应力约束全局化处理的连续体结构ICM拓扑优化方法

由于应力约束按单元计,加之多工况,使得连续体结构拓扑优化由于约束数目太多,导致应力敏度分析计算量太大而无法接受。基于第四强度理论提出了应力约束条件全局化处理的方法,化为全局替代约束——总应变能约束,用ICM方法对总应变能约束条件下的连续体结构拓扑优化进行建模及求解,其过程分为三步:第一步选择最大应变能对应的工况,在给定重量下求出最小结构总应变能;第二步提出一个数值经验公式,借助第一步的结果,计算出各工况下的许用总应变能;第三步以第二步计算出来的各工况的许用总应变能作为约束,以重量为目标建立模型并求解。顺便指出,第二步的处理方法可以处理载荷相差特别大的情况,即病态载荷情况。数值算例表明:全局性应力约束可以更好地得到传力路径,对于处理多工况问题具有优势。     

结构畸变比能处理的应力约束全局化的连续体结构拓扑优化

该文根据von Mises强度准则的畸变比能本质,计算单元畸变比能替代应力约束;依照应力全局化策略,定义结构畸变比能约束概念,求解应力约束下重量最小的连续体结构拓扑优化问题,急剧地减少了应力约束。构造许用应力和结构最大应力的比值含参数幂函数,对约束限进行动态修正。基于ICM(Independent Continuous and Mapping,独立、连续、映射)方法,采用指数型快滤函数建立了结构在畸变比能约束下的结构拓扑优化模型,并选取精确映射下的序列二次规划进行求解。数值算例表明:采用修正的结构畸变比能的应力全局化策略,对于结构拓扑优化问题的求解是有用和高效的。该文提出的方法对解决工况间存在病态载荷的问题也是有益的。     

屈曲与应力约束下连续体结构的拓扑优化

基于ICM(独立、连续、映射)方法建立了以结构重量最小为目标,以屈曲临界力、应力同时为约束的连续体拓扑优化模型:采用独立的连续拓扑变量,借助泰勒展式、过滤函数将目标函数作二阶近似展开;借助瑞利商、泰勒展式、过滤函数将屈曲约束化为近似显函数;将应力这种局部性约束采用全局化策略进行处理,即借助第四强度理论、过滤函数将应力局部性约束转化为应变能约束,大大减少了灵敏度分析的计算量;将优化模型转化为对偶规划,减少了设计变量的数目,并利用序列二次规划求解,缩小了模型的求解规模。数值算例表明:该方法可以有效地解决屈曲与应力约束共同作用的连续体拓扑优化问题,能够得到合理的拓扑结构,并有较高的计算效率。     

基于应力约束全局化策略的板壳结构强度拓扑优化

应力约束下板壳结构的拓扑优化设计由于应力约束难以显式化和约束条件数量庞大等问题,存在建模和求解的困难。为了解决这些困难,首先,该文通过类比独立连续映射(Independent Continuous and Mapping, ICM)方法中的过滤函数,在实体各向同性材料惩罚(Solid Isotropic Material Penalization, SIMP)方法中引进了单元重量惩罚函数和材料许用应力惩罚函数,实现了对SIMP方法惩罚函数概念的拓广。然后,该文移植了ICM方法中行之有效的应力约束全局化策略,基于拓广后的SIMP方法,构造了代替应力约束后的结构畸变能约束的近似显式化函数,建立了多工况下板壳结构拓扑优化模型。最后,采用对偶序列二次规划算法求解该优化模型,并基于Python语言在ABAQUS软件平台进行了程序实现。数值算例都取得了很好的结果,这表明该文提出的方法是可行而有 效的。     

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。     

钢框架支撑体系连续型拓扑优化设计

为了研究连续型拓扑优化理论在实际工程中的应用,该文给出了一种多层钢框架支撑体系连续型拓扑优化设计方法。基于灵敏度分析,探讨了连续体结构在多工况荷载作用下、同时受应力和多位移约束的拓扑优化删除准则。为保证拓扑优化结果的合理性,提出了设计区域平均厚度的概念。在该文给出的优化设计方法中,首先在不考虑位移约束的情况下对无支撑钢框架进行优化设计,然后在有位移约束的条件下采用渐进结构优化算法和删除准则对支撑体系进行连续型拓扑优化设计,并将获得的支撑最优拓扑构形转化成相应的杆件。通过一个3跨12层钢框架支撑体系的拓扑优化设计实例验证了该文给出的钢框架支撑体系连续型拓扑优化设计方法的有效性。     

多工况应力约束下的拓扑优化格栅

提出一种多工况应力约束下格栅结构的拓扑优化方法。优化目标结构是由无限细无限密的梁(或肋)构成的类格栅连续体(或加肋板)。采用正交异性增强复合材料模型模拟该类格栅连续体(或加肋板)的本构关系。以梁在结点处的密度和方向作为设计变量。根据有限元分析结果,采用满应力准则法优化各单工况下材料分布。按照多工况下材料的方向刚度与各单工况下材料的方向刚度最大值的差值最小为原则建立多工况下梁(或肋)的拓扑优化分布。经过少量迭代就可以建立优化的材料连续分布场。最后以3个算例演示拓扑优化的过程,并给出结点处梁的密度和方向分布。     

