基于可靠度的结构优化的序列近似规划算法

基于可靠度的优化的最直观解法是把可靠度和优化的各自算法搭配一起形成嵌套两层次迭代。为改善其收敛性提高计算效率,人们提出了功能测度法、半无限规划法、单层次算法等多种改进方法。本文对传统结构优化界的经典序列近似规划法改造并扩展应用于求解基于可靠度的结构优化问题,构造该问题的序列近似规划模型和求解过程;其核心思想是在每个近似规划子问题中采用近似可靠度指标对设计变量的线性近似,在优化迭代过程中同步更新设计变量和随机空间中的近似验算点坐标,以达到可靠度分析和优化迭代同步收敛的目标。为了算法的实施,还推导出近似可靠度指标的半解析灵敏度计算公式,编制了程序,最终实现与通用软件的连接。论文用算例证实算法的有效性。     

最大熵法在可靠度计算中的应用

在可靠度计算中,任意对立随机变量往往为不同概率分布,不利于可靠度计算。通常采用正态转换法将其转换成具有统一形式的正态分布,以便进行可靠度计算。但是,正态转换并不能保证原有随机变量概率分布特性,从而一定程度上造成可靠度计算误差。针对上述问题,本文提出在可靠度计算中利用最大熵法将任意随机变量概率密度函数转换成近似精度更高且具有统一标准形式的最大熵概率密度函数(MEPDF),然后提出对应的一阶可靠度计算方法进行可靠度求解,最后通过实例分析证明该方法的有效性。     

平稳随机激励下耦合Newmark滑移系统的可靠性分析

基于随机激励的离散形式,对耦合Newmark系统的动力可靠度问题进行解析分析。平稳随机激励下,耦合Newmark系统初始滑移极限状态方程可以写成n个标准正态随机变量的显式线性函数,并能给出可靠度指标的理论解。对于以相对滑移量为临界状态的情况,极限状态方程是n个标准正态随机变量的隐式函数,可借助静力可靠度方法进行求解。算例表明,系统初始滑移的设计点激励是以潜在滑动体自振频率为主频,振幅渐增的谐振时程;后者的失效概率与摩擦系数成非线性关系,存在合适的摩擦系数使失效概率最小。     

盐渍土输电铁塔基础耐久性可靠度敏感性研究

建立盐渍土条件下的输电铁塔基础耐久性预测模型,采用基本灵敏度因子定义相对均值和均方差灵敏度因子;以哈密南-郑州±800k V直流特高压线路为背景,计算了其中甘3标段某斜柱式基础耐久性可靠度对基础结构、混凝土材料、配筋、基础施工、外界环境等随机变量的相对均值和均方差灵敏度因子。一方面,通过对比各灵敏度因子,研究了各随机变量对基础耐久性可靠度的敏感性,为基础耐久性设计提供指导;另一方面,通过讨论相对均方差灵敏度因子,结合基础耐久性可靠度指标相对误差,给出了将随机变量视为确定性变量以减少模型中随机变量维数的判定方法,避免传统重复试算的繁琐。     

随机参数多自由度体系在平稳随机反应下的系统动力可靠性

对具有随机参数的多自由度体系,提出了求解其系统动力可靠度上、下限的一种计算方法。考虑结构的物理和几何参数具有随机性,从结构随机响应的频域表达式出发,利用求解随机变量数字特征的代数综合法和矩法,导出了随机参数多自由度体系在平稳随机激励下的平稳随机反应均方值的数字特征,再由动力可靠性的Poisson公式导出了随机参数结构的动力可靠度的计算公式,然后根据系统可靠性分析方法,分析了随机参数多自由度体系的系统动力可靠性,最后给出了系统动力可靠度上、下限的计算公式,并给出一个算例。     

结构可靠度的虚拟变量算法

从与结构失效函数有关随机变量均值和协方差的确定性特征出发 ,提出了准确计算结构可靠度的一种虚拟变量算法。使用虚拟变量算法时 ,只需给出失效函数就能正确算出结构的可靠度。由于无需人工确定失效函数的偏导数 ,计算较为简单 ,当失效函数形式复杂、与失效函数有关随机变量较多时 ,可使计算效率得到显著提高     

锅炉省煤器和空气预热器振动可靠性分析的研究

提出了锅炉尾部受热面的振动可靠性分析方法。该方法把卡门漩涡频率和声学驻波频率处理为随机变量，使用概率设计法确定锅炉省煤器和管式空气预热器避开声振动的可靠度。文中给出了管式空气预热器振动可靠性分析的实例。     

