  In the realm of aerospace design, achieving smooth curves is paramount,
particularly when crafting objects such as airfoils. Generative Adversarial
Network (GAN), a widely employed generative AI technique, has proven
instrumental in synthesizing airfoil designs. However, a common limitation of
GAN is the inherent lack of smoothness in the generated airfoil surfaces. To
address this issue, we present a GAN model featuring a customized loss function
built to produce seamlessly contoured airfoil designs. Additionally, our model
demonstrates a substantial increase in design diversity compared to a
conventional GAN augmented with a post-processing smoothing filter.
