Selfadapting Surrogate Model for Fluid Dynamic Optimization

Derivative-based optimization of fluid flows is a well established field, but often prohibitively expensive for multi-objective optimization tasks. We target adaptive, algorithmic differentiation-based surrogate models enabling multi-objective optimization with error estimation for the maritime industry.