基于截尾概率-非概率混合模型的可靠性优化算法

针对工程中截尾概率变量与非概率变量同时存在的情况,给出一种新的截尾概率与非概率混合可靠性模型。在该混合可靠性模型基础上,按照可靠性指标(RIA)法给出双层嵌套可靠性优化模型,并采用改进搜索策略后的ST-Powell优化算法在外层搜索设计变量的最优值,内层采用能保证收敛的改进的有限步长迭代法求解混合可靠性指标。数值算例表明,改进搜索策略后的ST-Powell优化算法的全局寻优性得到显著提升;改进搜索策略后的ST-Powell优化算法与改进的有限步长迭代法相结合求解双层嵌套混合可靠性优化模型的正确性得到验证,且对于非线性程度较高的极限状态函数同样能够得到满足截尾概率与非概率混合可靠性模型指标要求的最优解,并对工程结构算例具有很好的适应性。     

基于人工蜂群算法与NURBS的吸附式叶型优化设计

为提高轴流压气机吸附式叶型优化设计的质量,设计了一套基于人工蜂群(ABC)算法和非均匀有理B样条(NURBS)的自动优化设计系统.对人工蜂群算法的运行机制进行了深入分析,并与目前广泛使用的遗传算法(GA)进行了对比.对比发现人工蜂群算法可以更好地逼近全局最优值且收敛效率提高50%.使用NURBS对叶型进行参数化,并研究了参数化过程中的畸变问题.将抽吸参数与叶栅参数同时作为优化变量,使用该系统对一吸附式叶栅进行了优化.结果显示:抽吸槽设置在58.44%轴向弦长位置处流动损失下降明显,与优化前未抽吸叶型相比流动损失降低64.8%,气流分离得到有效抑制.     

Neural Networks Combined with Importance Sampling Techniques for Reliability Evaluation of Explosive Initiating Device

Concerning the issue of high-dimensions and low-failure probabilities including implicit and highly nonlinear limit state function, reliability analysis based on the directional importance sampling in combination with the radial basis function (RBF) neural network is used, and the RBF neural network based on first-order reliability method (FORM) is to approximate the unknown implicit limit state functions and calculate the most probable point (MPP) with iterative algorithm. For good efficiency, based on the ideas that directional sampling reduces dimensionality and importance sampling focuses on the domain contributing to failure probability, the joint probability density function of importance sampling is constructed, and the sampling center is moved to MPP to ensure that more random sample points draw belong to the failure domain and the simulation efficiency is improved. Then the numerical example of initiating explosive devices for rocket booster explosive bolts demonstrates the applicability, versatility and accuracy of the approach compared with other reliability simulation algorithm.     

基于粒子群和人工蜂群混合算法的气动优化设计

现代启发式智能算法存在全局与局部搜索能力的平衡问题,针对此问题,采用双种群进化策略和信息交流机制,提出一种基于粒子群算法和人工蜂群算法相结合的新型混合优化算法——MABCPSO,并分别进行函数测试和翼型的气动优化设计验证。结果表明:MABCPSO新型混合优化算法具有更好的寻优能力,相比粒子群算法和人工蜂群算法,该算法能以更少的进化代数分别提高1.7%和2.2%的减阻效果。     

截断分布下广义失效概率的可靠性分析方法

提出基于随机变量为截断分布和失效域模糊下的结构可靠性分析方法。由于常规的可靠性分析方法不能直接用于截断分布情况下广义失效概率的计算,因此,先将截断分布情况下的可靠性分析模型转化为非截断分布情况下的多模式并联系统模型,在此基础上引入模糊失效域的隶属函数,将截断分布情况下的模糊可靠性分析问题转化为一般的随机可靠性问题,利用Monte Carlo法和重要抽样法求得广义失效概率。给出了方法的实现步骤和原理,并用不同算例验证了方法的合理性与可行性。     

基于幂律退化轨道的小样本性能可靠性评定

结合航空航天领域高可靠、长寿命产品试验小子样的特点,运用性能退化可靠性理论和Bayes方法,对系统可靠性的统计推断方法进行了研究.首先对基于Bayes方法幂律退化轨道参数的计算模型进行研究,然后结合随机变量函数的分布的计算,推导出系统可靠性后验估计和置信下限估计的计算公式.在理论推导的基础上,结合工程实例说明该方法的有效性.     

