A Modified Bi-Directional Evolutionary Structural Optimization Procedure with Variable Evolutionary Volume Ratio Applied to Multi-Objective Topology Optimization Problem

Natural frequency and dynamic stiffness under transient loading are two key performances for structural design related to automotive,aviation and construction industries.This article aims to tackle the multi-objective topological optimization problem considering dynamic stiffness and natural frequency using modified version of bi-directional evolutionary structural optimization(BESO).The conventional BESO is provided with constant evolutionary volume ratio(EVR),whereas low EVR greatly retards the optimization process and high EVR improperly removes the efficient elements.To address the issue,the modified BESO with variable EVR is introduced.To compromise the natural frequency and the dynamic stiffness,a weighting scheme of sensitivity numbers is employed to form the Pareto solution space.Several numerical examples demonstrate that the optimal solutions obtained from the modified BESO method have good agreement with those from the classic BESO method.Most importantly,the dynamic removal strategy with the variable EVR sharply springs up the optimization process.Therefore,it is concluded that the modified BESO method with variable EVR can solve structural design problems using multi-objective optimization.

Stress Relaxation and Sensitivity Weight for Bi-Directional Evolutionary Structural Optimization to Improve the Computational Efficiency and Stabilization on Stress-Based Topology Optimization

Stress-based topology optimization is one of the most concerns of structural optimization and receives much attention in a wide range of engineering designs.To solve the inherent issues of stress-based topology optimization,many schemes are added to the conventional bi-directional evolutionary structural optimization(BESO)method in the previous studies.However,these schemes degrade the generality of BESO and increase the computational cost.This study proposes an improved topology optimization method for the continuum structures considering stress minimization in the framework of the conventional BESO method.A global stress measure constructed by p-norm function is treated as the objective function.To stabilize the optimization process,both qp-relaxation and sensitivity weight scheme are introduced.Design variables are updated by the conventional BESO method.Several 2D and 3D examples are used to demonstrate the validity of the proposed method.The results show that the optimization process can be stabilized by qp-relaxation.The value of q and p are crucial to reasonable solutions.The proposed sensitivity weight scheme further stabilizes the optimization process and evenly distributes the stress field.The computational efficiency of the proposed method is higher than the previous methods because it keeps the generality of BESO and does not need additional schemes.

A Smooth Bidirectional Evolutionary Structural Optimization of Vibrational Structures for Natural Frequency and Dynamic Compliance

A smooth bidirectional evolutionary structural optimization(SBESO),as a bidirectional version of SESO is proposed to solve the topological optimization of vibrating continuum structures for natural frequencies and dynamic compliance under the transient load.A weighted function is introduced to regulate the mass and stiffness matrix of an element,which has the inefficient element gradually removed from the design domain as if it were undergoing damage.Aiming at maximizing the natural frequency of a structure,the frequency optimization formulation is proposed using the SBESO technique.The effects of various weight functions including constant,linear and sine functions on structural optimization are compared.With the equivalent static load(ESL)method,the dynamic stiffness optimization of a structure is formulated by the SBESO technique.Numerical examples show that compared with the classic BESO method,the SBESO method can efficiently suppress the excessive element deletion by adjusting the element deletion rate and weight function.It is also found that the proposed SBESO technique can obtain an efficient configuration and smooth boundary and demonstrate the advantages over the classic BESO technique.

Structural Topology Optimization by Combining BESO with Reinforcement Learning

In this paper,a new algorithm combining the features of bi-direction evolutionary structural optimization(BESO)and reinforcement learning(RL)is proposed for continuum structural topology optimization(STO).In contrast to conventional approaches which only generate a certain quasi-optimal solution,the goal of the combined method is to provide more quasi-optimal solutions for designers such as the idea of generative design.Two key components were adopted.First,besides sensitivity,value function updated by Monte-Carlo reinforcement learning was utilized to measure the importance of each element,which made the solving process convergent and closer to the optimum.Second,ε-greedy policy added a random perturbation to the main search direction so as to extend the search ability.Finally,the quality and diversity of solutions could be guaranteed by controlling the value of compliance as well as Intersection-over-Union(IoU).Results of several 2D and 3D compliance minimization problems,including a geometrically nonlinear case,show that the combined method is capable of generating a group of good and different solutions that satisfy various possible requirements in engineering design within acceptable computation cost.