基于类桁架材料模型的不确定荷载下结构拓扑优化

用区间分析方法研究了不确定荷载下结构拓扑优化方法。采用类桁架材料模型建立拓扑优化类桁架连续体结构。根据区间变量运算法则推导出不确定荷载下应力约束体积最小类桁架结构的拓扑优化方法。首先采用区间分析方法得到任一点的最不利荷载工况下应变状态。在此应变状态下,利用满应力准则优化类桁架材料中杆件的方向和密度。如此反复分析和优化,直至迭代收敛。最后由类桁架中杆件分布场可以近似离散得到桁架结构。通过几个数值算例验证了方法的有效性。数值算例显示了不确定荷载下的结构拓扑优化布局更合理。     

具有多约束连续体结构仿生拓扑优化方法

通过浮动参考区间法分析具有多约束连续体结构拓扑优化问题。浮动区间法是指将结构的拓扑优化过程看作是骨骼重建过程,通过引入参考应变区间,将结构中所有各点处主应变绝对值落入参考应变区间作为重建平衡状态,当结构处于重建平衡状态时获得结构的最优材料分布。为了使得优化结果满足给定的性态约束,参考应变区间在优化迭代过程中须不断变化。讨论了几种常见性态约束对结构性能的要求。给出了结构具有多约束时优化问题的算法。数值算例表明该方法可行。     

基于遗传算法的离散型结构拓扑优化设计

采用遗传算法求解包括桁架结构和框架结构的离散型结构拓扑优化问题。在遗传算法的基础上,通过引入拓扑变量并修改被删除杆件的材料弹性模量,提出了一个受多工况荷载作用,能同时考虑应力、稳定及位移等约束的离散型结构拓扑优化问题统一数学模型。该模型不但能同时适用于桁架结构和框架结构等离散型结构拓扑优化问题,而且还能解决奇异最优解问题。结合上述统一数学模型和遗传算法,给出了求解离散型结构拓扑优化问题的优化方法。算例结果表明,采用该文提出的拓扑优化方法可有效、方便地对桁架结构、框架结构等离散型结构进行拓扑优化设计。     

动载荷激励下板壳结构加筋自适应成长方法

自适应成长法是基于自然界分支系统形态形成机理的一种高效结构拓扑优化设计方法。通过引入等效静态载荷法理论,运用自适应成长法解决板壳加筋结构在承受动载荷激励下的动态响应拓扑优化设计问题。根据板壳结构所受的动载荷边界条件,构建以动柔度为目标的优化数学模型,推导迭代公式,使板壳结构的加强筋从"种子"开始,沿着使结构最佳力学性能方向成长,从而形成最优加强筋分布形态。研究在简谐载荷和冲击载荷作用下的板壳结构加强筋设计例,并与静态载荷作用下的设计结果进行比较。研究结果表明,板壳结构在动态载荷作用下,其主加强筋布局形态和在静态载荷作用下相同,但在靠近载荷作用点附近出现与主加强筋平行的截面积较小的加强筋,以增加抵抗动态载荷的作用;而冲击载荷作用下的加强筋与一般简谐载荷作用下的加强筋相比,多出一层较复杂的框型筋板抵抗瞬时冲击力。     

Robust topology optimization under multiple independent uncertainties of loading positions

The topology optimization problem of a continuum structure is further investigated under the independent position uncertainties of multiple external loads, which are now described with an interval vector of uncertain-but-bounded variables. In this study, the structural compliance is formulated with the quadratic Taylor series expansion of multiple loading positions. As a result, the objective gradient information to the topological variables can be evaluated efficiently upon an explicit quadratic expression as the loads deviate from their ideal application points. Based on the minimum (largest absolute) value of design sensitivities, which corresponds to the most sensitive compliance to the load position variations, a two-level optimization algorithm within the non-probabilistic approach is developed upon a gradient-based optimization method. The proposed framework is then performed to achieve the robust optimal configurations of four benchmark examples, and the final designs are compared comprehensively with the traditional topology optimizations under the loading point fixation. It will be observed that the present methodology can provide a remarkably different structural layout with the auxiliary components in the design domain to counteract the load position uncertainties. The numerical results also show that the present robust topology optimization can effectively prevent the structural performance from a noticeable deterioration than the deterministic optimization in the presence of load position disturbances.     

