Parametric shape and topology optimization: A new level set approach based on cardinal basis functions

• Published in: International journal for numerical methods in engineering Vol. 114; no. 1; pp. 66 - 87
• Main Authors: Jiang, Long, Chen, Shikui, Jiao, Xiangmin
• Format: Journal Article
• Language: English
• Published: Bognor Regis Wiley Subscription Services, Inc 06.04.2018
• Subjects: Basis functions; Boundary representation; cardinal basis function; Collocation methods; Computing time; distance‐regularized evolution; Evolution; Finite element method; Mathematical models; Mathematical programming; Numerical stability; parametric level set method; Radial basis function; Regularization; Robustness (mathematics); Topology optimization; Variations
• ISSN: 0029-5981; 1097-0207
• DOI: 10.1002/nme.5733

Summary The parametric level set approach is an extension of the conventional level set methods for topology optimization. By parameterizing the level set function, level set methods can be directly coupled with mathematical programming to achieve better numerical robustness and computational efficiency. Moreover, the parametric level set scheme can not only inherit the primary advantages of the conventional level set methods, such as clear boundary representation and the flexibility in handling topological changes, but also alleviate some undesired features from the conventional level set methods, such as the need for reinitialization. However, in the existing radial basis function–based parametric level set method, it is difficult to identify the range of the design variables. Besides, the parametric level set evolution often struggles with large fluctuations during the optimization process. Those issues cause difficulties both in numerical stability and in material property mapping. In this paper, a cardinal basis function is constructed based on the radial basis function partition of unity collocation method to parameterize the level set function. The benefit of using cardinal basis function is that the range of the design variables can now be clearly specified as the value of the level set function. A distance regularization energy functional is also introduced, aiming to maintain the desired signed distance property during the level set evolution. With this desired feature, the level set evolution is stabilized against large fluctuations. In addition, the material properties mapped from the level set function to the finite element model can be more accurate.