随机过程激励下随机结构系统可靠度分析的一种方法

提出了随机过程荷载激励下，具有随机参数的结构系统可靠度分析的一种方法，该方法基于首次超越破坏机制，分析随机过程荷载激励下，结构参数（随机变量）取某一确定向量时的条件失效概率，采用Ｍｏｎｔｅ Ｃａｒｌｏ技术模拟结构参数的随机性，由条件失效概率给出随机结构的无条件失效概率，最后对中方法和程序作了检验，并进行了实际计算。     

基于概率密度演化方法的地下结构可靠度分析

本文提出基于概率密度演化方法的地下结构可靠度分析,通过求解极限状态函数的概率密度演化方程,可以得到响应量的概率密度函数曲线.相比于传统的随机模拟方法,概率密度演化方法考虑了样本点之间的概率联系,因此在求解效率以及精度上都得到大大提高.文中结合上海市轨道交通M6线地铁下程进行了基于概率密度演化方法的可靠度分析,与随机模拟的结果相比表明,基于概率密度演化方法的地下结构可靠度分析方法具有更好的效果.文中还介绍了基于等价极值事件的结构体系可靠度分析方法,并将等价极值事件的基本思想推广到复杂失效准则下地下结构的可靠性分析之中.结果表明此方法可以对地下结构可靠度给出较为准确的评价.     

非线性随机结构动力可靠度的密度演化方法

建议了一类新的非线性随机结构动力可靠度分析方法。基于非线性随机结构反应分析的概率密度演化方法,根据首次超越破坏准则对概率密度演化方程施加相应的边界条件,求解带有初、边值条件的概率密度演化方程,可以给出非线性随机结构的动力可靠度。研究了数值计算技术,建议了具有自适应功能的TVD差分格式。以具有双线型恢复力性质的8层框架结构为例进行了地震作用下的动力可靠度分析,与随机模拟结果的比较表明,所建议的方法具有较高的精度和效率。     

基于可靠性约束的结构优化设计技术研究

建立结构重量最小化、可靠度为约束的优化模型。将结构近似为串联可靠度模型，每个元件作为一失效单元；由应力状况建立元件的失效函数。采用一次二阶矩法求解元件的可靠性指标；用元件失效概率的和来表示结构失效概率；将结构失效概率的允许值平分给元件，建立设计变量的显示迭代式，并用满可靠度法进行修正，获得最终设计结果。在开展结构静强度优化设计的同时，对元件在线弹性范围内的屈曲可靠性优化设计问题做了初步的研究。桁架结构和机翼盒段结构的可靠性优化结果表明，与现有方法相比，本文提出的方法在具有较高精度的同时，极大地提高了优化设计的效率。     

随机激励下的结构尺寸优化设计

将结构优化设计中的位移约束拓展为位移可靠度约束。基于首超破坏准则,采用概率密度演化方法分析了结构在随机激励下的位移可靠度。将遗传算法与概率密度演化方法相结合,对一个具有位移可靠度约束的十杆桁架进行了尺寸优化设计,实现了概率密度演化方法在结构优化设计中的成功运用。这一研究对于随机激励下的结构优化设计提供了新的途径,也为概率密度演化方法在结构优化设计中的运用进行了新的尝试。     

考虑随机模糊性时结构广义可靠度计算方法

在元件强度外载既具有随机性又具有模糊性而元件的状态具有确定性的分界线时，元件的可靠度和失效概率可以表示成条件概率，这样就可以在考虑设计人员的经验的情况下降低元件的失效概率，算例结果证明了此结论；文中的另一个内容是给出了元件和结构的状态不存在明确界线时可靠度和失效概率的计算方法，从而更客观地反映结构的安全程度．     

考虑随机模糊性叶结构广义可靠度计算方法

在元件强度外载既具有随机性又具有模糊性而元件的状态具有确定性的分界线时，元件的可靠度和失效概率可以表示成条件概率，这样就可以在考虑设计人员的经验的情况下降低元件的失效概率，算例结果证明了此结论文中的另一个内容是给出了元件的结构和状态下存在明确界线时可靠度和失效概率的计算方法，从而客观地反映了结构的安全程度。     

