基于蚁群算法的桁架结构布局离散变量优化方法

提出的布局优化方法是将桁架结构的截面变量、拓扑变量及形状变量统一为离散变量.将离散变量转化为适应于蚁群算法求解TSP问题的离散变量,应用MATLAB语言编写求解桁架结构布局优化程序,最终实现对问题的分析与求解.通过对几个经典的平面、空间桁架结构布局优化算例的验算表明:本文设计的基于蚁群算法的桁架结构布局离散变量优化方法较单独处理截面优化、拓扑优化及形状优化问题具有更大的效益,相对于其他布局优化方法也展现出更好的优化效果.“基于蚁群算法的桁架结构布局离散变量优化方法”在程序设计、求解速度、求解空间及其方法通用性等方面都表现出良好的性能,并且简单、实用,适应于实际工程应用.     

基于类桁架连续体的结构拓扑优化方法与应用

以各向异性连续体为基结构,采用类桁架连续体材料模型进行结构拓扑优化。以材料在结点位置的密度和方向作为优化设计变量,使材料在设计域内连续分布。并以此建立材料的弹性矩阵和刚度矩阵。优化过程没有抑制中间密度,这从根本上避免了许多拓扑优化方法普遍存在的单元铰接、棋盘格现象以及单元依赖性等数值不稳定问题。采用满应力准则法,借助有限元结构分析,经过少量迭代,建立优化的材料连续分布场,即类桁架连续体结构。由于首先建立的拓扑优化结构是各向异性连续体,从而得到更大优化空间。然后可以结合工程实际需要将其转化为离散的拓扑优化杆系结构。最后,以1个经典Michell桁架和3种形式的拱桥为数值算例,演示了其结构拓扑优化过程。     

基于NURBS插值的三维渐进结构优化方法

提出一种基于等几何控制点密度变量的三维双向渐进结构拓扑优化方法。在当前列式下,高阶NURBS基函数被同时用于CAD模型中NURBS实体片的几何场、位移场和温度场以及密度场插值,实现了几何模型、分析模型和优化模型的有效统一,确保了位移场、温度场及密度场的高阶连续性;详细推导了基于等几何控制点密度变量的三维渐进结构法模型及其灵敏度分析列式;最后几个典型的数值算例,包括最小柔顺性、热传导优化问题及三维结构自由振动的基频最大化问题,验证了本文方法的有效性。     

Discrete and non-local elastica

In this paper, the buckling and post-buckling behavior of an elastic lattice system referred to as the discrete elastica problem is investigated using an equivalent non-local continuum approach. The geometrically exact post-buckling analysis of the elastic chain, also called Hencky system, is first numerically solved using the shooting method. This discrete physical model is also mathematically equivalent to a finite difference formulation of the continuum elastica. Starting from the exact difference equations of the discrete problem, a continualization method is applied for approximating the difference operators by differential ones, in order to better characterize the discrete system by an enriched continuous one. It is shown that the new continuum associated with the discrete system exactly fits the discrete elastica post-buckling problem, where the non-locality is of Eringen׳s type (also called stress gradient non-local model). An asymptotic expansion is performed for both the discrete and the non-local continuum models, in order to approximate the post-buckling branches of the discrete system. Some numerical investigations show the efficiency of the non-local approach, especially for capturing the scale effects inherent to the cell size of the lattice model.     

Parameter identification for a damage phase field model using a physics-informed neural network

This work applies concepts of artificial neural networks to identify the parameters of a mathematical model based on phase fields for damage and fracture. Damage mechanics is the part of the continuum mechanics that models the effects of micro-defect formation using state variables at the macroscopic level. The equations that define the model are derived from fundamental laws of physics and provide important relationships among state variables. Simulations using the model considered in this work produce good qualitative and quantitative results, but many parameters must be adjusted to reproduce certain material behavior. The identification of model parameters is considered by solving an inverse problem that uses pseudo-experimental data to find the best values that fit the data. We apply physics informed neural network and combine some classical estimation methods to identify the material parameters that appear in the damage equation of the model. Our strategy consists of a neural network that acts as an approximating function of the damage evolution with output regularized using the residue of the differential equation. Three stages of optimization seek the best possible values for the neural network and the material parameters. The training alternates between the fitting of only the pseudo-experimental data or the total loss that includes the regularizing terms. We test the robustness of the method to noisy data and its generalization capabilities using a simple physical case for the damage model. This procedure deals better with noisy data in comparison with a more standard PDE-constrained optimization method, and it also provides good approximations of the material parameters and the evolution of damage.     

连续体结构破损-安全拓扑优化预估失效区域的理性准则

本文指出，连续体结构拓扑优化研究方向，从2016年Zhou的研究开始，进入了一个新阶段：离散结构的设计继续从连续体拓扑优化的结果获益，同时连续体拓扑优化的理论可以从离散结构的拓扑优化中受益。借此新阶段，本文针对连续体结构破损-安全的拓扑优化问题，通过几何分析途径，建立了预估破损区域的理性准则，即给出了结构局部破损模式尺寸上、下限及相邻局部破损区域的间距上、下限。以此理性准则，分析了Janson及Zhou给出的破损区域预估分布策略的各自优缺点，并通过算例对于相关策略进行了验证。结果表明：Janson的策略过于保守而导致不必要的极大计算量；Zhou的无缝平铺的策略不能保证所有拓扑生成离散元件通过破损测试，但在多数情况下仍可以得到具有足够冗余的最优拓扑；本文提出的以满足理性准则的方式布置破损区域，可以保证所有拓扑生成离散元件通过破损测试，并保证得到更多冗余的最优拓扑。本文的研究表明，预估破损区域的理性准则条件，为连续体结构破损-安全拓扑优化问题，提供了表述局部破损区域的理论进展。     

带有预应力的连续体组合结构拓扑优化

考虑梁结构的预应力，导出了结构的应力及其灵敏度公式。同时，结合结构单元应力水平和相对差商，对于带有尺寸和拓扑变量的连续体组合结构优化问题，建立了一套优化准则，在双方向渐进结构优化方法思想的基础上，形成了一种新的拓扑优化算法。最后，算例表明了该方法的正确性和有效性。