动态结构系统可靠性的频率灵敏度分析

基于频率可靠性理论提出了动态结构系统的频率可靠性灵敏度的计算方法. 根据动态结构系统的固有频率与激振频率差的绝对值不超过规定值的关系准则,定义了随机结构振动问题的可靠性模式和系统的可靠度,进而提出了频率可靠性灵敏度分析方法,应用随机摄动技术、可靠性理论和灵敏度方法,推导出参数为正态随机变量时的准失效概率灵敏度的表达公式,对动态结构系统共振问题的可靠性灵敏度分析方法进行了探索. 并在此基础上,以一简化的车身-车轮-路面关系的系统模型为例,由可靠性灵敏度矩阵可以看出,各随机参数的变化对动态结构系统的可靠性及失效性的影响程度也不同,其计算结果与通常的定性分析结果完全一致,验证了所提方法的有效性. 该方法为动态结构系统的优化和设计提供了依据.      

可靠性灵敏度函数及其特征指标的条件概率模拟求解方法

可靠性分析中基本变量分布参数为区间均匀变量时,失效概率为分布参数的函数。基于条件概率马尔科夫链模拟,提出了一种可靠性灵敏度函数的求解方法,并提出了一种新的可靠性灵敏度度量指标,它为参数可靠性灵敏度函数在参数空间上的期望。文中推导了线性极限状态正态变量下全局灵敏度函数及新指标的计算式.并提出了高效的基于条件概率马尔科夫链...     

任意分布参数的梁结构刚度可靠性灵敏度分析

在刚度可靠性设计理论与灵敏度分析方法的基础上,研究了任意分布参数的梁结构刚度可靠性灵敏度分析问题,提出了刚度可靠性灵敏度分析的计算方法,给出了可靠性灵敏度的变化规律,研究了设计参数的改变对梁结构刚度可靠性的影响,为任意分布参数的梁结构刚度可靠性设计提供了理论依据。     

可靠性敏度分析方法及其在非线性蠕变疲劳失效模型中的应用

针对非线性极限状态方程,发展了两种基本随机变量为非正态情况下的可靠性敏度分析方法:基于改进一次二阶矩的近似解析法和基于Monte-Carlo的数字模拟法.近似解析法中非正态变量首先被等价变换为正态变量,然后用正态变量的敏度分析法和隐函数求导法则来得到失效概率对非正态变量分布参数的灵敏度,求解敏度的数字模拟法是从计算失效概率的所有样本点中选取合适的抽样点,利用回归分析和隐函数求导法则来求取可靠性灵敏度的.所提方法被用于非线性蠕变疲劳失效模式的可靠性灵敏度分析,近似解析法和数字模拟法结果的一致说明了所提方法的合理可行.蠕变疲劳失效的可靠性灵敏度随参数的变化趋势分析为工程设计提供了有益指导.     

基于随机响应面法的可靠性灵敏度分析及可靠性优化设计

基于随机响应面法建立了可靠性灵敏度分析方法,并将其用于结构可靠性优化设计。建立的方法利用随机响应面法将隐式的结构响应函数转换成显式函数,在显式的响应函数基础之上求解失效概率和进行可靠性灵敏度分析,得到的可靠性灵敏度能为基于函数梯度的优化算法提供梯度信息。算例表明,本文提出的可靠性灵敏度分析方法具有较高的效率和精度,提高了结构可靠性优化设计的效率。     

基于线抽样的可靠性灵敏度分析方法

提出了一种基于线抽样的可靠性灵敏度分析方法.线抽样可靠性分析中,结构失效概率Pf是由每个抽样样本对应的失效概率Pfj的算术平均值来计算的,由此可知Pf对基本变量分布参数θ的灵敏度(э)Pf/(э)θ可以表示为Pfj对θ的偏导数(э)Pfj/(э)θ的算术平均值,而(э)Pfj/(э)θ则可以很容易地由Pfj与基本变量分布参数θ的解析关系求得. (э)Pfj/(э)θ和(э)Pf/(э)θ的计算公式被详细推导.可靠性灵敏度分析的线抽样方法继承了线抽样法的优点,诸如精度高,收敛快且适用于高维及多模式情况等.这些优点由算例证实.     

