Topology optimization of the vibrating structure for fused deposition modelling of parts considering a hybrid deposition path pattern

ABSTRACT

Frequency optimization plays a vital role in designing machines and structures to avoid destructive responses caused by external excitation. In the current study, most frequency optimization research focuses on algorithm innovation to pursue better numerical results. However, with the development of additive manufacturing, increasingly more organic structures produced by topology optimization can be physically fabricated. Therefore, the combination of topology optimization and additive manufacturing is promising and widely investigated. This paper proposes a concurrent topology optimization method for maximizing the natural frequency of Fused Deposition Modelling (FDM) parts printed by a Hybrid Deposition Path (HDP) pattern. The proposed algorithm concurrently optimizes the shape of the structure and the raster directions of the substrate domain, wherein the method of solid orthotropic materials with penalization (SOMP) with double layers of smoothing and projection (DSP) is adopted. A dedicated sensitivity analysis is performed on both the topology and direction variables. Several numerical results are studied to show the effectiveness of the proposed method is efficient and to disclose the influence of raster direction on the vibration model. This work would be instructive to design for FDM printing.

KEYWORDS:

• Frequency optimization
• additive manufacturing
• fused deposition modeling
• hybrid deposition path pattern

Acknowledgments

This work has been a joint effort between Southern University of Science and Technology (SUSTech) and the University of Alberta (UA). The first author, Yifan, had graduated from SUSTech and was recruited by Dr. Ma in 2020, while for family reasons, in 2021, he retired from UA and joined SUSTech. There had been close collaboration between Drs. Ahmad and Ma, over the past years when they were colleagues, and they committed to continue the working mechanism through an international collaboration project which is to be sponsored by Guangdong province, China. We acknowledge that Dr. Jikai Liu from Shandong University had provided great assistance for concept validation and algorithm development for this work; his collaboration with UA team has been ongoing for the past years.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the China Scholarship Council under Grant CSC 202008440546.