Investigating the use of neural network surrogate models in the evolutionary optimization of interplanetary low-thrust trajectories

Building on recent advances in the fields of low-thrust trajectory optimization based on shaping methods, Artificial Neural Networks, and surrogate models in Evolutionary Algorithms, an investigation into a novel optimization routine is conducted. A flexible Python tool to evaluate linked trajectories in a two-body model based on the hodographic...

Computational Method for Early-Stage Design Optimization of Naturally Ventilated Terminals

This thesis focuses on the development of a computational model for early-stage design decision support of naturally ventilated terminal structures. The model is developed in a parametric Rhino Grasshopper environment paired with Python coding and CFD analyses through OpenFOAM. Optimization of air distribution parameters is performed with...