基于功能度量法的概率优化设计的收敛控制

概率结构优化设计(PSDO)中概率约束的评定可以采用最近提出的、被认为更高效、稳定的功能度量法(PMA). 改进均值(AMV)迭代格式经常在PMA中使用,但它对一些非线性功能函数或非正态随机变量,搜索最小功能目标点时可能陷入周期振荡或混沌解,从而使PSDO的两层次算法或序列近似规划算法优化计算失败. 利用混沌反馈控制的稳定转换法对功能度量法的AMV迭代格式实施了收敛控制,使嵌入周期和混沌轨道的不稳定不动点稳定化,获得稳定收敛解,从而使概率约束的评定能正常进行;再由两层次算法或序列近似规划算法进行结构优化设计. 算例结果表明了稳定转换法实施收敛控制的有效性,以及序列近似规划算法相对高效的优点.      

概率约束评估的功能度量法的混沌控制

功能度量法是基于可靠度的结构优化设计中评估概率约束的一种方法,其改进均值(AMV)迭代格式具有简洁、高效的优点,但对一些非线性功能函数搜索最小功能目标点时可能陷入周期振荡或混沌解,本文利用混沌反馈控制的稳定转换法对功能度量法的AMV迭代格式实施收敛控制.首先展示一些功能函数应用功能度量法AMV格式迭代计算产生了周期解和混沌解现象,并对迭代算法进行了混沌动力学分析.然后利用稳定转换法对功能度量法迭代失败的参数区间进行混沌控制,使嵌入周期和混沌轨道的不稳定不动点稳定化,获得了稳定收敛解,实现了迭代解的周期振荡、分岔和混沌控制.     

非概率区间模型可靠性指标的梯度投影算法

考虑不确定参数为区间变量,研究求解非概率可靠性指标的有效搜索算法.基于函数梯度法的基本思想,构造搜索方向,建立迭代算法格式,将传统的用于概率可靠性分析的梯度投影法用于非概率可靠性指标的求解.当收敛点为非最可能失效点时,提出了空间降维算法,并给出了整个搜索算法的计算步骤.通过数值算例,验证了本文提出的搜索迭代算法的有效性和正确性.     

优化迭代步长的两种改进增量谐波平衡法

增量谐波平衡法(IHB法)是一个半解析半数值的方法, 其最大优点是适合于强非线性系统振动的高精度求解. 然而, IHB法与其他数值方法一样, 也存在如何选择初值的问题, 如初值选择不当, 会存在不收敛的情况. 针对这一问题, 本文提出了两种基于优化算法的IHB法: 一是结合回溯线搜索优化算法(BLS)的改进IHB法(GIHB1), 用来调节IHB法的迭代步长, 使得步长逐渐减小满足收敛条件; 二是引入狗腿算法的思想并结合BLS算法的改进IHB法(GIHB2), 在牛顿-拉弗森(Newton-Raphson)迭代中引入负梯度方向, 并在狗腿算法中引入2个参数来调节BSL搜索方式用于调节迭代的方式, 使迭代方向沿着较快的下降方向, 从而减少迭代的步数, 提升收敛的速度. 最后, 给出的两个算例表明两种改进IHB法在解决初值问题上的有效性.      

最优步长因子法在桁架结构尺寸优化方面的应用

针对桁架结构尺寸优化的特性,依据原约束优化问题的对偶函数关于KKT乘子的一阶偏导数确定乘子的寻优方向;依据对偶函数的极值必要条件和约束优化问题的KKT条件,推导乘子迭代的最优步长因子;依据广义Lagrange函数关于各杆横截面积一阶偏导数应为零的极值必要条件,推导出求解该非线性方程组的优化迭代求解式及其步长因子;通过2种不同约束条件的10杆桁架结构尺寸优化算例验证了本文方法可自动确定各迭代求解式中的步长因子;与已有文献采用序列二次规划法的算例相比,本文方法无需采用一维搜索法寻找步长因子,可大幅度减少计算时间。     

MA对偶-信赖域算法在非线性不等式约束优化问题中的应用研究

针对含有非线性不等式约束条件的优化问题,提出了MA对偶-信赖域算法。在每次迭代过程中,基于信赖域方法和问题的逼近属性,构造了原优化问题中目标函数和约束函数的移动渐进线函数,由此建立简单的子优化问题。运用对偶方法求解子问题得到原优化问题的下降方向,再用线搜索方法取得搜索步长,最后得到下一步的迭代点。应用数学推理证明了该算法的全局收敛性。以悬臂梁最小柔度问题为例,应用MA对偶-信赖域算法对优化问题进行了求解,数值算例的结果表明,MA对偶-信赖域算法在求解非线性约束优化问题时比MMA和GCMMA算法的迭代次数少,收敛速度快。     

结构可靠指标的通用计算方法

在求解结构可靠指标时，保证迭代计算的收敛性是非常重要的，而实际计算表明，在有些情况下，用现有的计算方法（如JC法）进行迭代计算可能是不收敛的，这样给可靠指标的求解带来了困难。本文提出一个通用的可靠指标计算方法，通过引入可以根据迭代收敛条件自动调节的步长，实现对迭代过程和收敛性的控制。另外，本文方法不需要使用结构功能函数的偏导数，对于功能函数不能明确表达的可靠度问题尤为适用，对于功能函数可以明确表达但求导复杂的问题，可省去求导过程。最后，通过四个算例论证了本文方法的可行性。     

