随机结构随机激励下的响应灵敏度分析

对于随机激励下随机结构动力响应的灵敏度分析问题,提出基于点估计法的随机结构随机动力响应灵敏度分析方法.所提方法从随机结构响应均方值的均值表达式出发,首先将随机结构响应均方值的均值对基本随机变量分布参数灵敏度转化成求期望值问题,再由求解随机变量函数矩的点估计方法导出求解动力响应灵敏度的计算公式.算例分析表明该方法的计算结果是合理的,并且由于点估计法具有较高的效率和精度,因而所提方法具有一定的工程意义.     

基于支持向量机和蒙特卡洛法的结构随机灵敏度分析方法

该文利用具有良好小样本学习能力的支持向量机回归拟合结构响应的显式函数, 计算随机变量的灵敏度系数, 并结合蒙特卡洛法对结构响应的随机性进行分析。采用自适应混合粒子群法优化支持向量机相关参数取值, 提高了计算效率。通过两个工程算例验证了该方法的可行性, 并对比了训练样本抽样方法对计算精度的影响。算例结果表明:利用补充抽样方法抽取训练样本计算结构随机性得到的结果精度高, 拟合的概率密度分布曲线可以更好的反映真实情况;同时利用灵敏度系数研究了算例中不同随机变量对结构响应的敏感性。     

基于四分之一车辆模型的具有随机结构参数车辆的随机动力分析

本文通过具有随机结构参数的四分之一车辆模型研究了具有不确定性结构参数的车辆在受到来自道路的随机激励作用下的振动响应问题。文中将簧上质量、簧下质量、悬挂阻尼、悬挂刚度以及轮胎刚度均认为是随机变量。将路面的不平整引起的对车辆的激励看作高斯随机过程并通过简单指数功率谱密度来建立力学模型。利用蒙特卡洛方法得出了车辆的固有频率和模态振型的均值、标准差以及变异系数。利用随机变量函数矩方法在频域中建立了车辆的随机响应的均方值的数字特征的计算表达式。通过工程算例表明了车辆结构参数的随机性对其动力响应的影响。本文所做的工作可拓展应用于车辆结构参数的灵敏度分析和动力优化设计。     

复合随机振动系统的动力可靠性矩独立重要性测度及态相关参数解法

针对激励与结构参数同时存在不确定性的复合随机振动系统,由随机结构无条件动力可靠度表达式出发,利用条件概率密度函数解析变换给出衡量基本随机变量对动力可靠性影响的矩独立重要性测度指标。该指标可表征不确定性随机变量对动力可靠度响应量分布的平均影响程度,可全面反映随机变量对响应分布影响。基于状态依存参数模型,提出求解矩独立重要性测度指标的态相关参数(SDP)法。利用算例分析结构动力可靠性参数的矩独立重要性测度,并与直接Monte-Carlo法对比。所提方法可在保证计算精度同时大幅度提高计算效率,适用于分析复合随机振动系统非线性可靠性响应。     

刚架结构物理参数的随机性对其非平稳随机响应的影响

文中研究了随机刚架结构的非平稳随机响应问题。考虑结构在非平稳随机激励下其物理参数的随机性,从结构非平稳随机响应的表达式出发,利用求解随机变量函数矩的方法和求解随机变量数字特征的代数综合法,导出了结构位移响应均方值和应力响应均方值的均值、方差和变异系数的计算表达式。通过算例,考察了结构物理参数的随机性对结构动力响应均方值随机性的影响,获得了若干有意义的结论。     

平稳随机激励下线性随机桁架结构动力响应分析

考虑桁架结构的物理参数、几何尺寸的随机性，利用求解随机变量函数矩的方法和求解随机变量数字特征的代数综合法，从结构平稳随机响应在频域上的表达式出发，导出了随机桁架结构在平稳随机激励下位移响应均方值和应力响应均方值的均值、方差和变异系数的计算表达式。通过算例考察了结构物理参数和几何尺寸的随机性对结构位移响应均方值和应力响应均方值随机变量随机性的影响，并获得了一些有意义的结论。     