随机结构动力反应分析的概率密度演化方法

提出了随机结构动力反应分析的概率密度演化方法．基于有限单元法基本原理，导出了含有随机参数的结构反应状态方程，进而，通过引入扩展状态向量，建立了随机结构反应的概率密度演化方程．将精细时程积分方法与Lax-Wendroff差分格式相结合，探讨了求解概率密度演化方程的数值方法．对一个8层层间剪切型随机结构进行了算例分析，并与Monte Carlo方法的结果进行了比较．研究表明，随机结构反应的概率密度具有演化特征，且概率密度曲线与正态分布差异甚大，甚至可能出现双峰曲线．     

随机荷载作用下随机结构线性反应的概率密度演化分析

提出了随机荷载作用下随机结构线性静力反应的概率密度演化方法。基于力学平衡方程,导出了随机荷载作用下随机结构反应的状态方程,进而引入扩展状态向量,建立了随机荷载作用下的随机结构静力反应的概率密度演化方程,讨论了其差分数值求解技术,进行了八层框架结构在随机荷载作用下的反应的算例分析,在单一随机参数结构的情况下,与随机结构反应的精确解答进行了对比;对于多个随机参数结构随机反应,则与MonteCarlo分析结果进行了比较,研究表明,本文提出的方法具有很高的精度及良好的实用性。     

基于小子样试验的两种线性系统可靠度预测方法

本文提出了在小子样试验的前提下，结构系统关键失效模式可靠度预测的两各 一是基于抽样分布分析的转换法，在这种方法中，严格推导了元件强度和外和正态分布时，可靠度计算从正态分布概率积分到ｔ分布概率积分的转换。它适用于试验样本数不小于２的情况；其二是基于模糊学原理的加权平均法。此方法要求根据专家经验和现场数据，给出强度和载荷分布参数的隶属函数，然后用加权平均法给出结构系统关切关键失效模式的可靠度，这种方法     

Nonstationary probability densities of strongly nonlinear single-degree-of-freedom oscillators with time delay

The approximate nonstationary probability density of a nonlinear single-degree-of-freedom (SDOF) oscillator with time delay subject to Gaussian white noises is studied. First, the time-delayed terms are approximated by those without time delay and the original system can be rewritten as a nonlinear stochastic system without time delay. Then, the stochastic averaging method based on generalized harmonic functions is used to obtain the averaged Itô equation for amplitude of the system response and the associated Fokker–Planck–Kolmogorov (FPK) equation governing the nonstationary probability density of amplitude is deduced. Finally, the approximate solution of the nonstationary probability density of amplitude is obtained by applying the Galerkin method. The approximate solution is expressed as a series expansion in terms of a set of properly selected basis functions with time-dependent coefficients. The proposed method is applied to predict the responses of a Van der Pol oscillator and a Duffing oscillator with time delay subject to Gaussian white noise. It is shown that the results obtained by the proposed procedure agree well with those obtained from Monte Carlo simulation of the original systems.     

An approximation of the first passage probability of systems under nonstationary random excitation

An approximate method is presented for obtaining analytical solutions for the conditional first passage probability of systems under modulated white noise excitation. As the method is based on VanMarcke＇s approximation, with normalization of the response introduced, the expected decay rates can be evaluated from the second-moment statistics instead of the correlation functions or spectrum density functions of the response of considered structures. Explicit solutions to the second-moment statistics of the response are given. Accuracy, efficiency and usage of the proposed method are demonstrated by the first passage analysis of single-degree-of-freedom （SDOF） linear systems under two special types of modulated white noise excitations.     

一类Markov过程的最大绝对值过程概率密度求解的新方法

随机过程或随机系统响应的最大绝对值概率分布往往是科学与工程中关心的重要挑战性问题.本文从理论与数值上进行了Markov过程的时变最大绝对值过程及其概率分布研究.文中,通过引入扩展状态向量,构造了最大绝对值$\!$-$\!$-$\!$状态量联合向量过程,由此将不具有Markov性的最大值过程转化为具有Markov性的向量随机过程.在此基础上,通过最大绝对值$\!$-$\!$-$\!$状态量之间的关系,建立了联合向量过程的转移概率密度函数.进而,结合Chapman-Kolmogorov方程和路径积分方法,提出了最大绝对值概率密度函数求解的数值方法.由此,可以得到Markov过程最大绝对值过程的时变概率密度函数,可进一步用于结构动力可靠度分析等.通过数值算例,验证了本文所提方法的有效性. 该方法有望推广到更一般随机系统的极值分布估计之中.      

