基于自适应响应面法的输电塔线体系腐蚀疲劳可靠度研究

环境腐蚀和风振疲劳耦合作用下输电塔体的结构性能逐渐退化,满足预定设计功能的概率减小。然而,传统响应面法计算结构可靠度时均不能兼顾"效率"和"精度"。为此,首先通过严格的数学推导给出了交叉项是否存在的判断准则,将该判断准则与传统二次响应面法相结合建立了考虑部分交叉项的自适应响应面法。然后,通过Q345等边角钢腐蚀疲劳试验结果给出了构件腐蚀疲劳t-P-S-N曲线方程,再与概率论相结合建立了随机疲劳曲线方程。最后,通过工程算例采用建议自适应响应面法以风速、腐蚀时间和随机腐蚀疲劳S-N曲线方程为随机变量对输电塔线体系进行了腐蚀疲劳可靠度研究,结果表明:①交叉项判断准则能有效地保留相互影响随机变量之间的交叉项;②建议自适应响应面法在满足精度的同时能有效减少计算量;③构件随机腐蚀疲劳S-N曲线模型在结构可靠性分析中简单易行。     

基于单变量分析的自适应响应面法

由于简便易行,响应面法在结构可靠度分析中获得了众多关注,其中尤以不考虑交叉项的二次响应面应用最为广泛。然而,对于与强非线性相对应的复杂极限状态曲面,二次响应面的近似精度显然不够,从而引起可靠度估计的较大误差。虽然理论上高次响应面法可以解决这一问题,但待定系数的急剧增长导致计算效率降低甚至无法实现。为此,该文以多变量函数的单变量分析为基础,提出了一种合理确定高次响应面形式的算法,可以有效地减少响应面中待定系数的数量,降低了计算的困难,并且针对可能出现的问题提出了改进措施;此外,基于数论选点策略,发展了一类适用于响应面法的数论选点方案。最后,通过算例分析对建议算法进行验证,结果表明该算法具有较好的精度和效率。     

自由曲面轮廓度误差评定

在总结面轮廓度误差评定原则的基础上,提出了曲面轮廓度误差最小条件几何判定准则,即“三角形准则”和“交叉准则”。对曲面轮廓度误差最小条件评定算法进行了研究,首先特征点预定位,再用最小二乘原则粗匹配,最后通过最小条件原则精匹配,实现被测曲面与理论曲面之间的自适应调整。实例证明了几何判定准则的正确性和计算方法的可行性。     

基于自适应点估计和最大熵原理的结构体系多构件可靠度分析

准确而高效地求解结构体系中多个构件的可靠度水准对结构维护和优化具有重要意义,目前已有学者将蒙特卡洛法和响应面法用于此类可靠度分析。然而,蒙特卡洛法所需结构分析次数取决于失效概率的量级,通常计算成本较高。而响应面法的所需结构分析次数取决于杆件数量,当其数量较多时同样有较高的成本。鉴于此,该文提出了一种基于自适应点估计和最大熵原理的结构体系多构件可靠度分析方法,其所需的结构重分析次数上限与杆件数量无关,计算过程简便无需迭代。首先,通过引入自适应交叉项判定和双变量降维近似模型求解各杆件的前四阶矩;然后,根据各杆件的前四阶矩,采用最大熵原理求解各杆件的可靠度指标;最后,通过多个算例对比了蒙特卡洛法、响应面法和建议方法的精度和效率。结果表明建议方法所需的结构重分析次数远少于蒙特卡洛法和响应面法,实现过程简便,且精度能够满足工程要求。     

非线性隐式极限状态方程失效概率计算的组合响应面法

提出组合响应面的新方法,用以计算设计点附近非线性程度较大的隐式极限状态方程的失效概率。该方法用主响应面和多个次响应面近似对失效概率贡献较大的区域,其响应面函数形式为不含交叉的二次多项式。主响应面依据传统响应面法通过选择适当的插值点和迭代运算获得,其设计点为主设计点。延坐标轴正负方向偏移主设计点得到拟均值点。以拟均值点为基础得到一组次响应面和次设计点。通过主次响应面在各自设计点处的切平面建立组合响应面近似原隐式极限状态方程,并计算其失效概率。算例结果说明所提方法具有较高精度。     

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。     

非平稳地震作用下随机结构动力可靠度计算

对非平稳地震作用下的含随机参数结构,建议了一类结构体系动力可靠度的数值模拟求解方法.把结构动力方程写成状态方程形式,采用精细积分法对状态方程进行数值求解,将结构响应表达为一系列随机系数和离散时刻处随机激励乘积的和形式.随机系数为结构随机参数的函数,反映结构随机参数对随机响应的影响.在确定性结构非平稳随机响应时域分析方法的基础上,采用不含交叉项的二次多项式对该随机系数进行重构,获得了结构响应关于结构随机参数和离散时刻处随机激励的显式表达式.基于该显式表达式,利用数值模拟技术可以方便地进行首次超越失效准则下结构体系动力可靠度的求解.对一榀非平稳地震作用下的含随机参数框架进行了结构体系动力可靠度分析,并在计算精度和计算效率上与传统蒙特卡罗法进行了比较,结果显示所提出的方法具有理想的精度和相当高的效率.     

