基于ICM法的传热结构周期性拓扑优化设计

为了获得复合材料稳态导热性优化微结构构型,基于独立连续映射法,建立了周期性结构拓扑优化模型。在优化模型中,以重量最小化为目标、散热弱度为约束。采用一阶泰勒展开近似表达散热弱度约束函数。基于偏微分方程实施的图像过滤方法消除了棋盘格现象和网格依赖性问题。为了满足周期性约束,设计区域划分为若干相同大小的子区域,散热弱度贡献系数被重新分配。对比分析循环周期数、不同约束载荷工况下的拓扑优化构型。数值算例结果验证提出方法可以有效实现热传导下的复合材料微结构优化设计。     

零泊松比超材料设计的多评价点功能基元拓扑优化方法

提出基于多评价点约束的零泊松比超材料功能基元拓扑优化设计方法。在同一功能基元拓扑基结构中,通过建立对于多个评价点的正、负泊松比约束,实现胞元零泊松比效应。分别采用最小质量和最大柔度目标函数拓扑优化模型优化设计出与半内六角蜂窝相似的零泊松比功能基元最优拓扑构型。提取功能基元最优构型并周期性序构了零泊松比超材料试件,通过有限元方法验证了该功能基元的零泊松比效应,并分析超材料试件的静、动力学特性。计算结果表明,最大柔度目标函数设计的功能基元构型的泊松比更接近于零,且具有更好的承载与隔振性能。设计了零泊松比超材料环肋双层圆柱壳结构,进行外壳静压和内部设备激振下壳体水下辐射噪声分析。研究表明,零泊松比超材料环肋可将外壳压缩变形转换为内外壳间环肋旋转,实现耐压壳内壳的保形,且具有较好的降噪性能。      

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。     

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。     

考虑载荷不确定性的多材料结构稳健拓扑优化

传统的拓扑优化设计通常基于单材料与确定性条件,往往难以兼顾结构性能的稳健性。针对实际工程中载荷不确定性问题,研究多材料结构稳健拓扑优化设计方法。基于有序各向同性微结构材料惩罚模型法(Ordered-Solid Isotropic Microstructures with Penalization, Ordered-SIMP),进行多材料插值模型表征。构建载荷概率分布条件下结构柔度均值与标准差的加权目标函数,辅以体积约束。针对载荷满足随机场分布时,采用Karhunen-Loève展开将载荷随机场变换为有限个不相关的载荷随机变量加权和,并借助稀疏网格数值积分方法,将多材料结构稳健拓扑优化转化为求解一组多工况加权多目标确定性拓扑优化设计问题。通过数值算例验证所提方法的有效性与优化结果的稳健性。结果表明:针对不同材料组合方案,均能有效获得良好的多材料拓扑构型;与确定性设计相比较,稳健设计具有不同的材料布局方案,且结构性能更加稳定。     

任意负泊松比超材料结构设计的功能基元拓扑优化法

基于拓扑优化方法,提出了设计具有任意负泊松比超材料及结构的功能基元拓扑优化法。针对功能基元的不同初始拓扑基结构,包括矩形和三角形初始拓扑基结构,以指定的负泊松比值作为约束条件,以功能基元柔顺度最大化为目标函数,建立了任意负泊松比超材料拓扑优化模型并求解。提取拓扑优化得到的功能基元最优构型,经周期性分布从而形成负泊松比结构。建立优化得到的超材料结构有限元模型,验算了功能基元的泊松比,计算分析了该超材料试件的静、动力学特性。结果表明,该负泊松比效应超材料试件具有较好的承载能力,且在中低频段有较好的减振效果。     

考虑泊松效应的材料/结构一体化设计方法

为实现含有不同泊松比组分复合材料的优化设计,并考虑宏观结构及复杂的边界条件,提出了考虑泊松效应的材料/结构一体化设计方法,其显著特征在于不同组分材料中引入了泊松比插值,假设宏观结构由周期性排列的复合材料组成,复合材料含两种各向同性且泊松比不同的组分材料,以静态问题中柔顺度最小化或动态问题中特征值最大化为目标以及宏微观体积比为约束建立了拓扑优化模型。采用均匀化理论预测了复合材料等效性能,推导了目标函数对宏微观密度变量的敏度表达式。分别采用密度过滤和敏度过滤来消除宏微观拓扑优化中的不稳定性现象。采用优化准则法分别更新宏观、微观密度变量,考察了微观体积比和组分材料泊松比参数对优化结果的影响。三维数值算例结果表明所提出的一体化方法具有可行性和优越性。     

