Freire Júnior, Raimundo Carlos SilvérioDiniz, Bruno da Cunha2014-12-172013-05-152014-12-172013-02-15DINIZ, Bruno da Cunha. Desenvolvimento de perfis aerodinâmicos a partir de suas características utilizando redes neurais artificiais. 2013. 114 f. Dissertação (Mestrado em Tecnologia de Materiais; Projetos Mecânicos; Termociências) - Universidade Federal do Rio Grande do Norte, Natal, 2013.https://repositorio.ufrn.br/jspui/handle/123456789/15701One of the current major concerns in engineering is the development of aircrafts that have low power consumption and high performance. So, airfoils that have a high value of Lift Coefficient and a low value for the Drag Coefficient, generating a High-Efficiency airfoil are studied and designed. When the value of the Efficiency increases, the aircraft s fuel consumption decreases, thus improving its performance. Therefore, this work aims to develop a tool for designing of airfoils from desired characteristics, as Lift and Drag coefficients and the maximum Efficiency, using an algorithm based on an Artificial Neural Network (ANN). For this, it was initially collected an aerodynamic characteristics database, with a total of 300 airfoils, from the software XFoil. Then, through the software MATLAB, several network architectures were trained, between modular and hierarchical, using the Back-propagation algorithm and the Momentum rule. For data analysis, was used the technique of cross- validation, evaluating the network that has the lowest value of Root Mean Square (RMS). In this case, the best result was obtained for a hierarchical architecture with two modules and one layer of hidden neurons. The airfoils developed for that network, in the regions of lower RMS, were compared with the same airfoils imported into the software XFoilapplication/pdfAcesso AbertoPerfis aerodinâmicos. Características aerodinâmicas. Redes neurais artificiais. Arquiteturas de redeAerodynamic airfoils. Aerodynamic characteristics. Artificial neural networks. Network architecturesDesenvolvimento de perfis aerodinâmicos a partir de suas características utilizando redes neurais artificiaismasterThesisCNPQ::ENGENHARIAS::ENGENHARIA MECANICA