基于密度-敏度层次更新策略的三维连续体结构拓扑优化

针对三维连续体结构静力学拓扑优化中灰度单元过多的问题,以结构的柔度最小为目标函数,运用基于SIMP插值方法建立的静力学拓扑优化数学模型,提出一种密度-敏度层次更新策略.以数控插齿机床身为例,运用该更新策略,采用MATLAB编程进行三维拓扑优化.优化结果中灰度单元明显减少,说明了密度-敏度层次更新策略的合理性.     

基于ICM法的高层建筑大型支撑体系拓扑优化

提出应用连续体结构拓扑优化ICM法对高层建筑大型支撑体系进行拓扑优化。针对高层建筑规范对结构刚度限值是以层间相对位移差形式给出、并结合结构拓扑优化特点,推导了相对位移差敏度分析的伴随法公式,有效提高了计算效率。应用ICM法建立位移约束下结构重量极小化的优化模型,与高层建筑规范对结构刚度限值要求的提法更符合,得到的最优拓扑完全满足规范要求。所提方法应用在概念设计阶段,提供了一种自动化的分析计算及优化设计工具,可以有效地弥补基于经验设计的不足。     

连续体结构的变密度拓扑优化方法研究

为了实现使连续体结构的体积约束和柔顺度最小的拓扑优化及解决采用经典变密度法引起的结构优化结果存在如灰度单元、棋盘格等数值不稳定问题，提出了一种新的拓扑优化方法。首先，采用改进的固体各向同性材料惩罚法作为材料插值方案，建立结构拓扑优化模型；其次，通过引入基于高斯权重函数的敏度过滤法和设计新灰度单元抑制算子来解决数值不稳定问题；最后，借助优化准则法求解优化模型。通过算例分析可知：新策略可以改进拓扑优化方法；新的拓扑优化方法具有收敛速度较快、能更好地获取柔顺度小且拓扑构型好的优化结构和抑制灰度单元产生等优势。研究结果为其他连续体结构的拓扑优化研究提供了新思路。     

考虑设计相关载荷的稳态热传导拓扑优化设计

针对稳态热传导问题,以结构散热弱度最小为目标,建立了连续体传热结构的拓扑优化模型和方法,给出了相应的算例。优化方法中分别建立了设计相关载荷和非相关载荷的灵敏度列式,采用Rational Approximation of Material Properties (RAMP)方法对材料密度进行惩罚,利用优化准则法控制设计目标与材料分布,以敏度过滤技术抑制棋盘格效应。算例的结果直观显示了设计相关载荷和非设计相关载荷以及复合载荷对结构拓扑构型的影响规律,表明了该文考虑设计相关载荷的稳态热传导结构拓扑优化方法的合理性。     

考虑热振特性的连续体结构拓扑优化设计

为实现传热和振动条件下连续体结构的拓扑优化设计,以结构散热弱度最小化和动态特征值最大化加权函数为目标,建立传热和振动条件下连续体结构的多目标拓扑优化模型,实现了相应的算法和算例。方法中采用Rational Approximation of Material Properties(RAMP)方法对密度进行惩罚,利用优化准则法控制设计目标与材料分布,以敏度过滤技术抑制棋盘格效应,通过归一化目标函数有效地避免了不同性质目标函数的量级差异。通过算例,获得了热-振权重系数对结构拓扑构型和目标函数(宏观结构的散热弱度和基频)的影响规律,算例结果表明了该方法的有效性。     

基于对数型Heaviside近似函数作为过滤函数的动力响应结构拓扑优化ICM方法

应用ICM(Independent Continuous and Mapping)方法, 建立了以重量最小为目标函数, 以连续频率带或离散点频率的简谐激励下的响应振幅为约束的拓扑优化模型. 引入了对数型Heaviside近似函数作为过滤函数, 并做了敏度分析, 利用对偶二次规划进行优化模型的求解, 并运用敏度过滤的方法处理动力响应数值不稳定的问题. 数值算例比较了利用对数型函数和幂函数作为过滤函数时对拓扑结构的影响, 结果显示利用对数型函数较幂函数结构优化迭代次数更少, 收敛更快.     

