topology description function
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2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Ruichao Lian ◽  
Shikai Jing ◽  
Zefang Shi ◽  
Zhijun He ◽  
Guohua Song

In the structural topology optimization approaches, the Moving Morphable Component (MMC) is a new method to obtain the optimized structural topologies by optimizing shapes, sizes, and locations of components. However, the optimized structure boundary usually generates local nonsmooth areas due to incomplete connection between components. In the present paper, a topology optimization approach considering nonsmooth structural boundaries in the intersection areas of the components based on the MMC is proposed. The variability of components’ shape can be obtained by constructing the topology description function (TDF) with multiple thickness and length variables. The shape of components can be modified according to the structural responses during the optimization process, and the relatively smooth structural boundaries are generated in the intersection areas of the components. To reduce the impact of the initial layout on the rate of convergence, this method is implemented in a hierarchical variable calling strategy. Compared with the original MMC method, the advantage of the proposed approach is that the smoothness of the structural boundaries can be effectively improved and the geometric modeling ability can be enhanced in a concise way. The effectiveness of the proposed method is demonstrated for topology optimization of the minimum compliance problem and compliant mechanisms.


2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Xingfa Yang ◽  
Jie Liu ◽  
Yin Yang ◽  
Qixiang Qing ◽  
Guilin Wen

Optimal geometries extracted from traditional element-based topology optimization outcomes usually have zigzag boundaries, leading to being difficult to fabricate. In this study, a fairly accurate and efficient topology description function method (TDFM) for topology optimization of linear elastic structures is developed. By employing the modified sigmoid function, a simple yet efficient strategy is presented to tackle the computational difficulties because of the nonsmoothness of Heaviside function in topology optimization problem. The optimization problem is to minimize the structural compliance, with highest stiffness, while satisfying the volume constraint. The design problem is solved by a Sequential Linear Programming method. Convergent, crisp, and smooth final layouts are obtained, which can be fabricated without postprocessing, demonstrated by a series of numerical examples. Further, the proposed method has a rather higher accuracy and efficiency compared with traditional TDFM, when the classical topology optimization methods, such as bidirectional evolutionary structural optimization (BESO) and solid isotropic material with penalization (SIMP) method, are taken as benchmark.


Author(s):  
Xu Guo ◽  
Kang Zhao ◽  
Michael Yu Wang

In the present paper, a new approach for structural topology optimization based on implicit topology description function (TDF) is proposed. TDF is used to describe the shape/topology of a structure, which is approximated in terms of the nodal values. Then a relationship is established between the element stiffness and the values of the topology description function on its four nodes. In this way and with some non-local treatments of the design sensitivities, not only the shape derivative but also the topological derivative of the optimal design can be incorporated in the numerical algorithm in a unified way. Numerical experiments demonstrate that by employing this approach, the computational efforts associated with TDF (and level set) based algorithms can be saved. Clear optimal topologies and smooth structural boundaries free from any sign of numerical instability can be obtained simultaneously and efficiently.


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