Uncertain multiobjective redundancy allocation problem of repairable systems based on artificial bee colony algorithm

Based on the uncertainty theory, this paper is devoted to the redundancy allocation problem in repairable parallel-series systems with uncertain factors, where the failure rate, repair rate and other relative coefficients involved are considered as uncertain variables. The availability of the system and the corresponding designing cost are considered as two optimization objectives. A crisp multiobjective optimization formulation is presented on the basis of uncertainty theory to solve this resultant problem. For solving this problem efficiently, a new multiobjective artificial bee colony algorithm is proposed to search the Pareto efficient set, which introduces rank value and crowding distance in the greedy selection strategy, applies fast non-dominated sort procedure in the exploitation search and inserts tournament selection in the onlooker bee phase. It shows that the proposed algorithm outperforms NSGA-II greatly and can solve multiobjective redundancy allocation problem efficiently. Finally, a numerical example is provided to illustrate this approach.     

基于名义极限因子和降维方法的涡轮盘结构可靠性优化

结合名义极限因子方法完全实现了可靠性分析与优化过程的解耦,使可靠性分析成为进行优化之前的预分析过程,而在预分析中采用的基于降维的可靠性分析技术,在一阶可靠度方法(FORM)获得的计算结果的基础上进行适晕的数值计算就能够提高可靠性分析的结果.最后,以某涡轮盘结构优化为例对提出的方法可行性和效率进行了验证,结果表明:该方法...     

基于优化Kriging模型和重要抽样法的结构可靠度混合算法

 结构可靠度分析计算通常采用多项式响应面拟合隐式极限状态函数,但对于复杂航空航天机械结构产品极限状态方程往往表现出高度非线性,此时多项式响应面的模拟精度不够就会造成计算不收敛。为了提高结构可靠度计算的精度、效率和收敛性,提出了基于优化Kriging模型和重要抽样法的结构可靠度计算方法。首先,利用人工蜂群算法对Kriging模型的参数进行优化;再用优化后的模型模拟隐式极限状态函数,结合重要抽样法不断修正抽样重心,逐步提高模拟精度以达到给定要求;最后,结合一阶矩法(FORM)/二阶矩法(SORM)经典算法求解结构可靠度。该方法提高了高度非线性隐式极限状态方程可靠度计算的精度和收敛性,并且具有较高的计算效率。     

Hybrid uncertainty-based design optimization and its application to hybrid rocket motors for manned lunar landing

Design reliability and robustness are getting increasingly important for the general design of aerospace systems with many inherently uncertain design parameters. This paper presents a hybrid uncertainty-based design optimization (UDO) method developed from probability theory and interval theory. Most of the uncertain design parameters which have sufficient information or experimental data are classified as random variables using probability theory, while the others are defined as interval variables with interval theory. Then a hybrid uncertainty analysis method based on Monte Carlo simulation and Taylor series interval analysis is developed to obtain the uncer-tainty propagation from the design parameters to system responses. Three design optimization strategies, including deterministic design optimization (DDO), probabilistic UDO and hybrid UDO, are applied to the conceptual design of a hybrid rocket motor (HRM) used as the ascent propulsion system in Apollo lunar module. By comparison, the hybrid UDO is a feasible method and can be effectively applied to the general design of aerospace systems.     

A new structural reliability analysis method in presence of mixed uncertainty variables

For structures with both random and fuzzy uncertainty, this paper presents a novel method for determining the membership function in fuzzy reliability with the Automatic Updating Extreme Response Surface (AUERS) method. In the proposed method, fuzzy variables are initially converted into a value domain under the given cut level and the extreme point in the domain where the reliability reaches its extreme value is considered. Second, the Particle Swarm Optimization (PSO) algorithm is used to determine the extreme point according to the extreme responses for different sets of random sample inputs. A kriging response surface is subsequently constructed between the random variables and the corresponding extreme points. An automatic updating strategy is then introduced based on the Relative Mean Square Predicted Error (RMSPE) before performing every iteration of reliability analysis. By adding new sample points, the approximate quality of the kriging response surface is improved. Finally, reliability analysis is used to determine the reliability bound under the given cut level. The proposed method assures the accuracy and computation efficiency of the mixed uncertainty reliability analysis results while it prevents the solution from becoming trapped in a local optimum, which occurs in classical optimization methods. Two example analyses are used to demonstrate the validity and advantages of the proposed method.     