Structural Optimization of Hatch Cover Based on Bi-directional Evolutionary Structure Optimization and Surrogate Model Method

Weight reduction has attracted much attention among ship designers and ship owners.In the present work,based on an improved bi-directional evolutionary structural optimization(BESO) method and surrogate model method,we propose a hybrid optimization method for the structural design optimization of beam-plate structures,which covers three optimization levels:dimension optimization,topology optimization and section optimization.The objective of the proposed optimization method is to minimize the weight of design object under a group of constraints.The kernel optimization procedure(KOP) uses BESO to obtain the optimal topology from a ground structure.To deal with beam-plate structures,the traditional BESO method is improved by using cubic box as the unit cell instead of solid unit to construct periodic lattice structure.In the first optimization level,a series of ground structures are generated based on different dimensional parameter combinations,the KOP is performed to all the ground structures,the response surface model of optimal objective values and dimension parameters is created,and then the optimal dimension parameters can be obtained.In the second optimization level,the optimal topology is obtained by using the KOP according to the optimal dimension parameters.In the third optimization level,response surface method(RSM) is used to determine the section parameters.The proposed method is applied to a hatch cover structure design.The locations and shapes of all the structural members are determined from an oversized ground structure.The results show that the proposed method leads to a greater weight saving,compared with the original design and genetic algorithm(GA) based optimization results.

基于BESO算法的大型海洋垂直轴风力机支撑结构优化

大型海洋垂直轴风力机的研究对发展海洋风能具有重要意义,研究大型垂直轴风力机的合理支撑结构形式对风力发电结构安全至关重要.基于变删除率的双向渐进结构优化(BESO)算法,对大型海洋垂直轴风力机进行支撑结构优化,并通过风力机的动力响应特性分析,验证结构优化方法的可靠性.结果表明:反比例型变删除率的BESO算法能有效改善优化迭代速率,适用于垂直轴风力机的支撑结构优化设计;相比于初始结构,拓扑出的新结构模型在风荷载作用下的风致动力响应显著降低.研究成果可用于垂直轴风力机支撑结构设计优化.

基于BESO方法的连续体结构动态特性多目标拓扑优化

为实现动态多目标下的拓扑优化结构设计,以结构动柔顺度最小化和固有频率最大化加权函数为目标,提出基于双向渐进结构优化方法(Bi-direction Evolutionary Structural Optimization, BESO)的连续体结构动态特性多目标拓扑优化方法。基于等效静载荷法(Equivalent Static Loads, ESL),将结构动刚度优化问题转化为多工步载荷作用下的线性静刚度优化问题,结合BESO方法实现结构多工况线性静态优化。分别归一化目标函数和灵敏度,避免不同性质目标函数及灵敏度的量级差异引起的数值奇异性。数值算例结果表明,结构体积约束、频率与动柔顺度综合目标均能渐进收敛于最优目标值,优化结构具有清晰的拓扑构型。随着柔顺度灵敏度、权重因子的减小,优化结构拓扑形式发生显著变化,其动刚度逐渐减小,而固有频率逐渐增加。所提出的频率-动刚度多目标拓扑优化方法能够提高结构动态特性,拓展了BESO方法对结构动力学拓扑优化问题的应用范围。

Layout optimization of steel reinforcement in concrete structure using a truss-continuum model

Owing to advancement in advanced manufacturing technology,the reinforcement design of concrete structures has become an important topic in structural engineering.Based on bi-directional evolutionary structural optimization(BESO),a new approach is developed in this study to optimize the reinforcement layout in steel-reinforced concrete(SRC)structures.This approach combines a minimum compliance objective function with a hybrid trusscontinuum model.Furthermore,a modified bi-directional evolutionary structural optimization(M-BESO)method is proposed to control the level of tensile stress in concrete.To fully utilize the tensile strength of steel and the compressive strength of concrete,the optimization sensitivity of steel in a concrete–steel composite is integrated with the average normal stress of a neighboring concrete.To demonstrate the effectiveness of the proposed procedures,reinforcement layout optimizations of a simply supported beam,a corbel,and a wall with a window are conducted.Clear steel trajectories of SRC structures can be obtained using both methods.The area of critical tensile stress in concrete yielded by the M-BESO is more than 40%lower than that yielded by the uniform design and BESO.Hence,the M-BESO facilitates a fully digital workflow that can be extremely effective for improving the design of steel reinforcements in concrete structures.

