Adaptive isogeometric topology optimization of shell structures based on PHT-splines

被引:0
|
作者
Wen, Zepeng [1 ]
Pan, Qiong [2 ]
Zhai, Xiaoya [2 ]
Kang, Hongmei [1 ]
Chen, Falai [2 ]
机构
[1] Soochow Univ, Sch Math Sci, 1 Rd Shizi, Suzhou 215006, Jiangsu, Peoples R China
[2] Univ Sci & Technol China, Sch Math Sci, 96 Rd jinzhai, Hefei 230026, Anhui, Peoples R China
基金
中国国家自然科学基金;
关键词
Shell structures; Isogeometric topology optimization; Adaptive topology optimization; PHT-splines; SIMULTANEOUS SHAPE; GEOMETRY; NURBS;
D O I
10.1016/j.compstruc.2024.107565
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper proposes an adaptive isogeometric topology optimization framework for shell structures by utilizing a continuous density field represented as Polynomial splines over Hierarchical T-meshes (PHT-splines). This framework ensures an exact representation of shell structures, eliminating the geometric inaccuracies commonly associated with topology optimization. In the meanwhile, the meshes used for design and analysis are refined adaptively and locally along the density boundary to achieve a smooth material layout with reduced degrees of freedom (DOF). The adaptive sensitivity filter is tailored to the characteristics of PHT-splines, where the filter radius is determined automatically and adaptively, without the need to specify parameters in advance. Numerical experiments conducted on various shell structures validate the efficacy of the proposed adaptive framework. In comparison with isogeometric topology optimization based on non-adaptive cases (i.e. B-splines), the proposed adaptive framework demonstrates a notable enhancement in computational efficiency, with a 50% - 80% reduction in running time and a 30% - 60% reduction in DOF. Additionally, we offer a detailed comparison between PHT-splines and other locally refinable splines in the context of shell topology optimization. Numerical experiments exhibit that the efficient and localized refinement capability of PHT-splines provides advantages in both computational efficiency and structural performance for topology optimization.
引用
收藏
页数:18
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