Preliminary Study of Airfoil Design Synthesis Using a Conditional Diffusion Model and Smoothing Method

Generative models such as generative adversarial networks and variational autoencoders are widely used for design synthesis. A diffusion model is another generative model that outperforms GANs and VAEs in image processing. It has also been applied in design synthesis, but was limited to only shape generation. It is important in design synthesis to generate shapes that satisfy the required performance. For such aims, a conditional diffusion model has to be used, but has not been studied. In this study, we applied a conditional diffusion model to the design synthesis and showed that the output of this diffusion model contains noisy data caused by Gaussian noise. We show that we can conduct flow analysis on the generated data by using smoothing filters.