A material based model for topology optimization of thermoelastic structures

This paper presents the development of a computational model for the topology optimization problem, using a material distribution approach, of a 2-D linear-elastic solid subjected to thermal loads, with a compliance objective function and an isoperimetric constraint on volume. Defining formally the augmented Lagrangian associated with the optimization problem, the optimality conditions are derived analytically. The results of analysis are implemented in a computer code to produce numerical solutions for the optimal topology, considering the temperature distribution independent of design. The design optimization problem is solved via a sequence of linearized subproblems. The computational model developed is tested in example problems. The influence of both the temperature and the finite element model on the optimal solution obtained is analysed.     

Topology optimization of multiscale elastoviscoplastic structures

This paper extends current concepts of topology optimization to the design of structures made of nonlinear microheterogeneous materials. The objective is to maximize the macroscopic structural stiffness for a prescribed material volume usage while accounting for the nonlinearity and the microstructure of the material. The resulting design problem considers two scales: the macroscopic scale at which the optimization is performed and the microscopic scale at which the material heterogeneities and the nonlinearities are observed. The topology optimization at the macroscopic scale is performed by means of the bi‐directional evolutionary structural optimization method. The solution of the macroscopic boundary value problem requires as inputs the effective constitutive response with full consideration of the microstructure. While computational homogenization methods such as the FE² method could be used to solve the nonlinear multiscale problem, the associated numerical expense (CPU time and memory) is highly unacceptable. In order to regain the computational feasibility of the computational scale transition, a recent model reduction technique of the authors is employed: the potential‐based reduced basis model order reduction with graphics processing unit acceleration. Numerical examples show the efficiency of the resulting nonlinear two‐scale designs. The impact of different load amplitudes on the design is examined. Copyright © 2015 John Wiley & Sons, Ltd.     

A new efficient convergence criterion for reducing computational expense in topology optimization: reducible design variable method

A new efficient convergence criterion, named the reducible design variable method (RDVM), is proposed to save computational expense in topology optimization. There are two types of computational costs: one is to calculate the governing equations, and the other is to update the design variables. In conventional topology optimization, the number of design variables is usually fixed during the optimization procedure. Thus, the computational expense linearly increases with respect to the iteration number. Some design variables, however, quickly converge and some other design variables slowly converge. The idea of the proposed method is to adaptively reduce the number of design variables on the basis of the history of each design variable during optimization. Using the RDVM, those design variables that quickly converge are not considered as design variables for the next iterations. This means that the number of design variables can be reduced to save the computational costs of updating design variables. Then, the iteration will repeat until the number of design variables becomes 0. In addition, the proposed method can lead to faster convergence of the optimization procedure, which indeed is a more significant time saving. It is also revealed that the RDVM gives identical optimal solutions as those by conventional methods. We confirmed the numerical efficiency and solution effectiveness of the RDVM with respect to two types of optimization: static linear elastic minimization, and linear vibration problems with the first eigenvalue as the objective function for maximization. Copyright © 2012 John Wiley & Sons, Ltd.     

Composite material design of two‐dimensional structures using the homogenization design method

Composite materials of two‐dimensional structures are designed using the homogenization design method. The composite material is made of two or three different material phases. Designing the composite material consists of finding a distribution of material phases that minimizes the mean compliance of the macrostructure subject to volume fraction constraints of the constituent phases, within a unit cell of periodic microstructures. At the start of the computational solution, the material distribution of the microstructure is represented as a pure mixture of the constituent phases. As the iteration procedure unfolds, the component phases separate themselves out to form distinctive interfaces. The effective material properties of the artificially mixed materials are defined by the interpolation of the constituents. The optimization problem is solved using the sequential linear programming method. Both the macrostructure and the microstructures are analysed using the finite element method in each iteration step. Several examples of optimal topology design of composite material are presented to demonstrate the validity of the present numerical algorithm. Copyright © 2001 John Wiley & Sons, Ltd.     

