Z. W. Thu

Deep Generative and Probabilistic Surrogate Modeling for Uncertainty-Based Airfoil Design Optimization

Uncertainty-based aerodynamic shape optimization is challenged by the curse of dimensionality and high computational costs. To address this, we propose a deep generative and probabilistic surrogate modeling for optimizing subsonic airfoils under uncertainty. A variational autoencoder learns a compact latent representat...