Generative design of conformal cubic periodic cellular structures using a surrogate model-based optimisation scheme

Cellular structures (CSs) exhibit unique combinations of physical properties, including low weight, high structural strength, and substantial energy absorption, which could be useful in a variety of applications. Further, with the advent of additive manufacturing (AM), CSs are now easier to fabricate. While CSs and AM open up transformative opportunities, their potential for everyday use in industrial practice still lies largely idle. One of the major reasons is the lack of computational tools that allow us to automatically explore, verify, and optimise CSs and skin elements to create an optimised component that meets the exact specification. In this paper, we outline a periodic CS-based generative design pipeline that offers automated modelling, analysis, and inverse design solving of CS through the use of an integrated optimisation and finite-element analysis (FEA) framework. Specifically, a surrogate model-based optimisation scheme is proposed to design light-weight and high-strength functional parts by taking advantage of spatially varying conformal cubic periodic cellular structures.

Automated summary

This paper presents a generative design pipeline based on cellular structures, providing automated modeling, analysis, and inverse design solving. It utilizes an optimization and finite-element analysis (FEA) framework to design lightweight and high-strength functional parts by taking advantage of spatially varying conformal cubic periodic cellular structures.