结构可靠性灵敏度分析的方向（重要）抽样法

方向抽样法是在标准正态空间极坐标系下,通过对矢径的方向进行随机抽样来分析结构可靠度的.但是当极限状态面接近平面时,方向抽样法就没有优势了.为了提高方向抽样法的效率,提出了三种基于方向(重要)抽样法的可靠性灵敏度分析方法.根据独立标准正态空间中基本变量的x<'2>分布特性及矢径与随机变量分布参数的关系,推导失效概率对基本随机变量分布参数的可靠性灵敏度分析的计算公式.该文所提的可靠性及灵敏度计算方法有较高的计算效率和精度,对于高度非线性极限状态方程问题亦有很强的适应性.     

基于鞍点估计及其改进法的可靠性灵敏度分析

鞍点估计可以直接逼近非正态变量空间中线性功能函数概率分布, 进而得出功能函数的失效概率. 在此基础上进行了基于鞍点估计的可靠性灵敏度分析. 对于非线性功能函数, 尤其是强非线性功能函数, 基于鞍点估计进行可靠性及灵敏度分析时存在较大的误差, 为此建立了基于鞍点估计的改进方法------鞍点线抽样方法的可靠性灵敏度分析. 在标准化的变量空间中利用线抽样方法的样本点将系统失效概率转化为一系列线性响应功能函数失效概率的平均值, 从而可靠性灵敏度转化为一系列线性响应功能函数的失效概率对随机变量分布参数偏导数的平均值, 再采用鞍点概率估计方法直接估计非正态变量标准化空间中这一系列线性响应功能函数的失效概率及可靠性灵敏度. 通过比较两种方法的基本思想、实现过程和算例结果可以发现: (1) 第1种方法只适用于线性程度较好的功能函数的情况, 其误差主要来源于非线性极限状态函数的线性化; (2) 改进方法给出的是失效概率及失效概率对随机变量分布参数偏导数的估计值, 这些估计值随样本点数的增加而趋于真值, 并且该方法可以考虑功能函数的非线性对失效概率的影响, 因此具有广泛的适用范围.      

基于子集模拟和重要抽样的可靠性灵敏度分析方法

针对工程实际中大量存在的小失效概率问题,提出了基于子集模拟和重要抽样的可靠性灵敏度分析方法. 在子集模拟重要抽样可靠性分析方法中,通过引入合理的中间失效事件,将小的失效概率表达为一系列较大的条件失效概率的乘积,而较大的条件失效概率则可通过构造中间失效事件的重要抽样密度函数来高效求解. 基于子集模拟重要抽样可靠性分析的思想,论文将可靠性灵敏度转化为条件失效概率对基本变量分布参数的偏导数形式,推导了基于子集模拟和重要抽样的可靠性灵敏度估计值及估计值方差的计算公式,并采用算例对所提方法进行了验证. 算例结果表明所提方法具有较高的计算精度和效率,并且适用单个和多个失效模式系统.      

连续体结构非概率可靠性拓扑优化

基于非概率可靠性 指标的定义，考虑材料、几何及荷载大小的不确定性，提出以结构体积最小化为目标、具有 位移非概率可靠性约束的三维连续体拓扑优化数学模型. 采用目标性能方法对优化模型进行 转换，给出目标性能值的伴随法灵敏度分析算法，利用数学规划法实现优化问题的求解. 数 值算例验证了所提出优化模型的正确性及算法的有效性，并指出相对于确定性优化而言，非 概率可靠性拓扑优化能够给出在考虑不确定参数和荷载条件下更合理的材料分布.     

