Norberto is a PhD from the Department of Aeronautics working in the Loads Control and Aeroelasticity Lab from October 2018 to June 2022. His research interest lies in the simulation and modelling of very flexible aircraft including data-driven strategies, and implements his research on the in-house open source tool, SHARPy. He is also very interested in implementing robust machine learning methods to obtain forecasts and predictions of dynamical systems.
Prior to the PhD, he graduated in Aeronautical Engineering MEng with First Class Honours from Imperial College. During his undergraduate time, he spent a year working at Airbus Landing Gear in Filton and two summers at IberEspacio, a satellite thermal control firm, in Madrid.
He holds a Private Pilot Licence (FAA and EASA) and, whenever he is back home, makes the most out of the beautiful Spanish weather flying a Cessna 172. He is also an avid triathlete, member of the Imperial College Triathlon Club and Ironman finisher.
Goizueta N, Wynn A, Palacios R, 2022, Adaptive Sampling for Interpolation of Reduced-Order Aeroelastic Systems, Aiaa Journal, Vol:60, ISSN:0001-1452, Pages:6183-6202
et al., 2022, Flutter predictions for very flexible wing wind tunnel test, Journal of Aircraft: Devoted to Aeronautical Science and Technology, Vol:59, ISSN:0021-8669, Pages:1082-1097
et al., 2022, Modelling and numerical enhancements on a UVLM for nonlinear aeroelastic simulation, AIAA SCITECH 2022 Forum, American Institute of Aeronautics and Astronautics, Pages:1-20
Goizueta N, Wynn A, Palacios R, 2021, Fast flutter evaluation of very flexible wing using interpolation on an optimal training dataset, AIAA SCITECH 2022 Forum, American Institute of Aeronautics and Astronautics, Pages:1-21
Goizueta Alfaro N, 2021, SHARPy simulation and post-processing scripts for the Pre-Pazy Wing Model, v.1.1-1