变量相关情况下基于马尔可夫链样本模拟的线抽样可靠性灵敏度分析方法

针对变量具有相关性的可靠性灵敏度分析问题,提出了一种变量相关情况下基于马尔可夫链样本模拟的线抽样可靠性灵敏度分析方法。在所提方法中,首先将相关变量等价转换为独立正态变量,然后采用基于马尔可夫链样本模拟的线抽样方法,求解失效概率对等价独立正态变量分布参数的偏导数,最后利用等价变换前后变量分布参数之间的解析关系和复合函数求导法则,求得失效概率对相关变量分布参数的可靠性灵敏度。为了解所提方法的效率和精度,对所提方法的可靠性灵敏度估计值进行了方差分析。由于所提方法采用马尔可夫链快速产生失效域中的条件样本,这些失效域中的样本可用来准确获取重要方向,并可作为线抽样的随机样本,因而该方法具有很高的抽样效率。算例结果表明,所提方法是一种计算相关变量可靠性灵敏度的高效率、高精度方法。     

基于等基因序列双重随机遗传算法的复合材料铺层优化

复合材料铺层优化中常用的各种遗传算法，较难同时综合考虑表面45°、分层比例、连续铺层数限制等复杂工程约束问题，基于此，提出一种针对复合材料层压板的等基因序列双重随机遗传算法，在交换和突变算子中引入双重随机算法以保证优化迭代中基因序列的严格相等，基于SABRE 软件实现该优化算法，并通过算例验证算法的正确性。结果表明：该算法可满足均衡性、对称性、表面45°、连续铺层数限制、铺层比例等复杂工程约束，有较高的可靠性与工程适用性。     

Reliability and Sensitivity Analysis of Transonic Flutter Using Improved Line Sampling Technique

The improved line sampling (LS) technique, an effective numerical simulation method, is employed to analyze the probabilistic characteristics and reliability sensitivity of flutter with random structural parameter in transonic flow. The improved LS technique is a novel methodology for reliability and sensitivity analysis of high dimensionality and low probability problem with implicit limit state function, and it does not require any approximating surrogate of the implicit limit state equation. The improved LS is used to estimate the flutter reliability and the sensitivity of a two-dimensional wing, in which some structural properties, such as frequency, parameters of gravity center and mass ratio, are considered as random variables. Computational fluid dynamics (CFD) based unsteady aerodynamic reduced order model (ROM) method is used to construct the aerodynamic state equations. Coupling structural state equations with aerodynamic state equations, the safety margin of flutter is founded by using the critical velocity of flutter. The results show that the improved LS technique can effectively decrease the computational cost in the random uncertainty analysis of flutter. The reliability sensitivity, defined by the partial derivative of the failure probability with respect to the distribution parameter of random variable, can help to identify the important parameters and guide the structural optimization design.     

飞机舱门锁机构多失效模式可靠性分析方法

如何提高飞机舱门锁机构关闭系统的可靠性计算效率,减少计算时间,降低舱门故障率是亟待解决的 问题。选取某型飞机舱门锁机构为研究对象,通过 LMS建立飞机舱门锁机构仿真模型,研究锁机构关闭过程 中最大液压力失效和关锁时间失效模式的影响因素,考虑两种失效模式之间的相关性,基于重要抽样法和 B-P 神经网络方法,计算飞机舱门锁机构多失效模式下的可靠性;将这两种方法仿真计算结果与传统蒙特卡罗方法 计算结果进行对比,结果表明:以上两种计算飞机舱门锁机构可靠性的方法是合理的,其误差范围均在3%以 内,且两种方法的计算效率相较于传统方法均有所提高;其中,B-P神经网络方法比重要抽样法计算精度和效 率更高,更适用于研究飞机舱门锁机构的可靠性问题。     

