Direct and Inverse Problems for PDEs with Random Coefficients - Abstract
We consider robust optimization techniques for PDE-constrained problems involving uncertain parameters. The parameters are assumed to be contained in a given uncertainty set. We propose approximations of the robust counterpart based on linear or quadratic models which leads to a tractable problem. We show applications to the robust optimization of a permanent magnet synchronous motor geometry and to the robust geometry optimization of load-carrying structures governed by the elastodynamic wave equation.