Transient stochastic response of quasi integerable Hamiltonian systems

The approximate transient response of quasi integrable Hamiltonian systems under Gaussian white noise excitations is investigated. First, the averaged Ito equations for independent motion integrals and the associated Fokker-Planck-Kolmogorov (FPK) equation governing the transient probability density of independent motion integrals of the system are derived by applying the stochastic averaging method for quasi integrable Hamiltonian systems. Then, approximate solution of the transient probability density of independent motion integrals is obtained by applying the Galerkin method to solve the FPK equation. The approximate transient solution is expressed as a series in terms of properly selected base functions with time-dependent coefficients. The transient probability densities of displacements and velocities can be derived from that of independent motion integrals. Three examples are given to illustrate the application of the proposed procedure. It is shown that the results for the three examples obtained by using the proposed procedure agree well with those from Monte Carlo simulation of the original systems.     

Transient stochastic response of quasi-partially integrable Hamiltonian systems

The approximate transient response of multi-degree-of-freedom (MDOF) quasi-partially integrable Hamiltonian systems under Gaussian white noise excitation is investigated. First, the averaged Itô equations for first integrals and the associated Fokker–Planck–Kolmogorov (FPK) equation governing the transient probability density of first integrals of the system are derived by applying the stochastic averaging method for quasi-partially integrable Hamiltonian systems. Then, the approximate solution of the transient probability density of first integrals of the system is obtained from solving the FPK equation by applying the Galerkin method. The approximate transient solution is expressed as a series in terms of properly selected base functions with time-dependent coefficients. The transient probability densities of displacements and velocities can be derived from that of first integrals. One example is given to illustrate the application of the proposed procedure. It is shown that the results for the example obtained by using the proposed procedure agree well with those from Monte Carlo simulation of the original system.     

OPTIMUM DESIGN BASED ON RELIABILITY IN STOCHASTIC STRUCTURE SYSTEMS

IntroductionIn traditional optimum structural math model,the target function and the constraintfunction are all considered as the certain value.But it does not accord to the actual forcedenvironment condition and structural status.Thus the optimum results…     

Constructing transient response probability density of non-linear system through complex fractional moments

The probability density function for transient response of non-linear stochastic system is investigated through the stochastic averaging and Mellin transform. The stochastic averaging based on the generalized harmonic functions is adopted to reduce the system dimension and derive the one-dimensional Itô stochastic differential equation with respect to amplitude response. To solve the Fokker–Plank–Kolmogorov equation governing the amplitude response probability density, the Mellin transform is first implemented to obtain the differential relation of complex fractional moments. Combining the expansion form of transient probability density with respect to complex fractional moments and the differential relations at different transform parameters yields a set of closed-form first-order ordinary differential equations. The complex fractional moments which are determined by the solution of the above equations can be used to directly construct the probability density function of system response. Numerical results for a van der Pol oscillator subject to stochastically external and parametric excitations are given to illustrate the application, the convergence and the precision of the proposed procedure.     

First-passage failure of strongly non-linear oscillators with time-delayed feedback control under combined harmonic and wide-band noise excitations

A procedure for studying the first-passage failure of strongly non-linear oscillators with time-delayed feedback control under combined harmonic and wide-band noise excitations is proposed. First, the time-delayed feedback control forces are expressed approximately in terms of the system state variables without time delay. Then, the averaged Itô stochastic differential equations for the system are derived by using the stochastic averaging method. A backward Kolmogorov equation governing the conditional reliability function and a set of generalized Pontryagin equations governing the conditional moments of first-passage time are established. Finally, the conditional reliability function, the conditional probability density and moments of first-passage time are obtained by solving the backward Kolmogorov equation and generalized Pontryagin equations with suitable initial and boundary conditions. An example is worked out in detail to illustrate the proposed procedure. The effects of time delay in feedback control forces on the conditional reliability function, conditional probability density and moments of first-passage time are analyzed. The validity of the proposed method is confirmed by digital simulation.