Mixed-variable topology optimization for shell-infill structures with adaptive coating thickness

• Published in: Computer aided design Vol. 189; p. 103943
• Main Authors: Gao, Junfeng, Yang, Zihao, Liang, Yuan, Zhang, Yongcun, Liu, Kangjie
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.12.2025
• Subjects: Coated structures; Mixed-variable topology optimization; Non-uniform coating thickness; Shell-infill structures; Coated structures; Shell-infill structures; Mixed-variable topology optimization; Non-uniform coating thickness
• ISSN: 0010-4485
• DOI: 10.1016/j.cad.2025.103943

•A mixed-variable topology optimization method is proposed to design the base topology and adaptive coating thickness of shell-infill structures.•Discrete variable optimization is used to determine the structure's topology with a uniform coating thickness and a clear coating interface in each iteration.•Coating optimization is achieved through density-based topology optimization, incorporating a novel holeless coating constraint via a virtual temperature field.•The method achieves over 10 % mass reduction compared to uniform coating structures and shows effectiveness and scalability in numerical examples, including a large-scale 3D case. Inspired by natural shell-infill systems with spatially adaptive coating thicknesses (e.g., human femur bones), this paper proposes a mixed-variable topology optimization method for collaboratively designing the base topology and the adaptive coating thickness distribution of shell-infill structures. The optimization framework consists of two coupled levels. At the first level, a discrete-variable topology optimization method is employed to generate a base structure (shell and infill) with uniform coating thickness, effectively eliminating intermediate density elements to ensure a clear material interface for coating identification. At the second level, the coating size optimization is realized through density-based topology optimization combined with a novel holeless coating constraint based on a virtual temperature field. Meanwhile, to ensure manufacturability, a minimum coating thickness constraint is introduced. A density field mapping strategy further couples the two optimization levels, enabling iterative updates of both the base topology and coating thickness distribution. Three numerical examples demonstrate the effectiveness of the proposed method. The shell-infill structure with adaptive coating thickness achieves over 10 % mass reduction. Additionally, the constraints successfully eliminate unmanufacturable holes while preserving thickness continuity. Moreover, a large-scale 3D case validates the capability of the method for handling complex three-dimensional coating problems. The results highlight the potential of the method in designing bio-inspired, high-performance shell-infill structures.