Gradient-based optimization is a powerful tool for advancing engineering applications. 

Its success relies on three key ingredients: 

• accurate simulation models, 

• efficient gradient calculations, 

• and carefully chosen optimization methods. 

In this seminar, I will demonstrate how I developed fast, physics-based CFD models for nuclear fusion that are now being used for the design of future reactors. A particular focus will be on the challenges and solutions for obtaining gradients from Monte Carlo particle simulations, which are critical for modeling neutral-plasma interactions in fusion and neutron transport in fission systems. Lastly, I will discuss the application of these methods to the design of heat exchangers for lead-cooled small modular reactors (SMRs). The unique properties of liquid lead, particularly its low Prandtl number, introduce additional complexities for the optimization.

Niels Horstens