积研究了方程的双对称解.给出了二次特征值反问题双对称解的一般表达式,讨论了对任意给定矩阵的最佳逼近问题,并给出了问题的最佳逼近解.     

根据非完整模态信息进行结构动力模型识别

对于复杂结构的振动问题，我们很难给出比较准确的数学模型。本文建立了一种利用非完整模态试验数据来确定结构线性动力模型的识别办法。该方法的主要特点是不需要知道系统的全部模态信息，便可同时地唯一地识别出系统的质量矩阵、阻尼矩阵、刚度矩阵及其他相关参数．我们假定系统的质量矩阵、阻尼矩阵和刚度矩阵具有实对称性和正定性，并且系统的部分特征值和相应的特征向量已由实验给出，在此基础上利用最小二乘法及迭代修正技术进行系统矩阵及其他相关参数的识别．为了验证方法的可靠性，文中给出了若干构造性算例。     

用3个向量对构造梁振动系统的刚度矩阵

针对梁的离散化模型的刚度矩阵是五对角矩阵,梁振动反问题的实质是实对称五对角矩阵的特征值反问题.该文利用向量对、Moore-Penrose广义逆给出了实对称五对角矩阵向量对反问题存在唯一解的条件,并结合矩阵分块讨论了双对称五对角矩阵向量对反问题解存在唯一的条件,进而计算了次对角线位置元素为负,其它位置元素均为正的实对称五对角矩阵特征值反问题.由于构造梁的离散模型需要的数据可由测试得到,故而其结果适合于模态分析、系统结构的分析与设计等方面应用.最后给出了数值算例,通过数值讨论说明方法的有效性.     

用反馈控制修正无阻尼陀螺系统

本文利用代数特征值反问题的理论与方法,研究一类无阻尼陀螺系统的模型修正问题.为了保证陀螺系统的稳定性,本文利用输出反馈来修正陀螺矩阵,且找到了在Frobenius范数意义下满足特征方程以及反对称性的最佳逼近陀螺矩阵.最后,数值算例表明该方法是可行的.     

一类广义特征值反问题

本文提出了一个实对称带状矩阵的广义特征值反问题,并且证明了对于Jacobi矩阵和一般对称矩阵,问题的存在性.     

修正无阻尼结构系统的一种有效迭代法

结构动力学模型修正就是使得分析结果与实验结果的差最小化的一种程序.该文给出了一种基于不完全测量模态数据同时修正质量矩阵与刚度矩阵的迭代方法.通过此方法,在不计舍入误差的情况下,通过选取特殊的初始矩阵对,经有限步迭代,可得到满足特征方程的最优近似质量矩阵与刚度矩阵,并且保持了初始模型的高阶未测量且未知的特征信息.两个数值例子验证了该文给出的迭代算法是有效的.     

A new updating method for the damped mass-spring systems

In this paper, we concern the inverse problem of constructing a monic quadratic pencil which possesses the prescribed partial eigendata, and the damping matrix and stiffness matrix are symmetric tridiagonal. Furthermore, the stiffness matrix is positive semi-definite and weakly diagonally dominant, which has positive diagonal elements and negative off-diagonal elements. Based on the solution of the inverse eigenvalue problem, we apply the alternating direction method with multiplier to solve the finite element model updating problem for the serially linked mass-spring system. The positive semi-definiteness of stiffness matrix, nonnegativity of stiffness and the physical connectivity of the original model are preserved. Numerical results show that our proposed method works well.     

Model updating for undamped gyroscopic systems with connectivity constraints

ABSTRACT

An important and difficult aspect for the finite element model updating problem is to make the updated model have physical meaning, that is, the connectivity of the original model should be preserved in the updated model. In many practical applications, the system matrices generated by discretization of a distributed parameter system with the finite element techniques are often very large and sparse and are of some special structures, such as symmetric and band structure (diagonal, tridiagonal, pentadiagonal, seven-diagonal, etc.). In this paper, the model updating problem for undamped gyroscopic systems with connectivity constraints is considered. The method proposed not only preserves the connectivity of the original model, but also can update the analytical matrices with different bandwidths, which can meet the needs of different structural dynamic model updating problems. Numerical results illustrate the efficiency of the proposed method.     

The direct updating of damping and gyroscopic matrices

In this paper we develop an efficient numerical method for the finite element model updating of damped gyroscopic systems. This model updating of damped gyroscopic systems is proposed to incorporate the measured modal data into the finite element model to produce an adjusted finite element model on the damping and gyroscopic matrices that closely match the experimental modal data.     

A global damping factor for a non-invasive form finding algorithm

Inverse form finding based on the finite element method (FEM) aims in determining the optimal material (undeformed) configuration when knowing the target spatial (deformed) configuration in a discretized setting. The strategy is to iteratively update the material coordinates and recompute the spatial configuration by a FEM simulation until the computed spatial nodal positions are close enough to a priori given spatial nodal positions. A form finding algorithm is utilized, which is purely based on geometrical considerations and can be coupled with arbitrary external FEM software via subroutines in a non-invasive fashion. At large deformations degenerated elements can occur when updating the material coordinates. Evaluating the mesh quality of the updated material configuration and adjusting a global damping factor before recomputing the next spatial configuration helps to avoid mesh distortions. (© 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

New symmetry preserving method for optimal correction of damping and stiffness matrices using measured modes

Measured and analytical data are unlikely to be equal due to measured noise, model inadequacies, structural damage, etc. It is necessary to update the physical parameters of analytical models for proper simulation and design studies. Starting from simulated measured modal data such as natural frequencies and their corresponding mode shapes, a new computationally efficient and symmetry preserving method and associated theories are presented in this paper to update the physical parameters of damping and stiffness matrices simultaneously for analytical modeling. A conjecture which is proposed in [Y.X. Yuan, H. Dai, A generalized inverse eigenvalue problem in structural dynamic model updating, J. Comput. Appl. Math. 226 (2009) 42-49] is solved. Two numerical examples are presented to show the efficiency and reliability of the proposed method. It is more important that, some numerical stability analysis on the model updating problem is given combining with numerical experiments.     

