Stress-constrained shell-lattice infill structural optimisation for additive manufacturing

ABSTRACT

This paper presents a numerical study on stress-constrained shell-lattice infill structural optimisation. This problem is inherently challenging for several reasons: (i) different stress measures have to be used for the solid shell and the porous lattice infill, and the two types of stress constraints make the problem extremely complex to solve and (ii) involvement of the shell layer further complicates the optimisation problem modelling and its solution. To address these challenges, two stress constraints were formulated, i.e. a von Mises stress-based constraint for the solid shell layer and a Tsai-Hill yield criteria-based constraint for the porous lattice. Then, level set function is adopted to represent the shape of the shell layer and the constant-thickness shell layer is modelled based on the signed distance feature. Then, a comprehensive and accurate sensitivity result is derived to guide the concurrent structural shape and lattice density optimisation. A few numerical examples will be studied to prove the effectiveness of the developed algorithm. Some interesting phenomena have been observed, such as the soft narrow band at the shell-lattice interface to mitigate stress concentration.

KEYWORDS:

• Stress constraint
• shell-lattice infill
• structural optimisation
• additive manufacturing

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Huangchao Yu received his Ph.D. degree in Mechanical Engineering from the University of Alberta, Canada in 2017. He is currently working as an assistant professor at National University of Defense Technology. His research interests include mechanics and dynamics, optimisation, intelligent design and control of unmanned systems.

Jiaqi Huang received his Bachelor degree in Jilin University, Changchun, China in 2013. He is currently pursuing the Ph.D. degree in Shandong University. His research interests include topology optimisation and additive manufacturing.

Bin Zou is a Professor at School of Mechanical Engineering of Shandong University. He received his Ph.D. degree from the same university. His research interests include 3D printing, precision machining, and robotic machining.

Wen Shao is a lecture at College of Mechanical and Electrical Engineering of Central South University. He received his PhD degree from the University of Queensland, Australia in 2016. His main research is focused on precision machining/non-traditional machining/advanced manufacturing and anti-fatigue manufacturing.

Jikai Liu is a Professor at School of Mechanical Engineering of Shandong University. He received his PhD degree from University of Alberta, Canada, and used to work as a Postdoctoral Research Associate at the ANSYS Additive Manufacturing Research Laboratory at University of Pittsburgh, USA. His main research is focused on topology optimisation and additive manufacturing.

Additional information

Funding

The authors would like to acknowledge the support from the Qilu Young Scholar award, Shandong University. This research is supported by Key Laboratory of High-efficiency and Clean Mechanical Manufacture at Shandong University, Ministry of Education.