自由阻尼层结构阻尼材料配置优化的拓扑敏度法

提出阻尼胞单元和阻尼拓扑敏度等概念，建立了基于阻尼拓扑敏度综合评价的阻尼材料拓扑优化准则，并用于自由阻尼层结构振动控制中阻尼材料的配置优化。建立待控结构阻尼材料布局的拓扑基结构，计算各单元的阻尼拓扑敏度。再建立考虑重量目标及结构频响峰值约束的阻尼材料配置拓扑优化模型。根据所提出的阻尼材料拓扑优化准则，求解上述配置优化问题，确定阈值和各单元拓扑值。并用若干典型结构算例，验证所提出方法的正确性，讨论了阻尼材料布局拓扑基结构的规模与优化效率的关系。     

基于物质点描述的双向渐进式拓扑优化方法

:为了克服连续体结构拓扑优化中的数值不稳定现象,定义了表征物质点及其领域有无的物质点拓扑变量,提出基于物质点描述的双向渐进式拓扑优化方法.基于过滤法构造拓扑变量场的插值函数,从而在拓扑优化模型中自然消除了棋盘格现象.为适用于不同单元类型和网格离散形式等,重新定义了灵敏度密度.通过二维数值算例对理论方法进行验证.结果表明:方法在连续体结构拓扑优化设计中具有可行性和有效性.     

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。     

敏度分析与修正降维法

本文介绍了连续体结构形状优化设计中灵敏度分析的一种有效方法。根据设计变量和单元结点座标之间的映射关系,推导出三结点常应变元敏度分析的显式,避免用差分计算敏度时步长难以选定的困难,提高了精度及稳定性。本文还研究了修正降维法,并将该法应用于连续体结构的性态及敏度分析。示例表明,修正降维法具有很高的效率和满意的精度。     

基于混合PSO算法的桁架动力响应优化

摘 要：本文针对以结构动力响应为约束,最小重量为目标的桁架拓扑优化问题,提出了一种将微粒群算法和优化准则法结合的混合PSO算法。利用优化准则法的迭代关系找出群体中适应度最好的微粒,将其作为特殊微粒,其他微粒的寻优采用PSO的基本进化规则,位移响应约束利用特殊微粒的灵敏度信息近似计算。算例的计算结果表明,混合PSO算法适用于受简谐荷载以及脉冲荷载作用桁架结构的拓扑优化。混合PSO的计算效率比PSO算法高,其优化效果比优化准则法好。     

A hybrid topology optimization algorithm for static and vibrating shell structures

Structural designers are reconsidering traditional design procedures using structural optimization techniques. Although shape and sizing optimization techniques have facilitated a great improvement in the emergence of new optimum designs, they are still limited by the fact that a suitable topology must be assumed initially. In this paper a hybrid algorithm entitled constrained adaptive topology optimization, or CATO is introduced. The algorithm, based on an artificial material model and an adaptive updating scheme, combines ideas from the mathematically rigorous homogenization (h) methods and the intuitive evolutionary (e) methods. The algorithm is applied to shell structures under static or free vibration situations. For the static situation, the objective is to produce the stiffest structure subject to given loading conditions, boundary conditions and material properties. For the free vibration situation, the objective is to maximize or minimize a chosen frequency. In both cases, a constraint on the structural volume/mass is applied and the optimization process is achieved by redistributing the material through the shell structure. The efficiency of the proposed algorithm is illustrated through several numerical examples of shells under either static or free vibration situations. Copyright © 2002 John Wiley & Sons, Ltd.     

基于等几何裁剪分析的拓扑与形状集成优化

提出了将设计和分析、拓扑与形状优化集成的思想,探索了基于等几何裁剪分析的拓扑与形状集成优化设计算法,该方法统一了结构优化的计算机辅助设计、计算机辅助工程分析和优化设计的模型,基于B样条的等几何裁剪分析既能准确表达几何形状,又可以用裁剪面分析方便处理任意复杂拓扑优化问题,由裁剪选择标准确定合理的拓扑结构变动方向,结构变动时无需重新划分网格,设计结果突破初始设计空间的限制,还可方便优化形状。建立了等几何裁剪灵敏度分析的计算方法,给出了等几何裁剪分析拓扑与形状集成优化算法,通过典型实例表明所用方法的正确性和有效性。     

Topology optimization of double- and triple-layer grids using a hybrid methodology

In this article, a hybrid methodology combining evolutionary structural optimization (ESO) and gravitational particle swarm (GPS) methods is proposed for topology optimization of double- and triple-layer grids. In the present methodology, which is called the ESO-GPS method, the size optimization of double- and triple-layer grids is first performed by ESO. Then, the outcomes of the ESO are used to improve the GPS through four modifications. Structural weight is minimized against constraints on the displacements of nodes, internal stresses and element slenderness ratio. The GPS is used to investigate the optimum topology of large-scale skeletal structures with discrete variables whose agents update their respective positions by the particle swarm optimization velocity and the acceleration of the gravitational search algorithm. The numerical results show that the proposed algorithm, the ESO-GPS, performs better than the GPS and the other methods presented in the literature.     