基于HLRF法与修正对称秩1方法的改进可靠度方法EI北大核心CSCD

一次可靠度方法简单、高效,但在处理强非线性功能函数时存在较大误差;已有的二次可靠度方法在提高精度的同时往往降低了效率。为此,该文中在发展改进一次可靠度方法的同时提出了更好地兼顾精度与效率的改进二次可靠度方法。将修正对称秩1方法与HLRF法的步长确定策略相结合,提出了具有较好收敛性的改进一次可靠度方法,且在基本不增加计算量的前提下获得了功能函数的近似Hessian矩阵;结合坐标旋转、单变量降维近似和非中心卡方分布,提出了与改进一次可靠度方法同效率但具有更高精度的改进二次可靠度方法;通过数值算例和工程算例验证了建议方法的广泛适用性以及精度或效率上的优势。     

利用矩点估计法简化响应面可靠度指标的计算

针对响应面可靠度指标计算方法的缺陷,将罗森布鲁斯统计矩点估计法引入到经典响应面方法中对其进行改进。改进后响应面方法,考虑基本随机变量偏态情况,改变了模拟试验中随机变量抽样值的计算方法;直接采用了统计矩计算可靠度指标,使可靠度指标的计算在真实极限状态曲面的某些特殊点上进行;在计算过程中不需拟合近似极限状态曲面和对非线性方程进行线性化处理,不产生迭代误差和累积误差,计算过程简洁明了。最后分别利用改进的响应面方法和经典响应面方法分析了某一矿山大型工程的稳定可靠性,并以蒙特卡洛法计算结果作为准精确解进行了比较,计算结果满足工程要求。     

基于随机响应面法的结构可靠度分析

提出了考虑变量间相关性的随机响应面法,采用正交变换解决随机响应面法输入随机变量间相关性问题。推导了4阶和5阶Hermite随机多项式展开的解析表达式。编写了基于C#语言的随机响应面法计算程序。最后采用算例证明了随机响应面法在结构可靠度分析中的有效性。结果表明,提出的随机响应面法能够有效地分析输入随机变量间相关性的可靠度问题。3阶随机响应面法的计算精度在大多数情况下可以满足结构可靠度分析的需要,而且计算效率较高。但是随着变量间相关性的增加,4阶或5阶随机响应面法才能保证足够的计算精度。概率配点数目为随机多项式待定系数数目的两倍并不总能保证足够的计算精度,一般来说,配点数目要大于两倍待定系数的个数才能保证随机响应面法足够的计算精度。     

Adaptive response surface method based on a double weighted regression technique

In structural reliability analysis where the structural response is computed from the finite element method, the response surface method is frequently used. Typically, the response surface is built from polynomials whereof unknown coefficients are estimated from an implicit limit state function numerically defined at fitting points. The locations of these points must be selected in a judicious way to reduce the computational time without deteriorating the quality of the polynomial approximation. To contribute to the development of this method, we propose some improvements. The response surface is successively formed in a cumulative manner. An adaptive construction of the numerical design is proposed. The response surface is fitted by the weighted regression technique, which allows the fitting points to be weighted according to (i) their distance from the true failure surface and (ii) their distance from the estimated design point. This method aims to minimize computational time while producing satisfactory results. The efficiency and the accuracy of the proposed method can be evaluated from examples taken from the literature.     

An efficient response surface method using moving least squares approximation for structural reliability analysis

The response surface method (RSM) is widely adopted for structural reliability analysis because of its numerical efficiency. However, the RSM is time consuming for large-scale applications and sometimes shows large errors in the calculation of the sensitivity of the reliability index with respect to random variables. In order to overcome these problems, this study proposes an efficient RSM applying a moving least squares (MLS) approximation instead of the traditional least squares approximation generally used in the RSM. The MLS approximation gives higher weight to the experimental points closer to the most probable failure point (MPFP), which allows the response surface function (RSF) to be closer to the limit state function at the MPFP. In the proposed method, a linear RSF is constructed at first and a quadratic RSF is formed using the axial experimental points selected from the reduced region where the MPFP is likely to exist. The RSF is updated successively by adding one new experimental point to the previous set of experimental points. Numerical examples are presented to demonstrate the improved accuracy and computational efficiency of the proposed method compared to the conventional RSM.     