Bi-directional evolutionary structural optimization for design-dependent fluid pressure loading problems

This article presents an evolutionary topology optimization method for compliance minimization of structures under design-dependent pressure loads. In traditional density based topology optimization methods, intermediate values of densities for the solid elements arise along the iterations. Extra boundary parametrization schemes are demanded when these methods are applied to pressure loading problems. An alternative methodology is suggested in this article for handling this type of load. With an extended bi-directional evolutionary structural optimization method associated with a partially coupled fluid–structure formulation, pressure loads are modelled with hydrostatic fluid finite elements. Due to the discrete nature of the method, the problem is solved without any need of pressure load surfaces parametrization. Furthermore, the introduction of a separate fluid domain allows the algorithm to model non-constant pressure fields with Laplace's equation. Three benchmark examples are explored in order to show the achievements of the proposed method.     

拓扑相关荷载作用下结构拓扑优化的水平集方法

发展了一种利用水平集演化技术求解拓扑相关荷载作用下结构拓扑优化问题的数值方法。通过引入水平集函数,我们以隐含的方式对结构的拓扑和形状作了描述,从而把拓扑优化问题转化为了寻求最优水平集函数的数学规划问题。利用基于连续体概念的灵敏度分析技术,构造了用于驱动水平集演化的速度场。由于结构的边界可以用零水平集加以描述,因此利用适当的数学变换,我们可以方便地处理施加在结构上的拓扑相关荷载,这样就避免了以往算法中繁复的边界提取工作以及为了处理拓扑相关荷载所采取的特殊技巧。文末的数值算例表明了提出的优化方法在处理此类问题时所具有的独到的优越性。     

An efficient approach for reliability-based topology optimization

This article presents an efficient approach for reliability-based topology optimization (RBTO) in which the computational effort involved in solving the RBTO problem is equivalent to that of solving a deterministic topology optimization (DTO) problem. The methodology presented is built upon the bidirectional evolutionary structural optimization (BESO) method used for solving the deterministic optimization problem. The proposed method is suitable for linear elastic problems with independent and normally distributed loads, subjected to deflection and reliability constraints. The linear relationship between the deflection and stiffness matrices along with the principle of superposition are exploited to handle reliability constraints to develop an efficient algorithm for solving RBTO problems. Four example problems with various random variables and single or multiple applied loads are presented to demonstrate the applicability of the proposed approach in solving RBTO problems. The major contribution of this article comes from the improved efficiency of the proposed algorithm when measured in terms of the computational effort involved in the finite element analysis runs required to compute the optimum solution. For the examples presented with a single applied load, it is shown that the CPU time required in computing the optimum solution for the RBTO problem is 15–30% less than the time required to solve the DTO problems. The improved computational efficiency allows for incorporation of reliability considerations in topology optimization without an increase in the computational time needed to solve the DTO problem.     

索形优化后的双向张弦梁索力静载试验设计与研究

基于平衡荷载值确定双向张弦实腹梁结构的形状,设计了一个索形优化后的双向张弦梁整体结构索力静载试验。用万向节模拟撑杆与上弦钢梁节点,用特制花篮螺丝和改装的U型绳卡模拟拉索张拉端和锚固端,采用多点分配梁杠杆集中加载与跨中直接吊挂加载相结合的加载方案。试验结果显示,经过索网形状优化之后,竖向荷载增大到设计平衡荷载值时,双向各索索力值相近,分布均匀,明显改善受荷阶段结构中的索力分布。双向张弦梁下弦索对非对称活载尤其是二分之一跨分布形式较为敏感,可能出现边跨索力超过同级全跨荷载下的现象。     

Structural shape optimization using equivalent static loads transformed from dynamic loads

In structural optimization, static loads are generally utilized although real external forces are dynamic. Dynamic loads have been considered only in small‐scale problems. Recently, an algorithm for dynamic response optimization using transformation of dynamic loads into equivalent static loads has been proposed. The transformation is conducted to match the displacement fields from dynamic and static analyses. This algorithm can be applied to large‐scale problems. However, the application has been limited to size optimization. The present study applies the algorithm to shape optimization. Because the number of degrees of freedom of finite element models is usually very large in shape optimization, it is difficult to conduct dynamic response optimization with conventional methods that directly treat dynamic response in the time domain. The optimization process is carried out by interfacing an optimization system and an analysis system for structural dynamics. Various examples are solved to verify the algorithm. The results are compared to the results from static loads. It is found that the algorithm using static loads transformed from dynamic loads based on displacement is valid for very large‐scale shape optimization problems. Copyright © 2005 John Wiley & Sons, Ltd.     

Bidirectional evolutionary structural optimization for nonlinear structures under dynamic loads

This study aims to develop efficient numerical optimization methods for finding the optimal topology of nonlinear structures under dynamic loads. The numerical models are developed using the bidirectional evolutionary structural optimization method for stiffness maximization problems with mass constraints. The mathematical formulation of topology optimization approach is developed based on the element virtual strain energy as the design variable and minimization of compliance as the objective function. The suitability of the proposed method for topology optimization of nonlinear structures is demonstrated through a series of two- and three-dimensional benchmark designs. Several issues relating to the nonlinear structures subjected to dynamic loads such as material, geometric, and contact nonlinearities are addressed in the examples. It is shown that the proposed approach generates more reliable designs for nonlinear structures.