雷娜

个人信息Personal Information

教授

博士生导师

硕士生导师

主要任职:软件学院(大连理工大学-立命馆大学国际信息与软件学院)党委书记

性别:女

毕业院校:吉林大学

学位:博士

所在单位:软件学院、国际信息与软件学院

学科:软件工程. 计算数学. 计算机应用技术

办公地点:大连理工大学开发区校区信息楼309室

联系方式:nalei@dlut.edu.cn

电子邮箱:nalei@dlut.edu.cn

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Concurrent optimization of structural topology and infill properties with a CBF-based level set method

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论文类型:期刊论文

发表时间:2019-06-01

发表刊物:FRONTIERS OF MECHANICAL ENGINEERING

收录刊物:SCIE

卷号:14

期号:2

页面范围:171-189

ISSN号:2095-0233

关键字:concurrent topology optimization; parametric level set method; cardinal basis function; shell-infill structure design; conformal mapping

摘要:In this paper, a parametric level-set-based topology optimization framework is proposed to concurrently optimize the structural topology at the macroscale and the effective infill properties at the micro/meso scale. The concurrent optimization is achieved by a computational framework combining a new parametric level set approach with mathematical programming. Within the proposed framework, both the structural boundary evolution and the effective infill property optimization can be driven by mathematical programming, which is more advantageous compared with the conventional partial differential equation-driven level set approach. Moreover, the proposed approach will be more efficient in handling nonlinear problems with multiple constraints. Instead of using radial basis functions (RBF), in this paper, we propose to construct a new type of cardinal basis functions (CBF) for the level set function parameterization. The proposed CBF parameterization ensures an explicit impose of the lower and upper bounds of the design variables. This overcomes the intrinsic disadvantage of the conventional RBF-based parametric level set method, where the lower and upper bounds of the design variables oftentimes have to be set by trial and error. A variational distance regularization method is utilized in this research to regularize the level set function to be a desired distanceregularized shape. With the distance information embedded in the level set model, the wrapping boundary layer and the interior infill region can be naturally defined. The isotropic infill achieved via the mesoscale topology optimization is conformally fit into the wrapping boundary layer using the shape-preserving conformal mapping method, which leads to a hierarchical physical structure with optimized overall topology and effective infill properties. The proposed method is expected to provide a timely solution to the increasing demand for multiscale and multifunctional structure design.