Open Access

ARTICLE

Topology Optimization of Lattice Structures through Data-Driven Model of M-VCUT Level Set Based Substructure

Minjie Shao, Tielin Shi, Qi Xia^*, Shiyuan Liu^*

School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China

* Corresponding Authors: Qi Xia. Email: ; Shiyuan Liu. Email:

Computer Modeling in Engineering & Sciences 2025, 144(3), 2685-2703. https://doi.org/10.32604/cmes.2025.068078

Received 20 May 2025; Accepted 18 July 2025; Issue published 30 September 2025

Abstract

A data-driven model of multiple variable cutting (M-VCUT) level set-based substructure is proposed for the topology optimization of lattice structures. The M-VCUT level set method is used to represent substructures, enriching their diversity of configuration while ensuring connectivity. To construct the data-driven model of substructure, a database is prepared by sampling the space of substructures spanned by several substructure prototypes. Then, for each substructure in this database, the stiffness matrix is condensed so that its degrees of freedom are reduced. Thereafter, the data-driven model of substructures is constructed through interpolation with compactly supported radial basis function (CS-RBF). The inputs of the data-driven model are the design variables of topology optimization, and the outputs are the condensed stiffness matrix and volume of substructures. During the optimization, this data-driven model is used, thus avoiding repeated static condensation that would require much computation time. Several numerical examples are provided to verify the proposed method.

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Keywords

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