Sensitivity,probabilistic and stochastic analysis of the thermo-piezoelectric phenomena in solids by the stochastic perturbation technique

The main aim here is to present the application of the generalized stochastic perturbation technique to thermo-piezoelectric analysis of solid continua. The general nth order Taylor series representation for all random input parameters and the state functions is employed to formulate the coupled thermo-electro-elasticity equilibrium equations of the additional order; a determination of any probabilistic moments and characteristics is described; the discretization of the problem in terms of the Stochastic perturbation-based Finite Element Method is also provided. Since this expansion includes the lowest order partial derivatives, the structural sensitivity analysis using direct differentiation is performed at the same time with probabilistic modeling contrasted with the Monte-Carlo simulation results. The probabilistic approach is extended here towards an accounting for the stochastic ageing processes, which appear frequently in aggressive external environments and under dynamic excitation. The two parametric stochastic process with Gaussian initial value and ageing velocity is tested for this purpose. The entire procedure is tested on the example of the thermo-electro-elastic pulsation of the beam modeled analytically using the symbolic software MAPLE, where polynomial approximations, design sensitivities, probabilistic moments and their histories are computed and visualized.     

Probabilistic solutions of nonlinear oscillators excited by correlated external and velocity-parametric Gaussian white noises

This paper addresses the random vibrations of the oscillators with correlated external and parametric excitations being Gaussian white noises. The exponential polynomial closure method is used in the analysis, with which the probability density of the system responses is obtained. Two oscillators are analyzed. One is about the linear oscillator subjected to correlated external and parametric excitations. Another is about the oscillator with cubic nonlinearity and subjected to correlated external and parametric excitations. Numerical studies show that exponential polynomial closure method provides computationally efficient and relatively accurate estimates of the stationary probabilistic solutions, particularly in the tail regions of the probability density functions. Numerical results further show that correlated external and parametric excitations can cause unsymmetrical probabilistic solutions and nonzero means which are different from those when the external and parametric excitations are independent.     

Modélisation probabiliste d'une expérience ultrasonore : calcul de la dispersion sur les mesures de célérité

This Note presents a probabilistic model of transient wave reflection at a fluid–solid interface. The configuration represents an ultrasonic experiment used for bone tissue evaluation. The parametric method is used to derive the probabilistic model for the mechanical parameters of the solid (bone); the associated random variables are derived according to the maximum entropy principle. A Monte Carlo simulation, associated with the Cagniard–de Hoop method to calculate the acoustic response, yields the probability density for an output ultrasonic parameter similar to the velocity of longitudinal waves in the solid. Results demonstrate the sensitivity of the probability density of this parameter to the experimental setup. To cite this article: K. Macocco et al., C. R. Mecanique 333 (2005).     

On the stability of systems with stochastically variable parameters

The paper analyzes questions related to the construction of dynamic stability boundaries of elastic systems subjected to stochastic parametric excitation. It is supposed that the parametric action is a combination of a deterministic static component and a stochastic fluctuating component. The fluctuating component is taken to be a stationary ergodic process. The stability boundaries are built in the region of combination resonance using the stochastic averaging method and a probabilistic approach due to Khasminskii. In this connection, the stochastic averaging method based on the Stratonovich-Khasminskii theory is used. The probabilistic approach consists in using explicit asymptotic expressions for the largest Lyapunov exponent, from which the asymptotic stability boundaries are determined. As an application, the stability of a simply supported thin-walled bar subjected to a stochastically varying longitudinal load is investigated Published in Prikladnaya Mekhanika, Vol. 41, No. 12, pp. 128–138, December 2005.     

Stochastic approach to estimate the arterial pressure

The aim of this paper is to illustrate the application of a stochastic approach to estimate the human common carotid arterial pressure. The analysis took into account the possible random uncertainties of the problem inputs such as geometric information and mechanical model parameters so that it is called a probabilistic parametric approach. Based on the only available information reported in literature, entropy maximum principle was used to develop probabilistic density functions for every random variable. In addition, in vivo human experimental data were considered for the determination of the so-called mean or deterministic model. Furthermore, numerical simulations of Monte Carlo were carried out involving the dispersion of all the uncertain parameters. Results showed that uncertainty of 5% led to error up to 20% in the arterial pressure estimation. Convergence was proved and a region with a confidence probability of 95% was constructed to allow the prediction of the random response of the arterial pressure. Eventually, we managed numerous calculations to analyze the influence of each random variable of the problem inputs over the arterial pressure evolution.     

