机械可靠性分析的高精度响应面法

通过对已有可靠性分析中的响应面法的研究,提出了一种高精度的响应面法,该方法通过迭代线性插值的策略,来保证确定响应面的抽样点比经典的响应面法更接近真实的极限状态方程,并且该方法通过序列线性插值的方法来控制抽样点与插值中心点的距离,保证随着插值中心点收敛于真实设计点,抽样点提供更多的关于设计点附近真实极限状态方程的信息,进而保证了收敛的响应面能够在设计点附近更好地拟合真实的极限状态方程,并得到高精度的失效概率计算结果．算例充分说明了所提方法的合理性与适用性．     

无网格Chebyshev配点法求解二维位势问题

基于Chebyshev正交多项式插值理论和无网格配点技术,提出一种新型的无网格数值离散方法,称之为Chebyshev配点法.所提方法采用Chebyshev多项式的零点(Gauss-Lobatto节点)为插值节点,可最大限度地降低龙格现象,并且提供插值多项式的最佳一致逼近.数值算例表明,本文算法稳定,效率高,并可达到很高的计算精度.     

C~k连续的保形分段2k次多项式插值

1．引言在每个子区间上，通过插入至多一个内结点，Brodlie和Butt［1］给出了分段三次多项式保形插值算法，Randal［2］等讨论了分段五次多项式插值，作者［31讨论了一般分段奇次多项式的保形插值，并且给1了内结点的位置范围公式．这种插值方法完全解决了一般的分段奇次多项式的保形插值问题．关于分段偶次多项式的保形插值，大多数文献只讨论分段二次保形插值，这里要特别指出的是Shumake［4j导出了二次样条保凸的充要条件，并且给出了一个二次样条保形插值的方法．在每一个子区间上至多插入一个内结点，则一个二次插值样条就可得到．作…     

几种基于散乱数据拟合的局部插值方法

本文首先针对散乱数据拟合的Shepard方法,结合截断多项式、B样条基函数和指数函数来构造其权函数,使新的权函数具有更高的光滑度和更好的衰减性,并且其光滑性和衰减性可以根据实际需要自由调节,从而提高了曲面的拟合质量．同时还给出一种类似的局部插值方法．另外,本文还基于多重二次插值,结合多元样条的思想,给出了两个局部插值算法．该算法较好地继承了多重二次插值曲面的性质,从而保证了拟合曲面具有好地光顺性和拟合精度．曲面整体也具有较高的光滑性．     

对流扩散方程的三层WENO-MMOCAA差分方法

本文把三层修正特征线法,MMOCAA 差分方法及WENO 插值相结合,提出了求解对流扩散方程的三层WENO-MMOCAA 差分格式.此格式关于时间具有二阶精度,关于空间具有二阶以上精度且可避免基于二次以上Lagrange 插值的三层MMOCAA 差分方法在解的大梯度附近所产生的振荡.本文使用新的分析方法,给出了格式的误差估计.本文的数值算例表明新格式可消除振荡.     

一种Logistic模型参数估计的新方法及应用

介绍了logistic曲线参数估计的一种新方法,它是利用三次样条插值函数求导代替logistic曲线在这一点的导数值,进而利用最小二乘法得出参数的估计值,通过实例分析表明本文提出的方法比一般的三点法估计的参数值k再用线性化方法估计的参数值b,c,拟合精度更高.     

广义三次Hermite样条插值及其对振荡函数的积分等的数值逼近

本文在等距分划上引入在似于文［１］的Ｉ型广义Ｈｅｒｍｌｉｅ样条插值，改进了Ⅱ型广义Ｈｅｒｍｉｔｅ样条．与文［１］比较，我们证明了改进后的Ⅱ型广义Ｈｅｒｍｉｔｅ样条插值的逼近精度得到了充分的提高．并利用这二种样条插值，讨论了对振荡积分，有限Ｆｏｕｒｉｅｒ积分等的数值逼近．     

连续区间上积分值的二次样条拟插值

在实际问题中,某些插值点处的函数值往往是未知的,而仅仅已知一些连续等距区间上的积分值.如何利用连续区间上积分值信息来解决函数重构是一个有意义的问题.首先,文章利用连续等距区间上的积分值信息直接构造了一类二次样条拟插值,它称之为积分值型二次样条拟插值.然后,给出了积分值型二次样条拟插值的多项式再生性和逼近节点处函数值的超收敛性.最后,给出了一类改进的积分值型二次样条拟插值及其性质.实验结果表明,与已有的积分值型三次样条拟插值相比,文章提出的拟插值更简单和有效,并且可以推广到积分值型高次样条拟插值.     

