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Three-dimensional shell-porous structures are extensively utilized in aerospace, advanced manufacturing, and biomedical engineering due to their outstanding mechanical properties and lightweight characteristics. This paper presents a topology optimization framework for three-dimensional shell-graded porous structures, which integrates Triply Periodic Minimal Surfaces (TPMS) and the Moving Morphable Void (MMV) method, complemented by Problem-Independent Machine Learning (PIML) to enhance optimization efficiency. The MMV method is used to explicitly define the macroscopic topology, facilitating the direct generation of shell structures with well-defined boundaries and eliminating the need for post-processing. A Partitioned Coordinate Mapping (PCM) mechanism is introduced, employing TPMS functions to construct the spatially graded infill structure, while smooth geometric transitions between adjacent microstructures are ensured through the high-order continuity of Non-Uniform Rational B-Splines (NURBS) basis functions. To overcome computational challenges associated with full-scale analysis of complex lattice structures, a PIML framework is employed to accelerate the structural optimization process. A numerical example is given to validate the effectiveness of the proposed method.

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Design of 3D Shell-Graded Infill Structures Based on Moving Morphable Void and Triply Periodic Minimal Surfaces

  • 会议论文

  • 发表日期：

    2026年

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  • Xianglong Cao,
  • Wu Xu,
  • Shixin Zhao,
  • Yilin Guo,
  • Chang Liu,
  • Xu Guo

摘要

Three-dimensional shell-porous structures are extensively utilized in aerospace, advanced manufacturing, and biomedical engineering due to their outstanding mechanical properties and lightweight characteristics. This paper presents a topology optimization framework for three-dimensional shell-graded porous structures, which integrates Triply Periodic Minimal Surfaces (TPMS) and the Moving Morphable Void (MMV) method, complemented by Problem-Independent Machine Learning (PIML) to enhance optimization efficiency. The MMV method is used to explicitly define the macroscopic topology, facilitating the direct generation of shell structures with well-defined boundaries and eliminating the need for post-processing. A Partitioned Coordinate Mapping (PCM) mechanism is introduced, employing TPMS functions to construct the spatially graded infill structure, while smooth geometric transitions between adjacent microstructures are ensured through the high-order continuity of Non-Uniform Rational B-Splines (NURBS) basis functions. To overcome computational challenges associated with full-scale analysis of complex lattice structures, a PIML framework is employed to accelerate the structural optimization process. A numerical example is given to validate the effectiveness of the proposed method.