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。     

双尺度分级结构时域动刚度问题的并行拓扑优化

提出双尺度分级结构时域动刚度问题的并行拓扑优化方法，实现结构宏观拓扑构型和材料微观分布协同优化。利用三场密度方法实施宏观与微观结构的设计，基于能量的均匀化方法(energy-based homogenization method, EBHM)在微观结构上计算等效的宏观力学特性。针对比例阻尼系统，将HHT-α方法作为时间积分算法，求解多尺度结构的动力学有限元模型。融合先离散-后微分方法与伴随方法，在时间与空间离散的拓扑优化模型上实施敏度分析，避免了将时间作为连续变量而导致的灵敏度计算的一致性误差问题。以多尺度结构的动柔度最小化为目标，宏观与微观结构体积为约束，分别求解了正弦半波和余弦半波冲击载荷作用下多尺度结构的并行拓扑优化问题。最后，通过2种典型算例的数值结果验证了所提算法的有效性。     

基于多分辨率-多边形单元建模策略的多材料结构动刚度拓扑优化方法

利用多边形有限单元的高精度求解优势,融合多分辨率拓扑优化方法,实现粗糙位移网格条件下的高分辨率构型设计,由此提出多材料结构动刚度问题的拓扑优化方法。将多边形单元(位移场求解单元)劈分为精细的小单元,构造设计变量与密度变量的重叠网格,形成多分辨率-多边形单元的优化建模策略;以平均动柔度最小化为目标和多材料的体积占比为约束,建立多材料结构的动力学拓扑优化模型,通过HHT-α方法求解结构动响应,采用伴随变量法推导目标函数和约束的灵敏度表达式,利用基于敏度分离技术的ZPR设计变量更新方案构建多区域体积约束问题的优化迭代格式;通过典型数值算例分析优化方法的可行性和动态载荷作用时间对优化结果的影响机制。     

Conceptual design of efficient heat conductors using multi-material topology optimization

Conductive heat transfer plays an important role in dissipating thermal energy to achieve lower operating temperatures in various devices. Topology optimization has the potential to provide efficient structural solutions for such devices. The traditional topology optimization approach considers a single material. Adding additional materials with unique properties not only can expand the design options but also may improve the structural performance of the final structure. In this work, a multi-resolution topology optimization approach is employed to design multi-material structures for efficient heat dissipation. The implementation blends an efficient multi-resolution approach to obtain high-resolution designs with an alternating active phase algorithm to handle multi-material giving greater design flexibility. It solves the steady-state heat equation using finite element analysis and iteratively minimizes thermal compliance (maximizes conductivity). Several examples are presented to show the efficacy of the numerical implementation, which involves benchmark problems. Results indicate good prospects when quantitatively compared with single-material structures.     

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.     

周期性多孔结构特征值拓扑优化

为了实现尺度关联周期性多孔结构的隔振性能优化,提出一种周期性多孔结构特征值拓扑优化方法.基于子结构动态凝聚方法对多孔结构的刚度和质量矩阵进行缩减,采用局部水平集函数(LLSF)对多孔结构进行几何隐式描述,以最大化前6阶特征值为目标函数,以结构体积分数为约束条件,建立周期性多孔结构特征值拓扑优化模型,采用优化准则法对拓扑...     

Robust topology optimization for periodic structures by combining sensitivity averaging with a semianalytical method

Uncertainty factors play an important role in the design of periodic structures because structures with small periodic design spaces are extremely sensitive to loading uncertainty. Therefore, for the first time, this paper proposes a framework for robust topology optimization (RTO) of periodic structures assuming that load uncertainties follow a Gaussian distribution. In this framework, the expected value and variance of structural compliance can be easily computed using a semianalytical method combined with probability theory, which is important for RTO when uncertain variables follow probabilistic distributions. To obtain optimal topologies, the bidirectional evolutionary structural optimization method is used. Structural periodicity is calculated using a strategy of sensitivity averaging and consistency constraints. To eliminate the influence of numerical units when comparing the optimal results to deterministic and RTO solutions, a generic coefficient of variation is defined as the robust index, which contains both the expected value and variance. The proposed framework is verified through the optimization of both 2D and 3D structures with periodicity. Computational results demonstrate the feasibility and effectiveness of the proposed framework for designing robust periodic structures under loading uncertainties.     