基于同伦分析方法的随机结构静力响应求解

该文提出了一种基于同伦分析方法的求解含随机参数结构的静力响应的新方法。该方法将随机静力平衡方程重新进行同伦构造,利用含随机变量和趋近函数的同伦级数展式来表示结构的随机静力位移响应,该同伦级数的各阶确定性系数和趋近函数可通过对一系列的变形方程求解得到。由于趋近函数的引入,该同伦级数解相较于传统的摄动法有更大的收敛范围,对于含较大变异性随机参数的结构也能获得不错的求解精度。同时,该文提出了一种降维策略来提高该方法的计算效率。数值算例表明,与目前广泛应用的广义正交多项式展开法（GPC）相比,从计算精度上看,该文方法的3阶展开与GPC 2阶展开相当,该文方法的6阶展开与GPC 4阶展开相当,而计算时间上前者均明显少于后者。此外,该文方法也可以方便地应用到随机结构的几何非线性分析当中,并具有较好的计算精度和计算效率。     

模糊分布参数的全局灵敏度分析新方法

为合理度量随机输入变量分布参数的模糊性对输出性能统计特征的影响,提出了模糊分布参数的全局灵敏度效应指标,并研究了指标的高效求解方法。首先,分析了不确定性从模糊分布参数至模型输出响应统计特征的传递机理,以输出性能期望响应为例,利用输出均值的无条件隶属函数与给定模糊分布参数取值条件下的隶属函数的平均差异来度量模糊分布参数的影响,建立了模糊分布参数的全局灵敏度效应指标。其次,为减少所提指标的计算成本、提高计算效率,采用了扩展蒙特卡罗模拟法(EMCS)来估算输入变量分布参数与模型输出响应统计特征的函数关系。最后通过对算例的计算,验证该文所提方法的准确性和高效性。     

随机参数结构最优控制的闭环响应分析

在模态坐标下对结构降阶进行最优控制,用近似离散化的方法得到结构闭环响应的近似解来代替精确解。考虑结构中物理参数和几何参数的随机性,将这些随机参数用随机因子来表示。在此基础上,利用求解随机变量函数矩的方法,导出了在最优控制的作用下,随机结构位移闭环响应的均值和方差的计算表达式。通过算例考察了结构各个参数的随机性对闭环响应的影响,经与Monte Carlo数值模拟法结果比较,验证了文中理论分析和计算方法的正确性。     

随机参数结构在随机荷载激励下的动力响应分析

研究了基于概率的工程结构动力响应分析方法。利用振型迭加法导出了结构物理参数和作用荷载幅值同时具有随机性时结构动力响应随机变量的数字特征计算表达式，并提出了求解方法。通过算例考察了结构物理参数和作用荷载的随机性对结构动力响应的影响，表明文中提出的计算模型和方法是正确与可行的。     

Non-stationary random response analysis of structures with uncertain parameters

This paper proposes a non-stationary random response analysis method of structures with uncertain parameters. The structural physical parameters and the input parameters are considered as random variables or interval variables. By using the pseudo-excitation method and the direct differentiation method (DDM), the analytical expression of the time-varying power spectrum and the time-varying variance of the structure response can be obtained in the framework of first order perturbation approaches. In addition, the analytical expression of the first-order and second-order partial derivative (e.g., time-varying sensitivity coefficient) for the time-varying power spectrum and the time-varying variance of the structure response expressed via the uncertainty parameters can also be determined. Based on this and the perturbation technique, the probabilistic and non-probabilistic analysis methods to calculate the upper and lower bounds of the time-varying variance of the structure response are proposed. Finally the effectiveness of the proposed method is demonstrated by numerical examples compared with the Monte Carlo solutions and the vertex solutions.     

Reliability analysis of structures using neural network method

In order to predict the failure probability of a complicated structure, the structural responses usually need to be estimated by a numerical procedure, such as finite element method. To reduce the computational effort required for reliability analysis, response surface method could be used. However the conventional response surface method is still time consuming especially when the number of random variables is large. In this paper, an artificial neural network (ANN)-based response surface method is proposed. In this method, the relation between the random variables (input) and structural responses is established using ANN models. ANN model is then connected to a reliability method, such as first order and second moment (FORM), or Monte Carlo simulation method (MCS), to predict the failure probability. The proposed method is applied to four examples to validate its accuracy and efficiency. The obtained results show that the ANN-based response surface method is more efficient and accurate than the conventional response surface method.     

