Stress-driven generative design and numerical assessment of customized additive manufactured lattice structures

Fuyuan Liu, Min Chen*, Sanli Liu, Zhouyi Xiang, Songhua Huang, Eng Gee Lim, Shunqi Zhang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

The rise of additive manufacturing (AM) has positioned lattice infilling as a pivotal strategy for creating lightweight, customized engineering components. This study presents a generative method that enables the conformal design and stiffness prediction of complex gradient strut-node lattice structures. A stress-driven Multi-Agent System (MAS) is introduced for the parametric optimization of lattice material distribution, incorporating geometric limitations, stress factors, and AM constraints. A beam element model simplifies the numerical analysis of the structure linear stiffness. By applying the Response Surface Method (RSM), a numerical model is established, not only conducting a quantitative analysis on the sensitivity of MAS design variables but predicting mechanical performance. This method is validated by designing a supporting component, demonstrating that the optimized lattice design can achieve a linear stiffness 1.4 times greater than that of conventional uniform lattice infills for the same mass. This research provides a comprehensive framework for the efficient design and analysis of irregular lattice structures at a macroscopic scale.

Original languageEnglish
Article number112956
JournalMaterials and Design
Volume241
DOIs
Publication statusPublished - May 2024

Keywords

  • Design for additive manufacturing
  • Gradient lattice structure
  • Multi-agent system
  • Stress-driven lattice infilling

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