结构可靠性灵敏度因子的一种新指标

通过对可靠性灵敏度的分析和推导,利用灵敏度标准差值构造了一种新的可靠性灵敏度因子。与传统灵敏度因子不同的是,新因子不仅能反映各随机变量对结构失效概率影响的重要性程度,因子的数值大小还能表征将单个变量作为确定性变量处理或将多个变量同时作为确定性量处理时所引起的可靠指标误差大小。据此结论,采用新灵敏度因子进行灵敏度分析时,只需要进行一次分析就能识别出各随机变量对结构失效整体影响的有益信息,可以有效地提高计算效率,降低分析难度。利用数值算例验证说明了所提可靠性灵敏度因子指标的有效性。     

腐蚀油气管线的可靠性分析

ASME B31G是国际通用的评价腐蚀管线失效应力的标准,考虑到这种方法的保守性,以修正后的B31G模型作为研究腐蚀管线失效应力的基础,考虑管壁厚度、腐蚀速率、工作压力、缺陷深度等随机变量,构建腐蚀油气管线可靠性极限状态函数。然后,采用一次二阶矩法对腐蚀管线进行可靠性分析,得出管线的失效概率、可靠性指标以及剩余使用寿命。此外,为了更加规范的管理腐蚀管线,参照美国石油组织的相关规定,对不同失效概率的管线进行了等级划分。在最后的案例分析中,还讨论失效概率对不同变异系数对的敏感性,计算结果表明失效概率对管壁厚度的变异系数最为敏感。     

可靠性灵敏度分析的自适应重要抽样法

基于全局优化的模拟退火方法,提出了结构可靠性灵敏度分析的自适应重要抽样方法。所提方法由模拟退火来逐步寻找结构最可能失效点,通过逐步优化的最可能失效点来构建可靠性灵敏度分析所需的重要抽样函数。从重要抽样密度函数中抽取样本,来对结构可靠性灵敏度作无偏估计,推导了可靠性灵敏度估计量方差和变异系数的计算公式。与基于Monte-Carlo法的可靠性参数灵敏度分析相比,该方法具有更高的抽样效率,算例证明了所提方法的优越性。     

钢管混凝土短柱极限承载力可靠度分析

基于《建筑结构可靠度设计统一标准》(GB50068-2001),利用一次二阶矩法(JC法)对圆钢管混凝土轴压短柱的极限承载力进行了可靠度校准。结果表明,钢管混凝土构件的可靠指标随着混凝土强度等级的提高而提高,随着钢材强度、含钢率及套箍指标的提高而降低;此外钢材种类、荷载组合以及荷载效应比等也对钢管混凝土构件可靠指标有一定程度的影响。按照建议的分项系数值,能较好的满足《建筑结构可靠度设计统一标准》可靠指标的要求。     

平面连杆机构运动精度可靠性灵敏度设计

 将可靠性设计理论与灵敏度分析方法相结合,讨论平面连杆机构运动精度可靠性灵敏度设计问题.提出可靠性灵敏度设计的计算方法,给出可靠性灵敏度的变化规律,研究设计参数的改变对平面连杆机构运动精度可靠性的影响,为平面连杆机构设计提供理论依据.     

结构可靠性灵敏度分析的低偏差抽样方法

由于蒙特卡罗(MC)方法具有程序结构简单,收敛速度与问题维数无关等优点,故其在结构可靠性及可靠性灵敏度分析中得到了广泛应用。但是计算效率低这一主要缺点限制了该方法的应用范围。通过引进单位超立方体中不同的低偏差点集代替伪随机数序列,并结合重要抽样技术建立了结构可靠性灵敏度分析的低偏差抽样方法。该方法不但可以大幅度减少抽样点数目,还能够得到确定性的估计值避免传统MC方法只能得到概率意义下误差的缺陷。通过数值算例可以看出该方法具有较高的计算精度和效率。     

压杆稳定可靠性灵敏度设计

在稳定可靠性设计理论与灵敏度分析方法的基础上,研究了压杆稳定可靠性灵敏度设计问题。提出了稳定可靠性灵敏度设计的计算方法,给出了压杆可靠性灵敏度的变化规律,研究了设计参数的改变对压杆稳定可靠性的影响,为压杆稳定可靠性设计提供了理论依据。     

模糊随机桁架结构可靠性指标的灵敏度分析

在结构有限元分析基础之上研究了模糊随机桁架的可靠性指标对设计变量的灵敏度问题.同时考虑结构参数和荷载的模糊随机性,在利用双因子法得出结构模糊随机响应及其模糊数字特征的基础之上,推导了结构的可靠性指标对设计变量的灵敏度.通过算例验证了该方法的可行性,得出了若干有意义的结论.     