模糊参数平面连续体结构的拓扑优化设计

研究了具有模糊参数的连续体结构在模糊载荷作用下的拓扑优化设计问题。利用信息熵将模糊变量转换为随机变量,构建了随机载荷作用下的随机参数的连续体结构的拓扑优化设计数学模型,以结构的形状拓扑信息为设计变量,结构总质量均值极小化为目标函数,满足单元应力可靠性为约束条件,利用分布函数法对应力可靠性约束进行了等价显式化处理。基于随机因子法,利用代数综合法导出了应力响应的数字特征的计算表达式。采用双方向渐进结构优化(BESO)方法求解。通过两个算例验证了该文模型及求解方法的合理性和有效性。     

Topology optimization in magnetic fields using the homogenization design method

To improve the performance of electric machinery, it is necessary to obtain the optimal topology of a structure in magnetic fields. The homogenization design method is applied to obtain the optimal topology. In the method, the change of inner hole size and rotational angle of unit cell determines the optimal material distribution in a design domain and this distribution defines an optimal topology. The objective function is defined as maximizing magnetic mean compliance (MMC). This is the same as maximizing magnetic vector potential and effective to improve the performance of electomagnet. The analysis and optimization is performed based on three‐dimensional hexahedral elements. This design method is applied to the H‐shaped electromagnet (H‐magnet). Copyright © 2000 John Wiley & Sons, Ltd.     

Robust concurrent topology optimization of multiscale structure under single or multiple uncertain load cases

Concurrent topology optimization of macrostructure and material microstructure has attracted significant interest in recent years. However, most of the existing works assumed deterministic load conditions, thus the obtained design might have poor performance in practice when uncertainties exist. Therefore, it is necessary to take uncertainty into account in structural design. This article proposes an efficient method for robust concurrent topology optimization of multiscale structure under single or multiple load cases. The weighted sum of the mean and standard deviation of the structural compliance is minimized and constraints are imposed to both the volume fractions of macrostructure and microstructure. The effective properties of the microstructure are calculated via the homogenization method. An efficient sensitivity analysis method is proposed based on the superposition principle and orthogonal similarity transformation of real symmetric matrices. To further reduce the computational cost, an efficient decoupled sensitivity analysis method for microscale design variables is proposed. The bidirectional evolutionary structural optimization method is employed to obtain black and white designs for both macrostructure and microstructure. Several two-dimensional and three-dimensional numerical examples are presented to demonstrate the effectiveness of the proposed approach and the effects of load uncertainty on the optimal design of both macrostructure and microstructure.     

Topology optimization of periodic cellular solids based on a superelement method

It is well known that the structural performance of lightweight cellular solids depends greatly on the design of the representative volume element (RVE). In this article, an integrated topology optimization procedure is developed for the global stiffness maximization of 2D periodic and cyclic-symmetry cellular solids. A design variable linking technique and a superelement method are applied to model the structural periodicity and to reduce the computing time. In order to prevent the numerical instabilities associated with checkerboards in the design process, the quadratic perimeter constraint is used. Finally, the topology optimization problem is solved by the dual optimization algorithm. Several numerical examples are used to test the efficiency of the optimization procedure. Results show that the optimal topology of the RVE is not unique. It greatly depends on the size of the RVE. The computing efficiency can be greatly improved by means of the superelement technique. Also, for the optimal solution, the equivalent torsional rigidity has been compared with what is in the literature, to check the structural efficiency of the obtained topology. It has been observed that the current topology solution has the strongest rigidity when the same volume fraction of solid-phase materials is used.     

负泊松比微结构拓扑优化设计

在构建负泊松比结构拓扑优化模型时,直接用负泊松比的数学表达式构造目标函数,将使得目标函数高度非线性,迭代过程敏度分析困难。采用线性拟合法,构建了具有线性特征的负泊松比微结构拓扑优化目标函数,基于能量法和均匀化方法,结合拓扑优化理论,构建了一种可以快速准确求解负泊松比的拓扑优化设计模型,求解该模型得到了一种优化的拓扑构型及相应的负泊松比值。根据优化求解得到的结构模型,参考国家标准GB/T 22315-2008《金属材料弹性模量和泊松比试验方法》,利用有限元软件对其泊松比进行仿真计算,然后采用激光加工方式制造试样,并测试其泊松比,经过与优化模型求解得到的泊松比值对比分析,验证了所构建优化模型的正确性。本文方法既避免了以负泊松比表达式为优化函数时会出现的高度非线性问题,也降低了求解的复杂程度,为负泊松比微结构的设计提供了一种参考方法。     