汽轮机动叶片的可靠性设计方法

提出了汽轮机叶片可靠性设计方法,介绍了叶片可靠性的含义和计算方法。该方法以概率论和统计学为基础,把汽轮机叶片的静应力、动应力、叶片疲劳强度、叶片安全倍率、叶片振动频率和激振力频率处理为随机变量,通过试验数据的统计分析和计算,确定有关随机变量的分布参数。使用概率设计法、应力与强度干涉模型确定汽轮机叶片疲劳强度和振动设计的可靠度。文中给出了叶片疲劳强度的动应力设计法和安全倍率设计法以及第一种调频叶片、第二种调频叶片和整圈连接叶片组的振动可靠性设计的计算公式和一些应用实例。使用这些方法,可以在设计阶段确定汽轮机叶片设计的可靠度,为汽轮机叶片的可靠性设计提供了科学的依据。     

考虑材料性能空间分布不确定性的可靠度拓扑优化

论文研究了考虑材料性能空间分布不确定性的连续体结构可靠度拓扑优化问题。其中,材料的弹性模量视为具有给定概率分布特征的随机场,其离散采用级数最优线性估值法（EOLE）。随机结构的响应以及相应的灵敏度分析采用多项式混沌展开（PCE）近似表达,并采用Monte Carlo方法验证了该方法的精度。结构的可靠度分析采用一次可靠度方法（FORM）,在优化问题的求解中,对双层嵌套方法和序列近似规划（SAP）方法进行了对比。数值算例中,该方法应用于二维和三维结构的拓扑优化问题,优化结果验证了方法的正确性和有效性。     

非完整信息条件下的结构可靠性鲁棒设计

在非完整信息条件下,建立区间变量、模糊变量、随机变量同时存在的可靠性设计模型,并给出相应的序列优化设计方法;同时考虑设计变量的实现值与设计值之间的差别以及约束条件的鲁棒性,提出基于info-gap决策理论的鲁棒优化模型,研究可靠性鲁棒设计的序列求解策略。算例1表明:模糊可靠性设计比随机可靠性设计结果保守,当模糊设计指标α=0时(对应区间可靠度)结果最为保守。算例2表明:不同的鲁棒性指标αt对应不同的鲁棒优化解,当αt大于0.20时,不存在相应的鲁棒优化解。利用本文提出的鲁棒序列优化求解方法对目标函数计算1291次即可,而常规优化算法需8107次,表明本文算法大大提高了计算效率。     

Reliability evaluation and control for wideband noise-excited viscoelastic systems

Reliability of first-passage type for wideband noise-excited viscoelastic systems and the quasi-optimal bounded control strategy for maximizing system reliability are investigated. The viscoelastic term is approximately replaced by equivalent damping and stiffness separately. By using the stochastic averaging method based on the generalized harmonic functions, the averaged Itô stochastic differential equation is obtained for the system amplitude. The associated backward Kolmogorov equation is derived and solved to obtain the system reliability. By applying the dynamic programming principle to the averaged system, the quasi-optimal bounded control is devised by maximizing system reliability. The application of the proposed analytical procedures and the effectiveness of the control strategy are illustrated through one example.     

Frequency Reliability-Based Robust Design of the Suspension Device of a Jarring Machine with Arbitrary Distribution Parameters

The frequency reliability with arbitrary distribution parameters in the stochastic dynamic structure system of practical engineering and its related theories were studied deeply in the paper. The frequency reliability method of avoiding resonance was proposed by mechanical dynamics, stochastic finite element method, and reliability theory. Then the frequency reliability formula with arbitrary distribution parameters was deduced through Edgeworth series method. Furthermore, the frequency reliability sensitivity method was presented based on the frequency reliability research, which provided a preliminary efficient way to analyze how each random parameter contributed to the system reliability. Moreover, the frequency reliability-based robust design method of the stochastic dynamic structure system was obtained by robust and optimization technology on the basis of frequency reliability and sensitivity method, which helped designers to establish acceptable parameter values and to determine the fluctuations of the parameters for the safe operations. Meanwhile, a numerical example of the suspension device of a jarring machine with arbitrary distribution parameters was provided and studied, the numerical results were in agreement with practice, which demonstrated the efficiency and accuracy of the proposed methods.     

Feedback minimization of first-passage failure of quasi integrable Hamiltonian systems

A nonlinear stochastic optimal control strategy for minimizing the first-passage failure of quasi integrable Hamiltonian systems (multi-degree-of-freedom integrable Hamiltonian systems subject to light dampings and weakly random excitations) is proposed. The equations of motion for a controlled quasi integrable Hamiltonian system are reduced to a set of averaged Itô stochastic differential equations by using the stochastic averaging method. Then, the dynamical programming equations and their associated boundary and final time conditions for the control problems of maximization of reliability and mean first-passage time are formulated. The optimal control law is derived from the dynamical programming equations and the control constraints. The final dynamical programming equations for these control problems are determined and their relationships to the backward Kolmogorov equation governing the conditional reliability function and the Pontryagin equation governing the mean first-passage time are separately established. The conditional reliability function and the mean first-passage time of the controlled system are obtained by solving the final dynamical programming equations or their equivalent Kolmogorov and Pontryagin equations. An example is presented to illustrate the application and effectiveness of the proposed control strategy.     