Quadratic model updating with no spill-over and incomplete measured data: Existence and computation of solution

Quadratic finite element model updating problem (QFEMUP), to be studied in this paper, is concerned with updating a symmetric nonsingular quadratic pencil in such a way that, a small set of measured eigenvalues and eigenvectors is reproduced by the updated model. If in addition, the updated model preserves the large number of unupdated eigenpairs of the original model, the model is said to be updated with no spill-over. QFEMUP is, in general, a difficult and computationally challenging problem due to the practical constraint that only a very small number of eigenvalues and eigenvectors of the associated quadratic eigenvalue problem are available from computation or measurement. Additionally, for practical effectiveness, engineering concerns such as nonorthogonality and incompleteness of the measured eigenvectors must be considered. Most of the existing methods, including those used in industrial settings, deal with updating a linear model only, ignoring damping. Only in the last few years a small number of papers been published on the quadratic model updating; several of the above issues have been dealt with both from theoretical and computational point of views. However, mathematical criterion for existence of solution has not been fully developed. In this paper, we first (i) prove a set of necessary and sufficient conditions for the existence of a solution of the no spill-over QFEMUP, then (ii) present a parametric representation of the solution, assuming a solution exists and finally, (iii) propose an algorithm for QFEMUP with no spill-over and incomplete measured eigenvectors. Interestingly, it is shown that the parametric representation can be constructed with the knowledge of only the few eigenvalues and eigenvectors that are to be updated and the corresponding measured eigenvalues and eigenvectors—complete knowledge of eigenvalues and eigenvectors of the original pencil is not needed, which makes the solution readily applicable to real-life structures.     

A constrained optimization based method for acoustic finite element model updating of cavities using pressure response

A method based on constrained optimization for updating of an acoustic finite element model using pressure response is proposed in this paper. The constrained optimization problem is solved using sequential quadratic programming algorithm. Updating parameters related to the properties of the sound absorbers and the measurement errors are considered. Effectiveness of the method is demonstrated by numerical studies on a 2D rectangular cavity and a car cavity. It is shown that the constrained formulation, that includes lower and upper bounds on the updating parameters in the form of inequality constraints, is important for obtaining a correct updated model. It is seen that the proposed updating method is not only able to effectively update the model to obtain a close match between the finite element model pressure response and the reference pressure response, but is also able to identify the correction factors to the parameters in error with reasonable accuracy.     

An efficient statistically equivalent reduced method on stochastic model updating

The demand for computational efficiency and reduced cost presents a big challenge for the development of more applicable and practical approaches in the field of uncertainty model updating. In this article, a computationally efficient approach, which is a combination of Stochastic Response Surface Method (SRSM) and Monte Carlo inverse error propagation, for stochastic model updating is developed based on a surrogate model. This stochastic surrogate model is determined using the Hermite polynomial chaos expansion and regression-based efficient collocation method. This paper addresses the critical issue of effectiveness and efficiency of the presented method. The efficiency of this method is demonstrated as a large number of computationally demanding full model simulations are no longer essential, and instead, the updating of parameter mean values and variances is implemented on the stochastic surrogate model expressed as an explicit mathematical expression. A three degree-of-freedom numerical model and a double-hat structure formed by a number of bolted joints are employed to illustrate the implementation of the method. Using the Monte Carlo-based method as the benchmark, the effectiveness and efficiency of the proposed method is verified.     

Bayesian Ising Graphical Model for Variable Selection

In this article, we propose a new Bayesian variable selection (BVS) approach via the graphical model and the Ising model, which we refer to as the “Bayesian Ising graphical model” (BIGM). The BIGM is developed by showing that the BVS problem based on the linear regression model can be considered as a complete graph and described by an Ising model with random interactions. There are several advantages of our BIGM: it is easy to (i) employ the single-site updating and cluster updating algorithm, both of which are suitable for problems with small sample sizes and a larger number of variables, (ii) extend this approach to nonparametric regression models, and (iii) incorporate graphical prior information. In our BIGM, the interactions are determined by the linear model coefficients, so we systematically study the performance of different scale normal mixture priors for the model coefficients by adopting the global-local shrinkage strategy. Our results indicate that the best prior for the model coefficients in terms of variable selection should place substantial weight on small, nonzero shrinkage. The methods are illustrated with simulated and real data. Supplementary materials for this article are available online.     

基于变体积约束的阻尼材料微结构拓扑优化研究北大核心CSCD

阻尼复合结构的抑振性能取决于材料布局和阻尼材料特性.该文提出了一种变体积约束的阻尼材料微结构拓扑优化方法,旨在以最小的材料用量获得具有期望性能的阻尼材料微结构.基于均匀化方法,建立阻尼材料三维微结构有限元模型,得到阻尼材料的等效弹性矩阵.逆用Hashin-Shtrikman界限理论,估计对应于期望等效模量的阻尼材料体积分数限,并构建阻尼材料体积约束限的移动准则.将获得阻尼材料微结构期望性能的优化问题转化为体积约束下最大化等效模量的优化问题,建立阻尼材料微结构的拓扑优化模型.利用优化准则法更新设计变量,实现最小材料用量下的阻尼材料微结构最优拓扑设计.通过典型数值算例验证了该方法的可行性和有效性,并讨论了初始微构型、网格依赖性和弹性模量等对阻尼材料微结构的影响.