A projection-based method for topology optimization of structures with graded surfaces

Graded surfaces widely exist in natural structures and inspire engineers to apply functionally graded (FG) materials to cover structural surfaces for performance improvement, protection, or other special functionalities. However, how to design such structures with FG surfaces by topology optimization is a quite challenging problem due to the difficulty for determining material properties of structural surfaces with prescribed variation rule. This paper presents a novel projection-based method for topology optimization of this class of FG structures. Firstly, a projection process is proposed for ensuring the material properties of the surfaces vary with a prescribed function. A criterion of determining the values of parameters in projection process is given by a strict theoretical derivation, and then, a new interpolation function is established, which is capable of simultaneously obtaining clear substrate topologies and realizable FG surfaces. Though such structures are actually multimaterial gradient structures, only the design variables of single-material topology optimization problem are needed. In the current research, the classical compliance minimization problem with a mass constraint is considered and the robust formulation is used to control the length scale of substrates. Several 2D and 3D numerical examples illustrate the validity and applicability of the proposed method.     

Topology optimization of thermoelastic structures using level set method

This paper describes the topology optimization of thermoelastic structures, using level set method. The objective is to minimize the mean compliance of a structure with a material volume constraint. In level set method, free boundary of a structure is considered as design variable, and it is implicitly represented via level set model. Objective function of the optimization problem is defined as a function of the shape of a structure. Sensitivity analysis based on continuum model is conducted with respect to the free boundary, which suggests the steepest descent direction. A geometric energy term is introduced to ensure smooth structural boundary. Augmented Lagrangian multiplier method is adopted to enforce volume constraint. Numerical examples are provided for 2D cases, considering design independent temperature distribution.     

Topological design of microstructures of cellular materials for maximum bulk or shear modulus

This paper presents a new approach to designing periodic microstructures of cellular materials. The method is based on the bidirectional evolutionary structural optimization (BESO) technique. The optimization problem is formulated as finding a micro-structural topology with the maximum bulk or shear modulus under a prescribed volume constraint. Using the homogenization theory and finite element analysis within a periodic base cell (PBC), elemental sensitivity numbers are established for gradually removing and adding elements in PBC. Numerical examples in 2D and 3D demonstrate the effectiveness of the proposed method for achieving convergent microstructures of cellular materials with maximum bulk or shear modulus. Some interesting topological patterns have been found for guiding the cellular material design.     

Multiscale Optimization of 3D-Printed Beam-Based Lattice Structures through Elastically Tailored Unit Cells

Herein, a numerical multiscale tool is developed to design 3D periodic lattice structures. The work is motivated by the high design freedom of additive manufacturing technologies, which enable complex multiscale lattice structures to be printed. A finite-element-based free-material optimization method is used to determine the ideal orthotropic material properties of a 3D macrostructure space. Subsequently, a population-based algorithm is established to design optimized microscopic lattice unit cells with the desired structural properties. The design variables are the coordinates of lattice skeleton nodes defined within the 3D lattice unit cell space, and the connectivities between them resulting in a truss skeleton. For the calculation of the mechanical properties of the individual lattice cells, an effective Timoshenko beam-based finite element calculation method is developed. The macroscale structure can be constructed by periodically filling the domain with the customized unit cell representing a metamaterial. The method is demonstrated by 3D beam problems with compliance constraints. These macroscopic demonstrators of the developed lattice structures were also 3D-printed. The benefit regarding the weight-specific structural performance is validated through benchmarking with periodic lattice design solutions using well-known standard lattice cells.     

Lightweight design of bus frames from multi-material topology optimization to cross-sectional size optimization

A comprehensive solution for bus frame design is proposed to bridge multi-material topology optimization and cross-sectional size optimization. Three types of variables (material, topology and size) and two types of constraints (static stiffness and frequencies) are considered to promote this practical design. For multi-material topology optimization, an ordered solid isotropic material with penalization interpolation is used to transform the multi-material selection problem into a pure topology optimization problem, without introducing new design variables. Then, based on the previously optimal topology result, cross-sectional sizes of the bus frame are optimized to further seek the least mass. Sequential linear programming is preferred to solve the two structural optimization problems. Finally, an engineering example verifies the effectiveness of the presented method, which bridges the gap between topology optimization and size optimization, and achieves a more lightweight bus frame than traditional single-material topology optimization.