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.     

Feedback minimization of first-passage failure of quasi non-integrable Hamiltonian systems

The non-linear stochastic optimal control of quasi non-integrable Hamiltonian systems for minimizing their first-passage failure is investigated. A controlled quasi non-integrable Hamiltonian system is reduced to an one-dimensional controlled diffusion process of averaged Hamiltonian by using the stochastic averaging method for quasi non-integrable Hamiltonian systems. The dynamical programming equations and their associated boundary and final time conditions for the problems of maximization of reliability and of maximization of mean first-passage time are formulated. The optimal control law is derived from the dynamical programming equations and the control constraints. The dynamical programming equations for maximum reliability problem and for maximum mean first-passage time problem are finalized and their relationships to the backward Kolmogorov equation for the reliability function and the Pontryagin equation for mean first-passage time, respectively, are pointed out. The boundary condition at zero Hamiltonian is discussed. Two examples are worked out to illustrate the application and effectiveness of the proposed procedure.     

First passage failure of quasi-partial integrable generalized Hamiltonian systems

The first passage failure of quasi-partial integrable generalized Hamiltonian systems is studied by using the stochastic averaging method. First, the stochastic averaging method for quasi-partial integrable generalized Hamiltonian systems is introduced briefly. Then, the backward Kolmogorov equation governing the conditional reliability function and the Pontryagin equation governing the conditional mean of first passage time are derived from the averaged Itô equations. The conditional reliability function, the conditional probability density and mean of the first passage time are obtained from solving these equations together with suitable initial condition and boundary conditions, respectively. Finally, one example is given to illustrate the proposed procedure in detail and the solutions are confirmed by using the results from Monte Carlo simulation of the original system.     

First-passage failure and its feedback minimization of quasi-partially integrable Hamiltonian systems

An n degree-of-freedom Hamiltonian system with r(1<r<n) independent first integrals which are in involution is called partially integrable Hamiltonian system. A partially integrable Hamiltonian system subject to light dampings and weak stochastic excitations is called quasi-partially integrable Hamiltonian system. In the present paper, the procedures for studying the first-passage failure and its feedback minimization of quasi-partially integrable Hamiltonian systems are proposed. First, the stochastic averaging method for quasi-partially integrable Hamiltonian systems is briefly reviewed. Then, based on the averaged Itô equations, a backward Kolmogorov equation governing the conditional reliability function, a set of generalized Pontryagin equations governing the conditional moments of first-passage time and their boundary and initial conditions are established. After that, the dynamical programming equations and their associated boundary and final time conditions for the control problems of maximization of reliability and of maximization of mean first-passage time are formulated. The relationship between the backward Kolmogorov equation and the dynamical programming equation for reliability maximization, and that between the Pontryagin equation and the dynamical programming equation for maximization of mean first-passage time are discussed. Finally, an example is worked out to illustrate the proposed procedures and the effectiveness of feedback control in reducing first-passage failure.     

Optimal bounded control for maximizing reliability of Duhem hysteretic systems

The optimal bounded control of stochastic-excited systems with Duhem hysteretic components for maximizing system reliability is investigated. The Duhem hysteretic force is transformed to energy-depending damping and stiffness by the energy dissipation balance technique. The controlled system is transformed to the equivalent nonhysteretic system. Stochastic averaging is then implemented to obtain the Itô stochastic equation associated with the total energy of the vibrating system, appropriate for evaluating system responses. Dynamical programming equations for maximizing system reliability are formulated by the dynamical programming principle. The optimal bounded control is derived from the maximization condition in the dynamical programming equation. Finally, the conditional reliability function and mean time of first-passage failure of the optimal Duhem systems are numerically solved from the Kolmogorov equations. The proposed procedure is illustrated with a representative example.     

随机激励的耗散的Hamilton系统理论的研究进展

近几年中,利用Ｈａｍｉｌｔｏｎ系统的可积性与共振性概念及Ｐｏｉｓｓｏｎ括号性质等,提出了高斯白噪声激励下多自由度非线性随机系统的精确平稳解的泛函构造与求解方法,并在此基础上提出了等效非线性系统法,提出了拟Ｈａｍｉｌｔｏｎ系统的随机平均法,并在该法基础上研究了拟Ｈａｍｉｌｔｏｎ系统随机稳定性、随机分岔、可靠性及最优非线性随机控制,从而基本上形成了一个非线性随机动力学与控制的Ｈａｍｉｌｔｏｎ理论框架．本文简要介绍了这方面的进展．