利用机械结构的振动加速度信号反算应变的新方法

针对结构紧凑的机械结构难以采用布置应变计的方法来测量应变的问题,从动力学角度出发,采用虚拟力技术建立了实际作用力的等效力。通过进行虚拟测点的计算,以解决实际测点不足的难题。提出了加速度响应信号与输入载荷的协调方程,利用运行状态下机械结构的加速度响应信号来反算结构应变的方法。并通过工程实例得以验证。研究结果对结构紧凑、不利于进行应变测试的部位,可采用该方法进行应变数据的分析,为进行疲劳寿命分析奠定基础。     

地面运动激励下结构的动力学形状优化设计

通过推广和修改ESO方法来进行结构形状优化设计，以达到控制地面运动激励下的结构随机动力响应的目的，根据工程实际要求，用随机动力学理论构造具有白噪声功率谱的地面运动的随机响应表达式。基于特征导数的模态截断法和近似处理，导出了一套平均均方动响应的灵敏度公式，在优化软件上实现了形状优化算法，提供的算例显示了本方法的合理性和有效性。     

窄带随机激励下的结构动力学拓扑优化设计

基于模态截断法和一些近似处理,导出了一套窄带随机均方动响应及其灵敏度公式,再根据工程实际要求,研究了静载荷和窄带随机载荷作用下结构的动力学拓扑优化设计方法和算法,提供的算例显示了本方法的合理性和有效性。     

Reliability sensitivity analysis with random and interval variables

In reliability analysis and reliability‐based design, sensitivity analysis identifies the relationship between the change in reliability and the change in the characteristics of uncertain variables. Sensitivity analysis is also used to identify the most significant uncertain variables that have the highest contributions to reliability. Most of the current sensitivity analysis methods are applicable for only random variables. In many engineering applications, however, some of uncertain variables are intervals. In this work, a sensitivity analysis method is proposed for the mixture of random and interval variables. Six sensitivity indices are defined for the sensitivity of the average reliability and reliability bounds with respect to the averages and widths of intervals, as well as with respect to the distribution parameters of random variables. The equations of these sensitivity indices are derived based on the first‐order reliability method (FORM). The proposed reliability sensitivity analysis is a byproduct of FORM without any extra function calls after reliability is found. Once FORM is performed, the sensitivity information is obtained automatically. Two examples are used for demonstration. Copyright © 2009 John Wiley & Sons, Ltd.     

Time-varying reliability method based on linearized Nataf transform

In actual engineering, material properties, load effects, and other factors of mechanical structures change due to long-term use. In order to understand the operation of a mechanical structure in real time, it is crucial to obtain the dynamic trajectory of its reliability. Considering the time variability of a mechanical structure over time, uncertain random variables are introduced to express the uncertainty of various parameters of structures, and the Wiener process is used to describe the strength degradation process of structures so as to solve the calculation problem of time-varying reliability of mechanical structures. Based on the advanced first-order and second moment method (AFOSM), the proposed linearized Nataf change is used to complete the transformation from related nonnormal variables to independent standard normal variables in order to simplify the calculation process of reliability solution and solve the reliability calculation problem of random parameters subjected to arbitrary distribution. The deduced random variable sensitivity factor indicates the degree of influence of different random variables on the reliability of the mechanical structure, providing a theoretical basis for the optimal design and maintenance of a mechanical structure. The proposed method is analyzed using the cantilever beam and compared with the nonlinear Nataf transform and verified by the Monte Carlo simulation results. The results show that the proposed method can effectively solve the reliability sensitivity problem of structural system strength degradation.     

Evolutionary earthquake response of uncertain structure with bounded random parameter

The evolutionary earthquake response problem of an uncertain structure with bounded random parameters is solved in a unified way. Bounded random parameters, modelled by the λ-PDF, are more reasonable for engineering structures than the unbounded Gaussian random ones. The earthquake excitation is modelled as an evolutionary random process. The random structure is first transformed into an equivalent deterministic one by the Gegenbauer polynomial approximation. Then the evolutionary random response problem of the equivalent deterministic structure is solved by a unified approach formerly suggested by the last author. The essence of the orthogonal polynomial approximation is clearly explored. Numerical examples show that the proposed method is effective and practical.     

Sensitivity-based damage identification method for structures exposed to ground excitation

The purpose of this paper is to present a sensitivity-based finite element model (FEM) updating method using earthquake displacement response in the frequency domain and the frequency response function of structure due to ground excitation. The obtained sensitivity equation is solved by linear least square method through defining constraints on the design variables. Numerical examples of a plane truss and a plane frame support the fact that the proposed method is capable of reliable damage detection. In order to assess the effects of measurement and mass modelling errors on achieved results, model updating is conducted by adding random errors to numerically extracted displacement response and assigned mass properties. The issue of underlying soil foundation influences on obtained results is discussed and the proposed formulation is extended to more accurately capture the soil–structure behaviour. Results indicate that the proposed method is capable of identifying damage properties under different soil conditions with acceptable precision.