非线性有限元方程组求解器的设计与实现

本文主要介绍HAJIF-Ⅲ系统的非线性有限元方程组求解器的设计与实现。求解器由牛顿法、修正牛顿法、BFGS法、DFP法、割线牛顿法、弧长法和当前刚度参数、线性搜索、加速收敛等方法和措施混合组成,可由用户灵活控制,选定解法;也可由系统依据所分析的问题的特征自适应选择解法和载荷步长,有较好的自适应特性和高效可靠的优点。HAJIF-Ⅲ系统的应用实践表明:该求解器使用方便,计算效率高,结果可靠。     

非概率可靠性指标空间搜索算法

考虑不确定参数为区间变量,研究求解非概率可靠性指标的空间搜索算法。针对功能函数呈非线性性态的特征,采用切平面与G=0平面交线对非线性功能函数进行线性化处理,利用等倾线与等效线性功能函数的交点确定迭代点。经优化搜索,当功能函数取0值时,确定了最可能失效点,进一步确定非概率可靠性指标。经数值算例验证了本文提出的优化搜索算法具有较高的搜索效率,与相关结果比较验证了算法的正确性。     

耦合GPU与PCG的EFG法并行计算及应用研究

针对迭代法求解无网格Galerkin法中线性方程组收敛速度慢的问题,提出了一种耦合GPU和预处理共轭梯度法的无网格Galerkin法并行算法,在对其总体刚度矩阵、总体惩罚刚度矩阵进行并行联合组装的同时即可得到对角预处理共轭矩阵,有效地节省了GPU的存储空间和计算时间;通过采用四面体积分背景网格,提高了所提算法对三维复杂几何形状问题的适应性。通过2个三维算例验证了所提算法的可行性,且预处理共轭梯度法与共轭梯度法相比,其迭代次数最大可减少1686倍,最大的迭代时间可节省1003倍;同时探讨了加速比与线程数和节点个数之间的关系,当线程数为64时其加速比可达到最大,且预处理共轭梯度法的加速比与共轭梯度法相比可增大4.5倍,预处理共轭梯度法的加速比最大达到了88.5倍。     

Inexact Newton method via Lanczos decomposed technique for solving box-constrained nonlinear systems

This paper proposes an inexact Newton method via the Lanczos decomposed technique for solving the box-constrained nonlinear systems. An iterative direction is obtained by solving an affine scaling quadratic model with the Lanczos decomposed technique. By using the interior backtracking line search technique, an acceptable trial step length is found along this direction. The global convergence and the fast local convergence rate of the proposed algorithm are established under some reasonable conditions. Furthermore, the results of the numerical experiments show the effectiveness of the pro- posed algorithm.     

Phase Shifting Full-Field Interferometric Methods for Determination of In-Plane Tensorial Stress

A new method that combines phase shifting photoelasticity and transmission Coherent Gradient Sensing (CGS) is developed to determine the tensorial stress field in thin plates of photoelastic materials. A six step phase shifting photoelasticity method determines principal stress directions and the difference of principal stresses. The transmission CGS method utilizes a standard four step phase shifting method to measure the x and y first derivatives of the sum of principal stresses. These stress derivatives are numerically integrated using a weighted preconditioned conjugate gradient (PCG) algorithm, which is also used for the phase unwrapping of the photoelastic and CGS phases. With full-field measurement of the sum and difference of principal stresses, the principal stresses may be separated, followed by the Cartesian and polar coordinate stresses using the principal stress directions. The method is demonstrated for a compressed polycarbonate plate with a side V-shaped notch. The experimental stress fields compare well with theoretical stress fields derived from Williams solution for a thin plate with an angular corner.     

A finite element solutionof three-dimensional mixed convection gas flows in horizontal chnnels using preconditioned iterative metrix methods

An algorithm is presented for the finite element solution of three-dimensional mixed convection gas flows in channels heated from below. The algorithm uses Newton's method and iterative matrix methods. Two iterative solution algorithms, conjugate gradient squared (CGS) and generalized minimal residual (GMERS), are used in conjunction with a preconditioning technique that is simple to implement. The preconditioner is a subset of the full Jacobian matrix centered around the main diagonal but retaining the most fundamental axial coupling of the residual equations. A domain-renumbering scheme that enhances the overall algorithm performance is proposed on the basis of and analysis of the preconditioner. Comparison with the frontal elimination method demonstrates that the iterative method will be faster when the front width exceeds approximately 500. Techniques for the direct assembly f the problem into a compressed sparse row storage format are demonstrated. Elimination of fixed boundary conditions is shown to decrease the size of the matrix problem by up to 30%. Finally, fluid flow solutions obtained with the numerical technique are presented. These solutions reveal complex three-dimensional mixed convection fluid flow phenomena at low Reynolds numbers, including the reversal of the direction of longitudinal rolls in the presence of a strong recirculation in the entrance region of the channel.     

