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Optimization design of variable density lattice structure for additive manufacturing

Author

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  • Zhang, Xinju
  • Xue, Zhanpu
  • Cheng, Quntao
  • Ji, Yunguang

Abstract

Lattice material is a kind of super light and high strength porous material with high performance. At present, it is mainly composed of lattice structure with equal density components. In practice, each part of the lattice structure bears different loads, so the performance of the lattice structure with equal density can not be brought into full play. In view of the above problems, topology optimization was used to the process of lattice structure design to the optimal design of variable density lattice structure. According to the actual load, the optimal variable density lattice structure is designed to achieve the optimal performance. In the process of optimization, the most important design parameters are grid structure, grid filling ratio and mass constraint percentage. Taking aviation rocker arm as an example, orthogonal experiment is used to get the optimal optimization parameters, which makes the lightweight effect of rocker arm better. The numerical results show that by simulating nine groups of orthogonal experiments and integrating the factors of stress, strain and weight reduction, a lattice structure is finally selected. Compared with the original model, the strain is reduced by 14%, the stress is reduced by 68% and the weight is reduced by 23%. The rocker arm is processed and manufactured by adding material manufacturing technology, which solves the weight reduction optimization problem of aviation parts rocker arm.

Suggested Citation

  • Zhang, Xinju & Xue, Zhanpu & Cheng, Quntao & Ji, Yunguang, 2022. "Optimization design of variable density lattice structure for additive manufacturing," Energy, Elsevier, vol. 242(C).
  • Handle: RePEc:eee:energy:v:242:y:2022:i:c:s0360544221028036
    DOI: 10.1016/j.energy.2021.122554
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    Cited by:

    1. Liu, Yaru & Wang, Lei & Ng, Bing Feng, 2024. "A hybrid model-data-driven framework for inverse load identification of interval structures based on physics-informed neural network and improved Kalman filter algorithm," Applied Energy, Elsevier, vol. 359(C).

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