2 papers
cs.CE2025
Dflow-SUR: Enhancing Generative Aerodynamic Inverse Design using Differentiation Throughout Flow Matching
Aobo Yang, Zhen Wei, Rhea Liem +1
Generative inverse design requires incorporating physical constraints to ensure that generated designs are both reliable and accurate. However, we observe that current state-of-the…
cs.LG2025
Bayesian Optimization of a Lightweight and Accurate Neural Network for Aerodynamic Performance Prediction
James M. Shihua, Paul Saves, Rhea P. Liem +1
Ensuring high accuracy and efficiency of predictive models is paramount in the aerospace industry, particularly in the context of multidisciplinary design and optimization processe…