就地化保护装置跌落冲击载荷下的可靠性分析

目的 为了评估就地化保护装置跌落冲击载荷下的失效情况。方法 基于显式动力学理论,采用有限元法对就地化保护装置进行跌落冲击的建模仿真。分析PCB板变形与焊点失效之间的关系,探讨元件封装方式对产品抗跌落冲击性能的影响,提出以Von Mises准则得到的焊点最大应力联合跌落寿命模型,进行元件封装可靠性评估的分析方法。针对元件不同封装方式的装置进行跌落验证试验。结果 就地化保护装置跌落冲击仿真结果与试验结果基本吻合。结论 验证了评估元件封装失效分析方法的准确性,为推断产品可靠性提供了理论支撑。     

随机激励下随机结构动力可靠性灵敏度分析

对于随机激励下随机结构动力可靠性的灵敏度分析问题,在加权非线性响应面法的基础之上建立了随机结构动力可靠性灵敏度分析方法.所提方法从随机结构无条件动力可靠度的表达式出发,首先将随机结构的动力可靠性分析问题转化成传统的静力可靠性分析问题,然后采用基于加权非线性响应面法的Monte-Carlo可靠性灵敏度分析方法求解动力可靠性灵敏度值.算例表明该方法的计算结果是合理的,并且由于加权非线性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.     

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.     

基于BP神经网络的引信贮存可靠性预计

根据引信贮存可靠性的特点和BP神经网络结构．建立了引信贮存可靠性预计的神经网络模型;结合库存引信可靠性的实测数据,应用BP神经网络的误差反向传播算法．对引信贮存可靠度进行了训练并预计出引信贮存可靠度下限值,并与极大似然估计的可靠度下限值进行了比较,结果相吻合．神经网络在引信贮存可靠性预计中的应用．对处理目前库存引信的决策具有重要意义．     

Reliability analysis in fracture mechanics using the first-order reliability method and Monte Carlo simulation

The development of a Windows‐based framework to undertake probabilistic fracture mechanics studies is reported. For a selective library of standard case problems, the reliability index of critical and sub‐critical (fatigue) problems with stochastic definition is evaluated. Both first‐order reliability method (FORM) as well as and Monte Carlo simulation method (MCS) techniques are used in critical crack growth, and only MCS is adopted for fatigue problems. Numerical predictions for the stress intensity factors (SIF) were validated with NASA/FLAGRO and reliability predictions were validated with both RELTRAN and VaP. With the advent of powerful and inexpensive personal computer, and the user‐friendliness of graphical user interface, programs such as the one developed will indeed make it possible for engineer to correctly account for the stochastic nature of most fracture problems they are confronted with.     

多参数影响机构的可靠度敏感性分析

提出了一种用于求解多参数影响机构的可靠度敏感性的新方
法.利用多体系统动力学理论和Kriging理论建立机构的模型,并在此基础上计算机构的可靠度敏感性.该
方法能够克服机构模型的复杂性所带来的计算困难,特别是在无法得出机构的状态功能函数时,Kriging
理论的应用可以很好地解决此类问题．同时,该方法利用小尺度的蒙特卡洛抽样仿真计算,可以通过小数
目的抽样来为建立Kriging模型提供给定的输入和输出．通过实例可以看出,在计算过程中该方法使用方
便,计算结果符合机构的实际情况,可为机构的后续设计提供理论依据．     

Reliability analysis of laminated composite structures using finite elements and neural networks

Saving of computer processing time on the reliability analysis of laminated composite structures using artificial neural networks is the main objective of this work. This subject is particularly important when the reliability index is a constraint in the optimization of structural performance, because the task of looking for an optimum structural design demands also a very high processing time. Reliability methods, such as Standard Monte Carlo (SMC), Monte Carlo with Importance Sampling (MC–IS), First Order Reliability Method (FORM) and FORM with Multiple Check Points (FORM–MCPs) are used to compare the solution and the processing time when the Finite Element Method (FEM) is employed and when the finite element analysis (FEA) is substituted by trained artificial neural networks (ANNs). Two ANN are used here: the Multilayer Perceptron Network (MPN) and the Radial Basis Network (RBN). Several examples are presented, including a shell with geometrically non-linear behavior, which shows the advantages using this methodology.     

