Research areas of the Chair for Scientific Computing:
- Nonlinear Optimization
- Numerical Optimization
- Optimization and Control with PDEs
- Aerodynamic Shape Optimization in Multidisciplinary Design Context
- Optimal Active Flow Control
- Topology Optimization
- Robust Design
- Uncertainty Quantification (UQ)
- Partial Differential Equations
- Adjoint State Equations
- Computational Fluid Dynamics (CFD)
- Computational Aeroacoustics (CAA)
- Computational Structural Mechanics (CSM)
- Algorithmic Differentiation (AD)
- Machine Learning (ML)
- High-Performance Computing (HPC)
Some Research Projects
- SIVERT – Secure & Intelligent Visualization & Real-Time Reconstruction Techniques (for pCT)
- Algorithmic Differentiation in High-Energy Physics
- Machine Learning for Turbulence Modelling
- Hybrid RANS/LES Simulation for Turbulent Flows
- Aeroacoustic Prediction and Optimization
- Optimal Flow Control
- Optimization of Aero Engines
- One-Shot Optimization