A Study on Basis Functions of the Parameterized Level Set Method for Topology Optimization of Continuums

2020 ◽  
Vol 143 (4) ◽  
Author(s):  
Peng Wei ◽  
Yang Yang ◽  
Shikui Chen ◽  
Michael Yu Wang

Abstract In recent years, the parameterized level set method (PLSM), which rests on radial basis functions in most early work, has gained growing attention in structural optimization. However, little work has been carried out to investigate the effect of the basis functions in the parameterized level set method. This paper examines the basis functions of the parameterized level set method, including radial basis functions, B-spline functions, and shape functions in the finite element method (FEM) for topology optimization of continuums. The effects of different basis functions in the PLSM are examined by analyzing and comparing the required storage, convergence speed, computational efficiency, and optimization results, with the benchmark minimum compliance problems subject to a volume constraint. The linear basis functions show relatively satisfactory overall performance. Besides, several schemes to boost computational efficiency are proposed. The study on examples with unstructured 2D and 3D meshes can also be considered as a tentative investigation of prospective possible commercial applications of this method.

Author(s):  
Peng Wei ◽  
Michael Yu Wang

In this paper, a parametric structural shape and topology optimization method is presented. To solving structure optimization problems, the level-set method has become a powerful design tool and been widely used in many fields. Combined with the Radial Basis Functions (RBF), which is a popular tool in function approximation, the method of level-set can be represented in a parametric way with a set of advantages comparing with the conventional discrete means. Some numerical examples are presented to illustrate its advantages.


2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Wenhui Zhang ◽  
Yaoting Zhang

The local level set method (LLSM) is higher than the LSMs with global models in computational efficiency, because of the use of narrow-band model. The computational efficiency of the LLSM can be further increased by avoiding the reinitialization procedure by introducing a distance regularized equation (DRE). The numerical stability of the DRE can be ensured by a proposed conditionally stable difference scheme under reverse diffusion constraints. Nevertheless, the proposed method possesses no mechanism to nucleate new holes in the material domain for two-dimensional structures, so that a bidirectional evolutionary algorithm based on discrete level set functions is combined with the LLSM to replace the numerical process of hole nucleation. Numerical examples are given to show high computational efficiency and numerical stability of this algorithm for topology optimization.


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