Application of the response surface methods to solve inverse reliability problems with implicit response functions

The inverse first-order reliability method (FORM) is considered to be one of the most widely used methods in inverse reliability analysis. It has been recognized that there are shortcomings of the inverse FORM in solving inverse reliability problems with implicit response functions, primarily inefficiency and difficulties involved in evaluating derivatives of the implicit response functions with respect to random variables. In order to apply the inverse FORM to structural inverse reliability analysis, response surface methods can be used to overcome the shortcomings. In the present paper, two different response surface methods, namely the polynomial-based response surface method and the artificial neural network-based response surface method, are developed to solve the inverse reliability problems with implicit response functions, and the accuracy and efficiency of the two response surface methods are demonstrated through two numerical examples of steel structures. It is found that the polynomial-based response surface method is more efficient and accurate than the artificial neural network-based response surface method. Recommendations are made regarding the suitability of the two response surface methods to solve the inverse reliability problems with implicit response functions.     

Reliability analysis against progressive failure of TLP tethers in extreme tension

The tension leg platform (TLP) is a moored floating structure whose buoyancy is more than its weight. The mooring system of TLP consists of number of tensioned tethers connected to the columns at the top and anchored to the seabed at the bottom. These tethers are vulnerable to failure due to extreme (maximum and minimum) tensions. The reliability study of these tethers is an important subject of study. The reliability may further deteriorate after the failure or removal of any of these tethers. In the present study, reliability analysis of an intact TLP and TLP with one tether missing has been carried out. A Von-Mises failure criterion has been adopted to define the failure of tether against maximum tension. The minimum tension failure occurs when the tethers slack due to loss of tension. The limit state functions for maximum and minimum tension cases have been derived. The computationally efficient algorithm First order reliability method (FORM) has been adopted for reliability calculations. Results are presented in terms of reliability indices and probabilities of failure for each sea state. The probabilities of failure so obtained for different sea states have been used for the assessment of annual and life time probability of failures. Reliability of the TLP with one tether missing has been compared with that of the corresponding intact TLP. Effect of wind has also been studied on the progressive failure of TLP tethers and the results have been compared with that of an intact TLP.     

Reliability analysis and reliability-based design optimization of roadway horizontal curves using a first-order reliability method

This article presents reliability analysis and reliability-based optimization of roadway minimum radius design based on vehicle dynamics, mainly focusing on exit ramps and interchanges. The performance functions are formulated as failure modes of vehicle rollover and sideslip. To accurately describe the failure modes, analytical models for rollover and sideslip are derived considering nonlinear characteristics of vehicle behaviour using the commercial software TruckSim. The probability of an accident is evaluated using the first-order reliability method and numerical studies are conducted using a single-unit truck model. To propose a practical application for the study, the reliability analysis for the minimum radius recommended by American Association of State Highway and Transportation Officials is conducted. The results show that, even if there are deviations from assumed design conditions of the current design guideline, the proposed design method can guarantee given target margins of safety against rollover and sideslip. Based on the reliability analysis, reliability-based design optimization is carried out and the results indicate new recommendations for minimum radii satisfying given target reliability levels.     

基于神经网络响应面法的随机结构动力可靠度分析

在对神经网络响应面法的原理和算法进行研究的基础上，建立了基于神经网络响应面法的随机结构动力可靠度分析方法。首先，基于首次超越破坏准则，参照静力可靠度的功能函数模式，建立了随机结构的动力可靠度功能函数；然后引入响应面法，以三层BP神经网络作为拟合函数，推导了功能函数的拟合表达式；最后结合一次二阶矩方法求解可靠指标。算例分析表明了本文方法有较好的计算精度和计算效率，在复杂结构的动力可靠度分析中有较强的实用价值。     

基于神经网络的材料非稳态疲劳损伤可靠性研究

疲劳累积损伤是一个非稳态能耗过程，可以用遗传算法优化后的3层2—7-1BP神经网络来描述疲劳损伤的非线关系，经仿真验证表明，该神经网络具有较高的精度和泛化能力。通过对材料疲劳损伤临界值和栽荷的分散性的分析研究，建立了疲劳失效动态准则，并运用蒙特卡罗随机抽样法对材料疲劳寿命的可靠性进行了仿真验证；对调质45号钢在随机栽荷和2级栽荷作用下，进行了疲劳寿命可靠性仿真计算，仿真结果与实验结果和理论分析比较吻合。