应力和位移约束下连续体结构拓扑优化

同时考滤应力和位移约束的连续体结构拓扑优化问题,很难用现有的均匀方法或变密度方法等求解。主要困难在于难以建立应力和位移约束与拓扑设计变量间显式关系式;即使建立了这种关系,也由于优化问题规模过大,利用常规的数学规划方法难以求解。隋允康、杨德庆曾提出了基于独立连续拓扑变量及映射变换（ＩＣＭ）的桁架结构拓扑优化模型。本文在此基础上,建立了以重量为目标,考虑应力和位移约束的连续体结构拓扑优化模型,并推导出     

基于营养动力学的广义捕食者—食饵—生物残体系统的变结构控制

利用变结构控制理论研究了一个基于营养动力学的广义捕食者一食饵一生物残体系统的变结构控制问题.首先,给出了基于营养动力学的广义捕食者一食饵一生物残体系统的正则平衡点的稳定性条件;同时利用广义系统理论研究了基于营养动力学的广义捕食者一食饵一生物残体系统的正则化问题,得到了其可正则化条件;最后,对其实施控制,并利用变结构控制理论,实现了基于营养动力学的广义捕食者一食饵一生物残体系统的稳定化,保持了系统的持续生存.     

方向导数和广义锥-预不变凸集值优化问题

讨论拓扑向量空间中无约束集值优化问题的最优性条件问题.利用集值映射的Dini方向导数,在广义锥-预不变凸性条件下,建立了集值优化问题关于弱极小元和强极小元的最优性充分必要条件.     

向量映射的鞍点和Lagrange对偶问题

本文研究拓扑向量空间广义锥-次类凸映射向量优化问题的鞍点最优性条件和Lagrange对偶问题,建立向量优化问题的Fritz John鞍点和Kuhn-Tucker鞍点的最优性条件及其与向量优化问题的有效解和弱有效解之间的联系。通过对偶问题和向量优化问题的标量化刻画各解之间的关系,给出目标映射是广义锥-次类凸的向量优化问题在其约束映射满足广义Slater约束规格的条件下的对偶定理。     

基于离散变量的拓扑优化方法

单元敏度的不准确估计是离散拓扑优化算法数值不稳定的原因之一,特别是添加材料时,传统的敏度计算公式给出的估计误差较大,甚至有时估计符号都是错误的．为了克服这一问题,通过对弹性平衡增量方程的摄动分析构造了新的增量敏度估计公式．这一新的公式无论是添加材料还是删除材料都能较准确地估计出目标函数增量,它可以看作是通过非局部单元刚度阵对传统敏度分析公式的修正．以此为基础构建了一种基于离散变量的拓扑优化算法,它可以从任意单元上添加或删除材料以使目标函数减小,同时为避免优化过程中重新划分网格,采用了单元软杀策略以小刚度材料模拟空单元．这一方法的主要优点是简单,不需要太多的数学计算,特别有利于工程实际的应用．     

覆盖族生成拓扑的约简

本文研究了在覆盖族产生的拓扑不变的条件下覆盖族的约简问题.利用拓扑学理论讨论覆盖广义粗糙集的约简理论,给出计算约简的方法,丰富了覆盖广义粗糙集理论.     

基于参数化水平集法的材料非线性子结构拓扑优化

针对利用传统水平集法进行非线性结构拓扑优化计算过程复杂及计算效率低等问题,将参数化水平集方法引入材料非线性结构拓扑优化中。通过全局径向基函数插值初始水平集函数,建立了以插值系数为设计变量、结构的应变能最小为目标函数、材料用量为约束条件的材料非线性结构拓扑优化模型,利用有限元分析对材料非线性结构建立平衡方程,并用迭代法求解。同时,采用子结构法划分设计区域为若干个子区域,将全自由度平衡方程的求解分解为缩减的平衡方程和多个子结构内部位移的求解,减小了计算成本。算例表明,这种处理非线性关系的方法可以在保证数值稳定的同时提高计算效率,得到边界清晰、结构合理的拓扑优化构形。     

结构拓扑优化中棋盘格抑制方法的研究

针对棋盘格过滤技术中单元权重系数的计算,对已有文献中的棋盘格抑制方法进行改进,提出了物理意义明确且更具一般性的公式.建立含应力约束的弹塑性拓扑优化模型,将改进的棋盘格抑制方法用于弹塑性结构拓扑优化,采用ESO(evolutionary structural optimization)法进行优化.编程实现了两个数值算例,对算例结果分析表明:改进的棋盘格抑制方法具有更好的抑制效果,且该方法并不局限于材料线性范围的拓扑优化,也适用于进行材料非线性的拓扑优化时棋盘格的抑制.     