功能梯度材料结构热力耦合概率分析方法

基于自洽平均微观力学W-T(Wakashima-Tsukamoto)模型和拉丁超立方抽样,建立一种功能梯度平板热力耦合概率分析方法.以材料物理属性和空间分布的不确定性随机参数作为概率分析的输入,以热应力作为输出,基于本征正交分解POD(Proper Orthogonal Decomposition)对热应力的随机时间历...     

Sampling-Based RBDO of Ship Hull Structures Considering Thermo-Elasto-Plastic Residual Deformation

We present a shape optimization method using a sampling-based RBDO method linked with a commercial finite element analysis (FEA) code ANSYS, which is applicable to residual deformation problems of the ship hull structure in welding process. The programming language ANSYS Parametric Design Language (APDL) and shell elements are used for the thermo-elasto-plastic analysis. The shape of the ship hull structure is modeled using the bicubic Ferguson patch and coordinate components of vertices, tangential vectors of boundary curves are selected as design variables. The sensitivity of probabilistic constraint is calculated from the probabilistic sensitivity analysis using the score function and Monte Carlo Simulation (MCS) on the surrogate model constructed by using the Dynamic Kriging (DKG) method. The sequential quadratic programming (SQP) algorithm is used for the optimization. In two numerical examples, the suggested optimization method is applied to practical residual deformation problems in welding ship hull structures, which proves the sampling-based RBDO can be successfully utilized for obtaining a reliable optimum design in highly nonlinear multi-physics problem of thermo-elasto-plasticity.     

Material sensitivity analysis in homogenization of linear elastic composites

Summary  The main goal of the paper is to present theoretical aspects and the finite element method (FEM) implementation of the sensitivity analysis in homogenization of composite materials with linear elastic components, using effective modules approach. The deterministic sensitivity analysis of effective material properties is presented in a general form for an n-components periodic composite, and is illustrated by the examples of 1D as well as of 2D heterogeneous structures. The results of the sensitivity analysis presented in the paper confirm the usefulness of the homogenization method in computational analysis of composite materials the method may be applied to computational optimization of engineering composites, to the shape-sensitivity studies and, after some probabilistic extensions, to stochastic sensitivity analysis of random composites. Received 10 November 2000; accepted for publication 24 April 2001     

Sensitivity and randomness in homogenization of periodic fiber-reinforced composites via the response function method

The main issue this paper addresses is the derivation and implementation of a general homogenization method, including the simultaneous determination of sensitivity gradients and probabilistic moments of the effective elasticity tensor. This is possible with an application of the perturbation method based on Taylor expansion and with the effective modules method. The computational procedure is implemented using plane strain analysis carried out with the finite element method (program MCCEFF) and the symbolic computations system MAPLE. The sensitivity gradients and probabilistic moments are commonly determined on the basis of partial derivatives for the homogenized elasticity tensor, calculated using the response function method with respect to some composite parameters. They are subjected separately to a normalization procedure (in deterministic analysis) and the relevant algebraic combinations (for the stochastic case). This enriched homogenization procedure is tested on a periodic fiber-reinforced two component composite, where the material parameters are taken as design variables and then, the input random quantities. The results of computational analysis are compared against the results of the central finite difference approach in the case of sensitivity gradients determination as well as the direct Monte-Carlo simulation approach. This numerical methodology may be further applied not only in the context of the homogenization method, but also to extend various discrete computational techniques, such as Boundary/Finite element and finite difference together with various meshless methods.     

Stochastic stability of three-dimensional linear systems under parametric random action

The stability of a three-dimensional linear system, driven by a parametric random excitation is considered. The stability of the system is investigated using a combination of stochastic averaging method and a probabilistic approach. For this purpose, it is necessary to find the transient probability density of the components of the vector random process. Thus, the invariant measure of the system may be calculated from the stationary solutions of the associated Fokker–Planck equations. These solutions are obtained numerically, using the sweep method. As a comparison criterion, a digital simulation of It? equations has been carried out using the Monte-Carlo simulation (MCS) method. As an application, the example of instability of a thin-walled bar under the effect of parametric random action is considered