非齐次弹性力学问题双互易边界元方法研究北大核心CSCD

基于弹性力学边界元方法理论,将边界元法与双互易法结合,采用指数型基函数对非齐次项进行插值得到双互易边界积分方程.将边界积分方程离散为代数方程组,利用已知边界条件和方程特解求解方程组,得出域内位移和边界面力.指数型基函数的形状参数是由插值点最近距离的最小值决定,采用这种形状参数变化方案,分析径向基函数(RBF)插值精度以及插值稳定性.再次将指数型基函数应用到双互易边界元法中,分析双互易边界元方法下计算精度及稳定性,验证了指数型插值函数作为双互易边界元方法的径向基函数解决弹性力学域内体力项问题的有效性.     

求解二维Poisson方程的重心有理插值配点法

首先介绍了重心Lagrange插值法,然后通过改变重心Lagrange插值法的插值权函数,重点给出了重心有理插值的具体形式.基于等距节点和Chebyshev节点这两类插值节点,利用重心有理插值配点法求解了二维Poisson方程,并比较了采用上述两种插值节点时的计算精度.数值算例表明,重心有理插值配点法具有稳定性好,计算精度高和程序编写简单的特点.     

A hybrid self-adjusted mean value method for reliability-based design optimization using sufficient descent condition

Due to the efficiency and simplicity, advanced mean value (AMV) method is widely used to evaluate the probabilistic constraints in reliability-based design optimization (RBDO) problems. However, it may produce unstable results as periodic and chaos solutions for highly nonlinear performance functions. In this paper, the AMV is modified based on a self-adaptive step size, named as the self-adjusted mean value (SMV) method, where the step size for reliability analysis is adjusted based on a power function dynamically. Then, a hybrid self-adjusted mean value (HSMV) method is developed to enhance the robustness and efficiency of iterative scheme in the reliability loop, where the AMV is combined with the SMV on the basis of sufficient descent condition. Finally, the proposed methods (i.e. SMV and HSMV) are compared with other existing performance measure approaches through several nonlinear mathematical/structural examples. Results show that the SMV and HSMV are more efficient with enhanced robustness for both convex and concave performance functions.     

Optimization Design of Holding Poles Based on the Response Surface Methodology and the Improved Arithmetic Optimization Algorithm北大核心CSCD

抱杆优化设计需要耗费大量有限元分析计算时间,难以确定可行域.该文采用响应面法(response surface method,RSM)来模拟抱杆结构的真实响应,提出了改进的算术优化算法(improved arithmetic optimization algorithm,IAOA)对抱杆结构进行优化设计.将分数阶积分引入算术优化算法(arithmetic optimization algorithm,AOA),改善了算法的开发能力.采用拉丁超立方抽样,选取抱杆结构杆件截面试验样本,利用最小二乘法对样本点进行分析,构建了抱杆结构应力和位移关于杆件截面尺寸的二阶响应面代理模型.建立以抱杆质量最小化为优化目标,许用应力和位移为约束条件的优化模型,采用IAOA对其进行求解.结果表明:二阶响应面模型能够准确预测抱杆结构的响应值,IAOA的求解精度得到显著提升,代理模型可大幅降低有限元分析所需的计算代价,优化后抱杆结构质量减轻了8.2%.联合使用RSM和IAOA可有效求解大型空间杆系结构的优化设计问题.     