具有动应力和动位移约束的离散变量结构拓扑优化设计方法

讨论了动应力、动位移约束下离散变量结构拓扑优化设计问题.首先给出问题的数学模型,然后用拟静力算法,将结构惯性力极值作为静载荷施加到结构上,求得结构的动位移和动内力,将考虑动应力约束和动位移约束的离散变量结构拓扑设计问题化为静应力和静位移约束的优化问题,然后利用两类变量统一考虑的离散变量结构拓扑优化设计的综合算法进行求解.     

带有随机决策单元的广义数据包络分析方法

广义DEA方法是一种相对效率评价方法,解决了决策单元相对于任意参考系(样本单元集)的效率比较问题.在实际中,有时评价标准是确定的,决策单元的生产具有不确定性,有必要在进行生产之前基于确定性样本单元对随机性决策单元进行相对效率评价.为了解决这个问题,研究样本单元为确定值,决策单元为随机变量的广义DEA模型,分别通过期望值和机会约束将随机模型转化为确定性规划,给出决策单元GEDEA有效和GCDEA有效的概念,GEDEA有效与多目标规划Pareto有效关系,以及利用移动因子对决策单元进行有效性排序方法.     

General shape optimization capability

Structural optimization is almost as old as the finite element method (FEM). Whereas FEM found its way to real-life applications very quickly, structural optimization remained a topic of interest in the research community for many years. However, there have been a number of attemps recently to develop general purpose program systems for property optimization. For shape optimization, there is no general purpose code currently available that can solve realistic problems. This paper will describe a method of calculating shape sensitivities within , in a simple manner, without resort to external programs. Once the shape sensitivities are obtained, the shape optimization process can proceed in a manner similar to property optimization. The key concept is the use of natural design variables to define the shape changes in a given structure. The design variables are the magnitudes of enforced displacements applied to the structure. The displacements produced by these variables are added to the initial shape to obtain a new shape. This approach can be computationally intensive and since one shape variable is dependent of another, multiple CPU's can be used to significantly reduce the solution time.

Two examples are solved to demonstrate the capability of these techniques. The first is a cantilever beam with holes loaded by a point load at the free end. The shape of the holes as well as the thickness of the beam are selected as the design variables. The second example is the shape optimization of a connecting rod subjected to several different loading and boundary conditions.     

Large scale structural synthesis

A general purpose optimization program is coupled to a large scale finite element program to provide an efficient tool for structural synthesis. The resulting interface program may be used to design structures for minimum weight, subject to constraints on stress, displacement, and vibration frequencies. A variety of state-of-the-art techniques are employed, including design variable linking, constraint deletion, reciprocal variables, and formal approximations. The capability is demonstrated with the design of a gear housing using 30 design variables and over 5000 nonlinear inequality constraints. The finite element model consists of over 1600 elements and 7000 displacement degrees of freedom. The design required six detailed finite element analyses and approximately one hour on a Cray-1s supercomputer. It is concluded that structures of practical size and complexity can be efficiently designed using numerical optimization.     

The virtual element method in 50 lines of MATLAB

We present a 50-line MATLAB implementation of the lowest order virtual element method for the two-dimensional Poisson problem on general polygonal meshes. The matrix formulation of the method is discussed, along with the structure of the overall algorithm for computing with a virtual element method. The purpose of this software is primarily educational, to demonstrate how the key components of the method can be translated into code.     

