BibTex format
@inproceedings{Gaymann:2019,
author = {Gaymann, A and Schiaffini, G and Massini, M and Montomoli, F and Corsini, A},
title = {Neural network topology for wind turbine analysis},
year = {2019}
}
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Citation
RIS format (EndNote, RefMan)
TY - CPAPER
AB - In this work Artificial Neural Networks (ANN) are used for a multi-target optimization of the aerodynamics of a wind turbine blade. The Artificial Neural Network is used to build a meta-model of the blade, which is then optimized according to the imposed criteria. The neural networks are trained with a data set built by a series of CFD simulations and their configuration (number of neurons and layers) selected to improve performances and avoid over-fitting. The basic configuration of the airfoil is the profile S809, which is commonly used in horizontal axis wind turbines (HAWT), equipped with a Coanda jet. The design position and momentum of the jet are optimized to maximize aerodynamic efficiency and minimize the power required to activate the Coanda Jet.
AU - Gaymann,A
AU - Schiaffini,G
AU - Massini,M
AU - Montomoli,F
AU - Corsini,A
PY - 2019///
TI - Neural network topology for wind turbine analysis
ER -