Robust cutting parameters optimization for production time via computer experiment

This study intends to determine the optimal cutting parameters required to minimize the cutting time while maintaining an acceptable quality level. Usually, the equation for predicting cutting time is unknown during the early stages of cutting operations. This equation can be determined by studying the output cutting times vs. input cutting parameters through CATIA software, with assistance from the statistical method, response surface methodology (RSM). Then, the equation is formulated as an objective function in the form of mathematical programming (MP) to determine the optimal cutting parameters so that the cutting time is minimized. The formulation in MP also includes the constraints of feasible ranges for process capability consideration and surface roughness for quality concerns. The important ranking obtained from the statistical method in cooperation with the optimal solutions found from MP can also be used as references for the possibility of robust design improvements.     

Formation of wavy nanostructures on the surface of flat substrates by ion bombardment

A popular mathematical model for the formation of an inhomogeneous topography on the surface of a plate (flat substrate) during ion bombardment was considered. The model is described by the Bradley-Harper equation, which is frequently referred to as the generalized Kuramoto-Sivashinsky equation. It was shown that inhomogeneous topography (nanostructures in the modern terminology) can arise when the stability of the plane incident wavefront changes. The problem was solved using the theory of dynamical systems with an infinite-dimensional phase space, in conjunction with the integral manifold method and Poincaré-Dulac normal forms. A normal form was constructed using a modified Krylov-Bogolyubov algorithm that applies to nonlinear evolutionary boundary value problems. As a result, asymptotic formulas for solutions of the given nonlinear boundary value problem were derived.     

An efficient algorithm for solving generalized pantograph equations with linear functional argument

A numerical method for solving the generalized (retarded or advanced) pantograph equation under initial value conditions is presented. To display the validity and applicability of the numerical method four illustrative examples are presented. The results reveal that this method is very effective and highly promising when compared with other numerical methods, such as Adomian decomposition method, spline methods and Taylor method.     

灰色GM(1,1,k,k2)模型背景值及时间响应函数优化

本文提出了一种新的带有时间幂次项的灰色GM(1,1,k,k²)模型,给出了其灰微分方程和白化微分方程基本形式。基于最小二乘法获得了该模型参数估计值,并推导了该模型时间响应函数。鉴于GM(1,1,k,k²)模型灰微分方程与白化微分方程之间存在跳跃关系,首先对灰微分方程的背景值进行了优化,并推导了优化后的背景值计算公式。为了克服初始值的影响,根据误差平方和最小,进一步优化了GM(1,1,k,k²)模型时间响应函数。最后,该优化后的GM(1,1,k,k²)模型被应用于软土地基沉降预测,获得了较好的模拟预测效果,说明模型是可行的。     

Adaptive reliability analysis based on a support vector machine and its application to rock engineering

The response surface method (RSM), a simple and effective approximation technique, is widely used for reliability analysis in civil engineering. However, the traditional RSM needs a considerable number of samples and is computationally intensive and time-consuming for practical engineering problems with many variables. To overcome these problems, this study proposes a new approach that samples experimental points based on the difference between the last two trial design points. This new method constructs the response surface using a support vector machine (SVM); the SVM can build complex, nonlinear relations between random variables and approximate the performance function using fewer experimental points. This approach can reduce the number of experimental points and improve the efficiency and accuracy of reliability analysis. The advantages of the proposed method were verified using four examples involving random variables with different distributions and correlation structures. The results show that this approach can obtain the design point and reliability index with fewer experimental points and better accuracy. The proposed method was also employed to assess the reliability of a numerically modeled tunnel. The results indicate that this new method is applicable to practical, complex engineering problems such as rock engineering problems.     

结构可靠性分析的支持向量机方法

针对结构可靠性分析中功能函数不能显式表达的问题,将支持向量机方法引入到结构可靠性分析中．支持向量机是一种实现了结构风险最小化原则的分类技术,它具有出色的小样本学习性能和良好的泛化性能,因此提出了两种基于支持向量机的结构可靠性分析方法．与传统的响应面法和神经网络法相比,支持向量机可靠性分析方法的显著特点是在小样本下高精度地逼近函数,并且可以避免维数灾难．算例结果也充分表明支持向量机方法可以在抽样范围内很好地逼近真实的功能函数,减少隐式功能函数分析（通常是有限元分析）的次数,具有一定的工程实用价值．