Parallel structural optimization applied to bone remodeling on distributed memory machines

In this paper, we investigate parallel structural optimization methods on distributed memory MIMD machines. We have restricted ourselves to the case of minimizing a multivariate non-linear function subject to bounds on the independent variables, when the objective function is expensive to evaluate as compared to the linear algebra portion of the optimization. This is the case in structural applications, when a large three-dimensional finite element mesh is used to model the structure.This paper demonstrates how parallelism can be exploited during the function and gradient computation as well as the optimization iterations. For the finite element analysis, a torus wrap skyline solver is used. The reflective Newton method, which attempts to reduce the number of iterations at the expense of more linear algebra per iteration, is compared with the more conventional active set method. All code is developed for an Intel iPSC/860, but can be ported to other distributed memory machines.The methods developed are applied to problems in bone remodeling. In the area of biomechanics, optimization models can be used to predict changes in the distribution of material properties in bone due to the presence of an artificial implant. The model we have used minimizes a linear combination of the mass and strain energy in the entire domain subject to bounds on the densities in each finite element.Early results show that the reflective Newton method can outperform active set methods when few variables are active at the minimum.     

Numerical Procedures in Multiobjective Optimization with Variable Ordering Structures

Multiobjective optimization problems with a variable ordering structure, instead of a partial ordering, have recently gained interest due to several applications. In the previous years, a basic theory has been developed for such problems. The binary relations of a variable ordering structure are defined by a cone-valued map that associates, with each element of the linear space ? ^m , a pointed convex cone of dominated or preferred directions. The difficulty in the study of the variable ordering structures arises from the fact that the binary relations are in general not transitive. In this paper, we propose numerical approaches for solving such optimization problems. For continuous problems a method is presented using scalarization functionals, which allows the determination of an approximation of the infinite optimal solution set. For discrete problems the Jahn–Graef–Younes method, known from multiobjective optimization with a partial ordering, is adapted to allow the determination of all optimal elements with a reduced effort compared to a pairwise comparison.     

多重约束下空间桁架结构抗风优化

目前复杂结构的抗风优化研究大多集中于高层建筑,很少针对风敏感的大跨屋盖结构．考虑强度、刚度和几何尺寸等多重约束,基于虚功原理和Lagrange乘子将抗风优化转化为无约束问题,编制数值程序整合有限元计算和优化分析两部分,然后对杆件数为10080的实际双层柱面网壳进行优化设计,讨论了设计变量可行域、初始值和调整步选择等对优化结果的影响．研究表明,采用本文方法可实现对空间桁架结构进行多重约束下的高效抗风优化设计,网壳总重降低约37%,风致响应分布不均使得有必要设定可行域下限,而设计变量初值和调整步选择不影响最后的优化结果．     

Utility Function Programs and Optimization over the Efficient Set in Multiple-Objective Decision Making

Natural basic concepts in multiple-objective optimization lead to difficult multiextremal global optimization problems. Examples include detection of efficient points when nonconvexities occur, and optimization of a linear function over the efficient set in the convex (even linear) case. Assuming that a utility function exists allows one to replace in general the multiple-objective program by a single, nonconvex optimization problem, which amounts to a minimization over the efficient set when the utility function is increasing. A new algorithm is discussed for this utility function program which, under natural mild conditions, converges to an -approximate global solution in a finite number of iterations. Applications include linear, convex, indefinite quadratic, Lipschitz, and d.c. objectives and constraints.     

论理想流体与线弹性结构的耦联振动

本文对理想流体与线弹性结构的耦联振动问题作理论分析和数值分析.文中证明了耦联振动的固有频率存在并且均为正实数.将流-固耦合系统分析转化为单一结构物在真空中的自由振动分析后,频率方程中不再含有流体变元.使问题得以大大简化.给出了数值解的收敛性证明,以保证解的可靠性.文中还综合里兹法、边界元和有限元方法,提出一种分析转化后结构的混合算法.利用该算法,只需对现有结构分析程序稍作改进,就可分析那些理想流场与结构的耦合问题.一些数例说明了算法的有效性.     

Application of lower bound direct method to engineering structures

Direct methods provide elegant and efficient approaches for the prediction of the long-term behaviour of engineering structures under arbitrary complex loading independent of the number of loading cycles. The lower bound direct method leads to a constrained non-linear convex problem in conjunction with finite element methods, which necessitates a very large number of optimization variables and a large amount of computer memory. To solve this large-scale optimization problem, we first reformulate it in a simpler equivalent convex program with easily exploitable sparsity structure. The interior point with DC regularization algorithm (IPDCA) using quasi definite matrix techniques is then used for its solution. The numerical results obtained by this algorithm will be compared with those obtained by general standard code Lancelot. They show the robustness, the efficiency of IPDCA and in particular its great superiority with respect to Lancelot.