Avaliação estrutural de sistemas de geração de energia eólica de pequeno porte utilizando métodos estocásticos

Detalhes bibliográficos
Ano de defesa: 2012
Autor(a) principal: Leandro Filho, Francisco de Assis
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Não Informado pela instituição
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://www.repositorio.ufc.br/handle/riufc/4473
Resumo: A structural evaluation of wind turbines is an issue that depends on many variables such as the wind regime, type and size of the wind turbine as well as the uncertainties related to these factors. To enter these uncertainties are established probability distributions for the physical parameters of the medium. In this paper, we propose a probabilistic structural analysis using the finite element method to evaluate the uncertainties associated with wind power generation. Assesses the response of the structure to random loads, for an analysis of system stability. With this purpose we developed a finite element model based on ANSYS R platform able to faithfully reproduce the behavior of the tower subjected to wind loads produced by wind in spades. A statistical approach, we determined the solution modal and dynamic response with respect to random wind loads. We used Monte Carlo method as the method of probabilistic analysis. Once charging is considered the random objective was to determine the variation of output parameters, given the initial uncertainties, analyze the characteristics of material properties, stresses, displacements, natural frequencies and frequency response of the structure to randomness of the wind. We analyzed the influence of each uncertainty about the response in the frequency domain. From the results, it can be concluded that the numerical tool used may represent efficiently models of stochastic processes in structures for wind power generation and perform sensitivity analysis of dynamic variables involved.