Material cloud method for topology optimization

Material cloud method (MCM), a new approach for topology optimization, is presented. In MCM, an optimal structure can be obtained by manipulating the sizes and positions of material clouds, which are material patches with finite sizes and constant material densities. The optimal distributions of material clouds can be obtained by MCM using fixed background finite element meshes. In the numerical analysis procedure, only active elements, where more than one material cloud is contained, are treated. Optimal material distribution can be element‐wise extracted from the distribution of material clouds. With MCM, an expansion–reduction procedure of design domain can be naturally realized through movements of material clouds, so that a true optimal solution can be found without any significant increase of computational costs. It is also shown that a clear material distribution with narrow region of intermediate density can be obtained with relatively fast convergence. Several numerical examples are shown. Some of the results are compared with those of the traditional density distribution method (DDM). Copyright © 2005 John Wiley & Sons, Ltd.     

桁架结构智能布局优化设计

结构的布局优化由于涉及尺寸、形状和拓扑三个层次的综合设计而成为优化问题中的难点,结合桁架结构提出了一个基于多个初始基结构的布局优化方法。以智能生成的、型式多样合理的基结构代替传统模型中的单一基结构,然后从不同基结构下的拓扑优化结果中找出最优设计。在克服传统基结构法有可能限制求解空间而丢失最优解这一局限性的同时,将形状和拓扑优化设计有效分离,降低了求解的难度,并且结合拓扑变化法,实现了桁架结构从选型生成、分析计算到优化设计的一体化智能设计过程。算例表明:利用该文提出的方法进行桁架结构的最优布局设计是可靠有效的。     

A new scheme for imposing a minimum length scale in topology optimization

A new scheme for imposing a minimum length scale in topology optimization is presented. It guarantees the existence of an optimal design for a large class of topology optimization problems of practical interest. It is formulated as one constraint that is computationally cheap and for which sensitivities are also cheap to compute. The constraint value is ideally zero, but it can be relaxed to a positive value. The effect of the method is illustrated in topology optimization for minimum compliance and design of compliant mechanisms. Notably, the method produces compliant mechanisms with distributed flexibility, something that has previously been difficult to obtain using topology optimization for the design of compliant mechanisms. The term ‘MOLE method’ is suggested for the method. Copyright © 2003 John Wiley & Sons, Ltd.     

Topology optimization of compliant mechanisms using the homogenization method

A procedure to obtain a topology of an optimal structure considering flexibility is presented. The methodology is based on a mutual energy concept for formulation of flexibility and the homogenization method. A multi-objective optimization problem is formulated as an application of compliant mechanism design. Some examples of the design of compliant mechanisms for plane structures are presented. © 1998 John Wiley & Sons, Ltd.     

稳态热传导结构非概率可靠性拓扑优化设计

研究具有区间参数的稳态热传导结构在散热弱度非概率可靠性约束下的拓扑优化设计问题。建立了以单元相对导热系数为设计变量,导热材料体积极小化为目标函数,满足散热弱度非概率可靠性为约束条件的稳态热传导结构的拓扑优化设计数学模型。基于区间因子法,推导出散热弱度的均值及离差的计算表达式。采用渐进结构优化法的求解策略与方法,并利用过滤技术消除优化过程中的数值不稳定性现象。通过算例验证文中模型及求解策略、方法的合理性和有效性。     