基于改进人工蜂群算法的多值属性系统故障诊断策略

针对实际工程应用中常见的多值属性系统故障诊断策略问题,在传统人工蜂群算法(Artificial Bee ColonyAlgorithm,简称 ABC算法)的基础上,提出改进蜂群算法用于多值属性系统的测试序列寻优。首先,在蜂群算法中重新定义多值 D矩阵和五元组的含义;其次,引入方向信息概率矩阵,设置状态转移规则和矩阵元素更新策略;最后,采用导弹舵系统实例说明算法的实现过程和有效性。最终测试序列寻优结果表明:与传统的多值 Rollout算法相比,文中所提算法能得到较好的诊断策略结果,具有一定的应用价值。     

Kriging模型及代理优化算法研究进展

代理模型方法由于能显著提高工程优化设计问题的效率,在航空航天及其他领域得到了广泛重视,并逐渐发展成为一类优化算法,本文称其为代理优化（SBO）算法。在现有的代理模型方法中,如多项式响应面、径向基函数、神经网络、支持向量回归、多变量插值/回归、多项式混沌展开等,源于地质统计学的Kriging模型具有代表性,是一种非常具有应用潜力的代理模型方法。以飞行器设计领域的优化问题为背景,介绍了Kriging代理模型及应用于优化设计的理论和算法的最新研究进展。首先,概述了Kriging模型的基本理论和算法,并讨论了影响Kriging模型鲁棒性和效率的几个关键性问题。其次,回顾了Kriging模型理论和算法研究的3个最新研究进展,包括梯度增强型Kriging、CoKriging和分层Kriging模型。而后,分析提炼了基于Kriging模型的代理优化算法的优化机制和优化框架,给出了“优化加点准则”和“子优化”的概念,并介绍了目前常用的几种优化加点准则及其相应子优化问题的求解与约束处理;同时,还介绍了最新提出的局部EI加点准则以及代理优化的终止条件。最后,介绍了代理优化在标准测试函数算例验证、飞行器气动与多学科优化设计典型算例确认方面的研究进展,并对当前存在的一些关键科学问题以及未来研究方向进行了讨论。     

结构系统可靠性及可靠性灵敏度分析的改进子集模拟法

在再生自适应子集模拟(RASS)法的基础上,提出了一种改进的再生自适应子集模拟(MRASS)法以用于结构系统的可靠性及可靠性灵敏度分析。MRASS法继承了RASS法中马尔可夫链再生、延迟拒绝、自适应马尔可夫过程及分量各自采样等优点,并改进了自适应采样过程。MRASS法通过对产生的样本点的接受率与最佳接受率进行比较,有针对性地寻找合适的建议分布方差,提高了抽样的效率。工程算例的数值结果表明:MRASS法相比于RASS法及传统的子集模拟(SS)法,在处理具有高维随机变量、小失效概率及高度非线性特点的结构系统时,有更好的适应性、稳健性及精度。     

考虑模糊失效准则的结构疲劳寿命可靠性

 针对常规设计中对功能函数失效状态规定与常识不符这种情况,提出了考虑模糊失效准则的结构疲劳寿命可靠性,将结构寿命视为随机变量,而设计寿命视为模糊变量,研究了设计寿命服从线性L-R分布时的结构疲劳寿命可靠度,给出了随机载荷下结构疲劳寿命概率密度函数的确定方法,并提出了随机变量与模糊变量相组合时的一种新的可靠度数值计算方法,该方法先利用Gauss-Legendre积分将模糊可靠度求解的二次积分转换成一次积分,列出与Legendre多项式零点相对应的阀值,然后在给定的阀值下,将设计寿命转化成普通的截集区间,在截集区间内假定结构疲劳寿命概率密度函数服从均匀分布,利用Monte Carlo模拟得到对应于该阀值的结构疲劳寿命可靠度值。数值结果表明,常规设计下结构的疲劳寿命可靠度偏于危险。     

某型飞机平尾转轴可靠性灵敏度分析

采用了基于改进一次二阶矩法、基于Monte-Carlo直接模拟法、基于重要抽样法的可靠性灵敏度分析方法以及一种基于重要抽样的可靠性灵敏度分析方法,对某型飞机平尾转轴进行可靠性灵敏度的求解,并分析了某型飞机平尾转轴可靠性灵敏度随变异系数变化的趋势,为其可靠性设计提供了参考信息。通过4种方法结果相比较,可以说明各种方法的特点并验证了它们在工程问题上的可行性。