复合材料/结构两尺度动力学拓扑优化设计

基于均匀化理论,建立以结构第一阶固有频率最大为目标的宏/微观结构构型与材料分布的两尺度动力学拓扑优化模型,推导目标函数和约束函数对宏/微观设计变量的灵敏度,研究两尺度动力学拓扑优化方法。另外,采用一个修正固体各向同性材料惩罚(SIMP)模型避免局部模态现象。相关数值算例说明,该方法可以有效实现结构基频最大化的材料/结构两尺度动力学拓扑优化设计。此外,通过算例研究复合材料的弹性模量对优化结果的影响规律。

考虑质量约束的多相材料结构拓扑优化新方法

提出了一种将双向渐进法(BESO)与快速非支配排序遗传算法(NSGA-Ⅱ)相结合的拓扑优化方法,称为BESO-NSGA-Ⅱ方法.与传统双向渐进法的体积约束不同,本文算法以质量作为约束条件,并采用多相材料插值方案实现了多相材料的优化分布.通过大量的算例,证明了算法的稳定性和有效性.与传统双向渐进法相比,新算法在相同约束条件下能有效地提高结构刚度.同时,为了获得干净的拓扑,该算法提出了在交叉变异过程中使用的双惩罚算子来实现干净的拓扑结构.结果表明,该算法能较好地实现结构的轻量化设计.

COMPUTER PROGRAM FOR DIRECTED STRUCTURE TOPOLOGY OPTIMIZATION

To compensate for the imperfection of traditional bi-directional evolutionary structural optimization, material interpolation scheme and sensitivity filter functions are introduced. A suitable filter can overcome the checkerboard and mesh-dependency. And the historical information on accurate elemental sensitivity numbers are used to keep the objective function converging steadily. Apart from rational intervals of the relevant important parameters, the concept of distinguishing between active and non-active elements design is proposed, which can be widely used for improving the function and artistry of structures directly, especially for a one whose accurate size is not given. Furthermore, user-friendly software packages are developed to enhance its accessibility for practicing engineers and architects. And to reduce the time cost for large timeconsuming complex structure optimization, parallel computing is built-in in the MATLAB codes. The program is easy to use for engineers who may not be familiar with either FEA or structure optimization. And developers can make a deep research on the algorithm by changing the MATLAB codes. Several classical examples are given to show that the improved BESO method is superior for its handy and utility computer program software.

基于双尺度拓扑优化的多相材料结构设计方法

针对双尺度优化问题,研究小组提出了一种将双向渐进法(BESO)与快速非支配排序遗传算法(NSGA-Ⅱ)相结合的拓扑优化方法,称为BESO-NSGA-Ⅱ。通过基于能量的均匀化理论推导非均质材料的有效性质,并采用多相材料插值方案实现双尺度结构多相材料的拓扑优化。为了获得“干净”的拓扑,BESO-NSGA-Ⅱ算法提出了在交叉变异过程中使用双惩罚算子来实现“干净”的拓扑结构。通过算例并与经典BESO算法进行对比,验证了BESO-NSGA-Ⅱ算法的稳定性和有效性及其获得收敛解的能力,以期为后续的双尺度拓扑优化研究提供参考依据。

基于柔性机构的机翼前缘变形多目标优化

全柔性机构用于自适应机翼具有实现其形状的连续平滑变形和轻量化等优点。文章根据机翼前缘在不同飞行状态下气动外形要求,以离散体结构拓扑优化为出发点,以目标形状与实际形状的边界曲线之差最小为优化目标,并考虑机构变形要求和刚性要求等问题,建立了多目标优化函数;采用遗传算法(GA)和双向渐进结构优化法(BESO)相结合,应用于Matlab与Ansys,通过二次优化,获得了稳定的最优解,不仅实现编程模块化,而且提高了优化效率。最后,对结果进行Ansys仿真分析和模型实验验证。结果表明:仿真结果和模型实验结果一致,该方法是可行的。

基于应力突变率的双向进化结构优化方法

提出了一种新的基于应力突变率的双向进化结构优化方法,以进化优化过程中一次删除或添加单元后,新旧拓扑结构的应力突变率作为添加单元的准则,实现了线弹性结构的拓扑优化设计。方法易于实现并改进了传统双向进化结构优化方法中参数较多的缺点。算例表明:基于应力突变率的双向进化结构优化方法可以得到结构合理、边界清晰的拓扑优化构形,并且具有更好的全局寻优能力。

