1 citations · 2 across the 4 of their papers we have counts for
4 papers
Parameter conditioned interpretable U-Net surrogate model for data-driven predictions of convection-diffusion-reaction processes
Michael Urs Lars Kastor, Jan Rottmayer, Anna Hundertmark +1
We present a combined numerical and data-driven workflow for efficient prediction of nonlinear, instationary convection-diffusion-reaction dynamics on a two-dimensional phenotypic…
Adjoint-Based Aerodynamic Shape Optimization with a Manifold Constraint Learned by Diffusion Models
Long Chen, Emre Oezkaya, Jan Rottmayer +3
We introduce an adjoint-based aerodynamic shape optimization framework that integrates a diffusion model trained on existing designs to learn a smooth manifold of aerodynamically v…
Data-driven aerodynamic shape design with distributionally robust optimization approaches
Long Chen, Jan Rottmayer, Lisa Kusch +2
We formulate and solve data-driven aerodynamic shape design problems with distributionally robust optimization (DRO) approaches. Building on the findings of the work \cite{gotoh201…
Trailing-Edge Noise Reduction using Porous Treatment and Surrogate-based Global Optimization
Jan Rottmayer, Emre Özkaya, Sutharsan Satcunanathan +6
Broadband noise reduction is a significant problem in aerospace and industrial applications. Specifically, the noise generated from the trailing edge of an airfoil poses a challeng…