The World Congress of Structural and Multidisciplinary Optimization, Beijing, China

Authors: Juan Pablo Leiva, Hong Dong, Brian Watson
Publication Date: May 20-24, 2019

Additive Manufacturing (AM) is a relatively new manufacturing process that can be used to generate complex parts which sometimes conventional processes cannot create. In recent years, users of AM technologies have started to use results from structural and topology optimization techniques to generate better AM designs. However, results from optimization cannot always be successfully or easily printed. In this paper, we describe some methods and techniques that allow the end user to generate structural design proposals which could be manufactured using 3D printing with minimum changes. In general, the methods and techniques described in this work are based on parameterizing the design domain and are developed for gradient-based topology optimization and can optionally be used together with other optimization methods such as shape and sizing. The proposed methods take into consideration irregular FEA meshes commonly used in industrial applications. The main focus of the methods discussed in this paper is to prevent that the final design contains overhang members with shallow angles as such features would either fail or require non-structural supports. The manufacturing requirements are built in the parameterization of the design space and will also be able to impose minimum member size which are also necessary to print 3D printed parts. The methods are discipline independent and have been implemented to be used with responses calculated from different analysis types such as statics, heat transfer, and/or dynamic problems. The discussed methods have been implemented in the GENESIS program and examples, that show their effectiveness, are included.