Assessment of adaptive and heuristic time stepping for variably saturated flow

The performance of improved initial estimates and ‘heuristic’ and ‘adaptive’ techniques for time step control in the iterative solution of Richards equation is evaluated. The so‐called heuristic technique uses the convergence behaviour of the iterative scheme to estimate the next time step whereas the adaptive technique regulates the time step on the basis of an approximation of the local time truncation error. The sample problems used to assess these various schemes are characterized by nonuniform (in time) boundary conditions, sharp gradients in the infiltration fronts, and discontinuous derivatives in the soil hydraulic properties. It is found that higher order initial solution estimates improve the convergence of the iterative scheme for both the heuristic and adaptive techniques, with greater overall performance gains for the heuristic scheme, as could be expected. It is also found that the heuristic technique outperforms the adaptive method under strongly nonlinear conditions. Previously reported observations suggesting that adaptive techniques perform best when accuracy requirements on the numerical solution are very stringent are confirmed. Overall both heuristic and adaptive techniques have their limitations, and a more general or mixed time stepping strategy combining truncation error and convergence criteria is recommended for complex problems. Copyright © 2006 John Wiley & Sons, Ltd.     

Fuzzy relaxed-finite step size method to enhance the instability of the fuzzy first-order reliability method using conjugate discrete map

Fuzzy reliability analysis can be implemented using two discrete optimization maps in the processes of reliability and fuzzy analysis. Actually, the efficiency and robustness of the iterative reliability methods are two main factors in the fuzzy-based reliability analysis due to the huge computational burdens and unstable results. In the structural fuzzy reliability analysis, the first-order reliability method (FORM) using discrete nonlinear map can provide a C membership function. In this paper, a discrete nonlinear conjugate map is proposed using a relaxed-finite step size method for fuzzy structural reliability analysis, namely Fuzzy conjugate relaxed-finite step size method fuzzy CRS. A discrete conjugate map is stabilized using two adaptive factors to compute the relaxed factor and step size in FORM. The framework of the proposed fuzzy structural reliability method is established using two linked iterative discrete maps as an outer loop, which constructs the membership function of the response using alpha level set optimization based on genetic operator, and the inner loop, implemented for reliability analysis using proposed conjugate relaxed-finite step size method. The fuzzy CRS and fuzzy HL-RF methods are compared to evaluate the membership functions of five structural problems with highly nonlinear limit state functions. Results demonstrated that the fuzzy CRS method is computationally more efficient and is strongly more robust than the HL-RF for fuzzy-based reliability analysis of the nonlinear structural reliability problems.     

Comparison of variants of the bi-conjugate gradient method for compressible Navier-Stokes solver with second-moment closure

Variants of the bi-conjugate gradient (Bi-CG) method are used to resolve the problem of slow convergence in CFD when it is applied to complex flow field simulation using higher-order turbulence models. In this study the Navier-Stokes and Reynolds stress transport equations are discretized with an implicit, total variation diminishing (TVD), finite volume formulation. The preconditioning technique of incomplete lower-upper (ILU) factorization is incorporated into the conjugate gradient square (CGS), bi-conjugate gradient stable (Bi-CGSTAB) and transpose-free quasi-minimal residual (TFQMR) algorithms to accelerate convergence of the overall itertive methods. Computations have been carried out for separated flow fields over transonic bumps, supersonic bases and supersonic compression corners. By comparisons of the convergence rate with each other and with the conventional approximate factorization (AF) method it is shown that the Bi-CGSTAB method gives the most efficient convergence rate among these methods and can speed up the CPU time by a factor of 2·4–6·5 as compared with the AF method. Moreover, the AF method may yield somewhat different results from variants of the Bi-CG method owing to the factorization error which introduces a higher level of convergence criterion.     

Fully coupled finite volume solutions of the incompressible Navier–Stokes and energy equations using an inexact Newton method

An inexact Newton method is used to solve the steady, incompressible Navier–Stokes and energy equation. Finite volume differencing is employed on a staggered grid using the power law scheme of Patankar. Natural convection in an enclosed cavity is studied as the model problem. Two conjugate-gradient -like algorithms based upon the Lanczos biorthogonalization procedure are used to solve the linear systems arising on each Newton iteration. The first conjugate-gradient-like algorithm is the transpose-free quasi-minimal residual algorithm (TFQMR) and the second is the conjugate gradients squared algorithm (CGS). Incomplete lower-upper (ILU) factorization of the Jacobian matrix is used as a right preconditioner. The performance of the Newton- TFQMR algorithm is studied with regard to different choices for the TFQMR convergence criteria and the amount of fill-in allowed in the ILU factorization. Performance data are compared with results using the Newton-CGS algorithm and previous results using LINPACK banded Gaussian elimination (direct-Newton). The inexact Newton algorithms were found to be CPU competetive with the direct-Newton algorithm for the model problem considered. Among the inexact Newton algorithms, Newton-CGS outperformed Newton- TFQMR with regard to CPU time but was less robust because of the sometimes erratic CGS convergence behaviour.