Simultaneous partial topology and size optimization of a wing structure using ant colony and gradient based methods

This article presents a methodology and process for a combined wing configuration partial topology and structure size optimization. It is aimed at achieving a minimum structural weight by optimizing the structure layout and structural component size simultaneously. This design optimization process contains two types of design variables and hence was divided into two sub-problems. One is structure layout topology to obtain an optimal number and location of spars with discrete integer design variables. Another is component size optimization with continuous design variables in the structure FE model. A multi city-layer ant colony optimization (MCLACO) method is proposed and applied to the topology sub-problem. A gradient based optimization method (GBOM) built in the MSC.NASTRAN SOL-200 module was employed in the component size optimization sub-problem. For each selected layout of the wing structure, a size optimization process is performed to obtain the optimum result and feedback to the layout topology process. The numerical example shows that the proposed MCLACO method and a combination with the GBOM are effective for solving such a wing structure optimization problem. The results also indicate that significant structural weight saving can be achieved.     

Particle swarm optimization approach for multi-objective composite box-beam design

This paper presents a multi-agent search technique to design an optimal composite box-beam helicopter rotor blade. The search technique is called particle swarm optimization (‘inspired by the choreography of a bird flock’). The continuous geometry parameters (cross-sectional dimensions) and discrete ply angles of the box-beams are considered as design variables. The objective of the design problem is to achieve (a) specified stiffness value and (b) maximum elastic coupling. The presence of maximum elastic coupling in the composite box-beam increases the aero-elastic stability of the helicopter rotor blade. The multi-objective design problem is formulated as a combinatorial optimization problem and solved collectively using particle swarm optimization technique. The optimal geometry and ply angles are obtained for a composite box-beam design with ply angle discretizations of 10°, 15° and 45°. The performance and computational efficiency of the proposed particle swarm optimization approach is compared with various genetic algorithm based design approaches. The simulation results clearly show that the particle swarm optimization algorithm provides better solutions in terms of performance and computational time than the genetic algorithm based approaches.     

考虑位移要求的大型三维连续体结构拓扑优化数值技术研究

大型复杂三维结构拓扑优化设计既具有理论意义,又具有重要的应用价值。基于等效转换的非奇异的结构优化模型,研究结构位移要求的最小结构重量设计问题。首先,介绍了位移约束的三维结构优化准则和公式。而后,为了提高拥有数万个单元以上的三维结构的计算效率,结合结构位移计算的迭代方法,在分析用于结构特性参数计算模型的基础上,建立了一套三维结构拓扑优化的求解策略和算法。最后,给出了几个典型和复杂的三维结构的拓扑优化设计算例。算例表明求解策略和算法是正确和有效的,且具有广泛的工程应用前景。     

Structural shape and topology optimization based on level-set modelling and the element-propagating method

This article introduces the element-propagating method to structural shape and topology optimization. Structural optimization based on the conventional level-set method needs to solve several partial differential equations. By the insertion and deletion of basic material elements around the geometric boundary, the element-propagating method can avoid solving the partial differential equations and realize the dynamic updating of the material region. This approach also places no restrictions on the signed distance function and the Courant–Friedrichs–Lewy condition for numerical stability. At the same time, in order to suppress the dependence on the design initialization for the 2D structural optimization problem, the strain energy density is taken as a criterion to generate new holes in the material region. The coupled algorithm of the element-propagating method and the method for generating new holes makes the structural optimization more robust. Numerical examples demonstrate that the proposed approach greatly improves numerical efficiency, compared with the conventional level-set method for structural topology optimization.     

基于GMPSO的有限元模型修正方法验证

为提高有限元模型修正方法效率,保证修正精度,提出基于高斯白噪声扰动的粒子群优化（GMPSO）有限元模型修正方法。介绍标准粒子群优化（PSO）方法和改进后的GMPSO方法,基于测试函数比对两种方法的全局寻优能力和寻优效率;提出高效的基于GMPSO有限元模型修正方法,阐述方法流程并明确各参数与实际物理量的对应关系;基于GMPSO有限元模型修正方法对高维有损伤简支梁模型（变量维度为10）实施修正,并与基于遗传算法（GA）的模型修正结果进行比对;基于GMPSO有限元模型修正方法对某在役桥梁结构实施修正（变量维度为13）,验证所提方法可行性。结果表明:经局部改进的GMPSO方法较原PSO方法的优化能力显著提升;高维损伤简支梁模型修正结果显示,基于GMPSO模型修正方法可获得较好的修正结果,修正效率较基于GA的模型修正方法有显著提升;在役桥梁结构有限元模型修正结果显示,基于GMPSO模型修正方法可有效降低主梁计算频率和试验频率的误差,所提方法可适用于较工程复杂结构模型修正问题。     

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。