Application of convolutional neural networks to the fast simulation of fluid dynamic systems

Proyecto

Trabajo de Fin de Máster

Docente

Ekaitz Zulueta Guerrero

Centro

University of Basque Country (UPV/EHU)

Empresa

Siemens Gamesa

Curso

2022/2023

Descripción

This project consists of two well differentiated parts. In the first one, a Convolutional Neural Network (CNN) is employed to predict the temporal evolution of the velocity and pressure fields around a circle geometry. Secondly, Deep Learning (DL) techniques are used to predict and measure the most suitable form and size of a Gurney flap (GF) for a specific case.