基于权重比的车架多工况拓扑优化方法研究

在赛车实际行驶过程中车架会受到各种工况的考验,因此在进行车架结构拓扑优化设计时必须同时考虑多个工况下车架的拓扑优化结果.然而,在进行多工况下拓扑结构设计时往往会遇到如何分配各个工况权重比的问题,各工况权重比的分配直接影响车架最终的拓扑结构.针对此问题进行研究,通过构造代理模型并利用遗传算法寻找最佳权重比.首先,采用折衷规划法建立同时考虑多个工况下车架刚度的拓扑优化综合目标函数模型;接着,采用最优拉丁超立方试验设计方法采样,构造径向基函数代理模型,并在代理模型的基础上利用NSGA-II进行求解,得到各个工况最佳权重比;最后,将获得的各个工况最佳权重比代入综合目标模型中进行拓扑计算,获得同时考虑各工况下车架刚度的拓扑结构.将该方法与获得权重比常用的层次分析法(AHP)和正交试验法(OED)进行比较,该方法较其他两种方法得到的综合目标值是最优的,车架所有工况的加权柔度是最低的.结果表明,所提出的方法很好地解决了多工况下拓扑优化权重比分配的问题,并且较其他方法具有明显的优越性.     

Multi-material topology optimization for the transient heat conduction problem using a sequential quadratic programming algorithm

Transient heat conduction analysis involves extensive computational cost. It becomes more serious for multi-material topology optimization, in which many design variables are involved and hundreds of iterations are usually required for convergence. This article aims to provide an efficient quadratic approximation for multi-material topology optimization of transient heat conduction problems. Reciprocal-type variables, instead of relative densities, are introduced as design variables. The sequential quadratic programming approach with explicit Hessians can be utilized as the optimizer for the computationally demanding optimization problem, by setting up a sequence of quadratic programs, in which the thermal compliance and weight can be explicitly approximated by the first and second order Taylor series expansion in terms of design variables. Numerical examples show clearly that the present approach can achieve better performance in terms of computational efficiency and iteration number than the solid isotropic material with penalization method solved by the commonly used method of moving asymptotes. In addition, a more lightweight design can be achieved by using multi-phase materials for the transient heat conductive problem, which demonstrates the necessity for multi-material topology optimization.     

OPTIMAL TOPOLOGIES OF FLEXURAL SYSTEMS

The main objects of this paper are:

a)To introduce some relationships between optimal topologies and the geometric parameters of flexural systems.b) To investigate the effect of compatibility conditions on the optimal topology.

Assuming the force method analysis, a linear programming formulation can be obtained under certain circumstances. In such cases where the active constraints can be determined a priori, a direct solution in the space of redundant forces might be possible.

It is shown that the optimal design might correspond to a singular point in the design space. Neglecting compatibility conditions, multiple optimal topologies might be obtained for certain geometries. In such cases some of the resulting solutions usually represent statically determinate structures, therefore compatibility conditions do not affect the optimum

Numerical examples illustrate these phenomena and how the optimal topology and its corresponding load path change with the geometric parameters.     

基于变频率区间约束的结构材料优化设计

针对频率约束的结构材料优化问题,基于结构拓扑优化思想,提出变频率区间约束的结构材料优化方法。借鉴均匀化及ICM(独立、连续、映射)方法,以微观单元拓扑变量倒数为设计变量,导出宏观单元等效质量矩阵及导数,进而获得频率一阶近似展开式。结合变频率区间约束思想,获得以结构质量为目标函数、频率为约束条件的连续体微结构拓扑优化近似模型;采用对偶方法求解。通过算例验证该方法的有效性及可行性,表明考虑质量矩阵变化影响所得优化结果更合理。     

拓扑优化方法及其在微型柔性结构设计中的应用

介绍了连续体结构拓扑优化设计中常用的均匀化方法和渐进结构优化法的原理，对拓扑优化中出现的数值不稳定现象——棋盘格式、网格依赖性和局部极值——进行了分析，通过典型实例和笔者最近的研究工作说明了拓扑优化在微型柔性机构设计中的应用，最后对拓扑优化技术的发展进行了展望。     

多载荷多工位转盘拓扑优化设计

基于拓扑优化理论,以结构总质量最小为目标,利用SIMP材料插值方法,结合HyperWorks/Optistruct拓扑优化功能对自动化组装设备中常用的多工位转盘进行了拓扑优化．根据优化后的重构模型与原始结构模型的静力学对比分析知,优化后降低了多工位转盘的总质量,提高了多工位转盘的刚度,同时减小了多工位转盘的局部最大应力．数据结果表明本方法对多工位转盘优化设计是有效的．