Ole Burghardt, SciComp Title: Conjugate heat transfer support within SU2 Abstract: Computing estimations for heat fluxes from a heated solid’s wall into a cooling fluid flow is based on a good assumption of the wall’s temperature distribution. If such a … Continue reading →

Tim Albring, SciComp Title: Constrained-based Shape Parameterization Abstract: The ability to drive a baseline shape to one with superior performance hinges on the quality of the shape parameterization. On the one hand it is often useful to delimit the design … Continue reading →

Lisa Kusch, SciComp Title: Topology Optimization of Structures using the One-Shot Approach – Challenges and First Steps Abstract: The one-shot approach is traditionally used in the context of shape optimization with an underlying expensive partial differential equation constraint. If the … Continue reading →

Prof. Stefan Ulbrich, Nonlinear Optimization, TU Darmstadt Title: Robust Nonconvex PDE-Constrained Optimization based on Second Order Approximation Techniques and Reduced Order Models Abstract: We consider robust optimization techniques for nonconvex PDE-constrained problems involving uncertain parameters. The parameters are assumed to … Continue reading →

Prof. Charles Swanson, NASA Langley Research Center and Old Dominion University, USA Title: Transport Equations: Mathematical and Discrete Issues Abstract: There is considerable effort to solve the problem of well-posedness, regularity, and global existence for the Navier-Stokes equations. While progress … Continue reading →

Dr. Emre Özkaya, SciComp Title: Robust Aerodynamic Shape Optimization Using Adjoint Assisted Surrogate Modeling Abstract: In the present work, we present an hybrid optimization framework for robust aerodynamic shape optimization. The suggested method combines a Kriging (also known as Gaussian … Continue reading →

Dr. Josef Schüle, SciComp/RHRK Title: Using GPUs in SU2 code Abstract: GPUs may be used to reduce the required wall clock time in SU2 calculations. In this talk some early experiments on the usage of one GPU in implicit RANS … Continue reading →

Prof. Marc Pfetsch, Research Group Optimization, TU Darmstadt Title: Compressed Sensing and Discrete Optimization Abstract: The goal of this talk is to give an overview on compressed sensing from an discrete optimization/geometry point of view. The main problem in compressed … Continue reading →