Generative Design by Deep Learning

  • Paper:
    International Design & Engineering Technical Conferences, 2018. (PDF)
Design Automation by Integrating Generative Adversarial Networks and Topology Optimization

Recent advances in deep learning enable machines to learn existing designs by themselves and to create new designs. Generative adversarial networks (GANs) are widely used to generate new images and data by unsupervised learning. This research proposes a design automation process by combining GANs and topology optimization. The suggested process has been applied to the wheel design of automobiles and has shown that an aesthetically superior and technically meaningful design can be automatically generated without human interventions.