Generalized pointwise bias error bounds for response surface approximations

This paper proposes a generalized pointwise bias error bounds estimation method for polynomial‐based response surface approximations when bias errors are substantial. A relaxation parameter is introduced to account for inconsistencies between the data and the assumed true model. The method is demonstrated with a polynomial example where the model is a quadratic polynomial while the true function is assumed to be cubic polynomial. The effect of relaxation parameter is studied. It is demonstrated that when bias errors dominate, the bias error bounds characterize the actual error field better than the standard error. The bias error bound estimates also help to identify regions in the design space where the accuracy of the response surface approximations is inadequate. It is demonstrated that this information can be utilized for adaptive sampling in order to improve accuracy in such regions. Copyright © 2005 John Wiley & Sons, Ltd.     

Reliability analysis of non-linear reinforced concrete frames using the response surface method

In this paper, a formulation to compute the reliability of reinforced concrete structures, in which physical and geometrical non-linearities are taken into account, is described. The adopted non-linear model allows the representation of the mechanical behaviour of concrete structures at the failure stage, which is governed by possible large displacement effects, softening behaviour of concrete and tension stiffening effects. On the other hand, the reliability model is based on adaptive failure surfaces representing the mechanical model responses. The failure surface is obtained by fitting the internal force ultimate state of the structure using a quadratic polynomial. The structural reliability index is estimated by the Rackwitz and Fiessler algorithm, which has shown to converge after a reduced amount of iterations. A parametric numerical analysis of columns and frames is presented for practical applications, where the partial safety factors proposed by international codes of practice are associated with reliability indexes.     

Reliability analysis of automotive body-door subsystem

This paper proposes an efficient method for the reliability analysis of a vehicle body-door subsystem with respect to one of the important quality issues—the door closing energy. The developed method combines optimization-based and simulation-based approaches and is particularly applicable for problems with highly non-linear and implicit limit state functions. The proposed approach consists of two major parts. In the first part, an optimization-based method is used to search for the most probable point (MPP) on the limit state. This is achieved by using an adaptive response surface constructed through an optimal symmetric Latin hypercube design of experiments. In the second part, a multi-modal adaptive importance sampling method is proposed using the MPP information from the first part as the starting point. It is demonstrated through numerical examples that the proposed method is superior to existing methods in terms of efficiency and accuracy. The proposed method is illustrated for application to the reliability estimation with respect to the door closing energy problem. A generalized framework for reliability estimation is then established for problems with large numbers of random variables and complicated limit states.     

基于响应面法的结构动力学模型修正

为了获得精确的结构动力学模型,提出了响应面和优化相结合的方法。利用参数化模型和优化拉丁方试验设计获取样本点构造多项式响应面模型,最小二乘法确定多项式系数并检验响应面的拟合精度。用响应面计算结果与实验结果的误差构造目标函数,自适应模拟退火算法来优化修正响应面参数,将修正后的参数值带入有限元模型得到修正模型。以欧洲航空科技组织的基准模型GARTEUR飞机模型为算例,对比修正前后模态频率,结果表明修正后的模型在测试频段和预测频段具有良好的复现和预测能力,进而验证了基于响应面法与优化方法相结合的结构动力学有限元模型修正的有效性。     

Hybrid perturbation-Galerkin methods for structural reliability analysis

A major challenge in the reliability analysis of complex structures is to determine the response function or surface from which the limit state function can be established and hence the failure probability of the structure can be predicted. The intention of this paper is to propose a new class of hybrid perturbation-Galerkin methods to determine the response function (surface) of the structure. The proposed methods, mainly including single-variable and double-variable approximations, are based on a combination of the perturbation technique and Bubnov–Galerkin projection, where various orders of summation terms of power polynomial expansions are used as the Galerkin trial functions or basis vectors. A series of examples is provided to demonstrate the accuracy and efficiency of the proposed method by comparison with various existing methods. It is found from the numerical examples that with a significantly lower computational effort with respect to the existing reliability methods, very accurate results can be obtained by the proposed methods.     

A new adaptive response surface method for reliability analysis

Response surface method is a convenient tool to assess reliability for a wide range of structural mechanical problems. More specifically, adaptive schemes which consist in iteratively refine the experimental design close to the limit state have received much attention. However, it is generally difficult to take into account a lot of variables and to well handle approximation error. The method, proposed in this paper, addresses these points using sparse response surface and a relevant criterion for results accuracy. For this purpose, a response surface is built from an initial Latin Hypercube Sampling (LHS) where the most significant terms are chosen from statistical criteria and cross-validation method. At each step, LHS is refined in a region of interest defined with respect to an importance level on probability density in the design point. Two convergence criteria are used in the procedure: The first one concerns localization of the region and the second one the response surface quality. Finally, a bootstrap method is used to determine the influence of the response error on the estimated probability of failure. This method is applied to several examples and results are discussed.