Design Space Exploration, Optimization and Uncertainty Quantification
K. Maute, University of Colorado
L. Noel, TU Delft
Over the past fifteen years, research in isogeometric analysis has reduced geometric divide between CAD systems and FEA software. The close integration of CAD and analysis provides distinct advantages for design space exploitation, design optimization, and uncertainty quantification, as variations in geometry can be directly mapped onto the analysis model. The goal of this minisymposium is to bring together experts from computer-aided geometric design, numerical analysis, design optimization, and stochastic modeling to discuss challenges and opportunities in exploiting IGA for design und uncertainty quantification.