面向飞机颤振模型设计的结构拓扑优化研究

飞机颤振模型的结构设计是一个以固有频率为目标、兼具结构相似要求的反求问题。针对拓扑优化方法只能得到不规则孔洞而无法满足模型相似要求的难题,提出了一种含规则几何约束的结构拓扑优化方法,并将基于单元材料特性更改的方法与双向渐进结构法相结合,利用敏度再分配方法,实现了以频率为目标、具有规则孔洞的结构拓扑优化,且有效抑制了优化中的棋盘格式和局部模态现象。某飞机机身壁板的优化算例证明,该方法能设计出具有给定固有频率的结构,并使之与原机身具有一定的结构相似性。

基于非概率可靠性的连续体结构拓扑优化设计

研究区间参数的连续体结构在区间载荷作用下的拓扑优化设计问题。构建区间载荷作用下区间参数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,满足单元区间应力非概率可靠性为约束条件。基于区间因子法,导出应力响应的均值和离差的计算表达式。采用双方向渐进结构优化(bi-directional evolutionary structural optimization,BESO)的求解策略与方法。通过两个算例验证文中模型及求解策略与方法的合理性和方法的有效性。

结构定向拓扑优化及软件实现

基于区域分割思想对传统双向渐进结构优化方法进行必要地改进,在优化过程中通过添加边界条件的检查语句,实现结构定向拓扑优化;编写第三方插件,使得改进后的优化方法 MATLAB子程序与ABAQUS有限元软件数据交换,从而拓展了双向渐进结构优化方法的实际工程运用领域。ABAQUS建模软件具有界面操作简单、建模快捷、通用性好、易于实现等特点,降低了对设计人员的技能要求。灵活的MATLAB二次开发平台为科研人员提供了广阔的算法改进空间。算例结果表明,优化后桥梁用料变为原有的17%,大大减轻了自重,且优化后的结构对称,受力合理。该算法可运用于对预设结构有特定使用要求或美观要求的结构优化问题。

基于增材制造各向异性的强度约束拓扑优化

增材制造工艺的特殊性导致制造结构展现出各方向不同的力学性能,为满足其所带来的更加严苛的结构强度设计需求,提出了一种基于双向渐进结构优化法的各向异性强度约束拓扑优化策略。推导了描述增材结构强度的各向异性Tsai-Hill失效系数,通过权重因子构建了包含失效系数约束的目标函数。详细求解了优化灵敏度公式,并采用敏度归一化等数值方法稳定优化历程。典型算例表明,所提方法可有效抑制高失效风险区域以保证结构强度,且在材料各向异性强度假设下可获得更优于von-Mesis应力相关设计的结果。此外,优化结果高度依赖于各向异性程度与材料堆叠角度参数的变化,因此合理的调整将有助于优化结构性能。

基于拓扑优化的油船货舱结构设计研究

研究油船货舱结构拓扑优化设计和普通构件级结构拓扑优化设计的不同点:如设计变量数目多、约束条件多、计算工况多以及计算工况之间应变能差异等。为使普通计算机也能运行舱段结构拓扑优化计算并得到清晰拓扑构型的结果,有必要对舱段拓扑优化设计的优化对象、单元类型、初始板厚、工具方法、约束条件、体积分数、工况加权权值等主要控制参数进行研究。文中给出工程上适用的舱段拓扑优化基结构建模方法和计算方法,并以某一单纵舱壁型VLCC为例,分别采用SIMP法和BESO法给出舱段主要支撑结构拓扑优化的清晰构型。

以频率为目标的加筋平板结构优化设计研究

以加筋平板结构的多阶模态频率达到指定值为优化目标,探讨结构的优化设计方法。提出一种双向渐进结构拓扑优化法结合尺寸优化方法的结构频率优化设计的改进方法。该方法采用具有规则格栅骨架的加筋平板结构优化模型,以骨架中的梁为结构修改基本单位,以梁敏度计算为基础。实现以频率为目标函数、以体积为约束,并结合敏度再分配策略的结构优化设计。最后,运用尺寸优化方法对优化结果进行后续详细设计。经加筋平板结构频率优化设计算例证明,该方法能满足结构的多阶模态频率优化要求;同时优化结果不存在一般拓扑优化的不规则结构问题,抑制局部模态的产生,对飞机风洞颤振实验模型的设计具有借鉴意义。