Desenvolvimento de perfis aerodinâmicos a partir de suas características utilizando redes neurais artificiais

One 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 XFoil

Variação de temperatura e umidade e suas influências nas características físicas e mecânicas dos fios de algodão

Cotton is a hydrofilic textile fiber and, for this reason, it changes its properties according to the environment changes. Moisture and Temperature are the two most important factors that lead a cotton Spinning sector and influence its quality. Those two properties can change the entire Spinning process. Understanding this, moisture and temperature must be kept under control when used during the Spinning process, once the environment is hot and dry, the cotton yarns absorb moisture and lose the minimal consistency. According to this information, this paper was developed testing four types of cotton yarns, one kind of cotton from Brazil and the others from Egypt. The yarns were exposed to different temperatures and moisture in five different tests and in each test, six samples that were examined through physical and mechanical tests: resistance, strength, tenacity, yarn´s hairness, yarn´s evenness and yarn´s twisting. All the analysis were accomplished at Laboratório de Mecânica dos Fluídos and at COATS Corrente S.A., where, it was possible to use the equipments whose were fundamental to develop this paper, such as the STATIMAT ME that measures strength, tenacity, Zweigler G566, that measure hairiness in the yarn, a skein machine and a twisting machine. The analysis revealed alterations in the yarn´s characteristics in a direct way, for example, as moisture and temperature were increased, the yarn´s strength, tenacity and hairness were increased as well. Having the results of all analysis, it is possible to say that a relatively low temperature and a high humidity, cotton yarns have the best performance