Metodologia ótima robusta para o projeto de uma técnica de controle passivo de supressão do fenômeno de flutter em painéis compósitos de interesse aeronáutico

• Autor(a) principal: Ribeiro, Lorrane Pereira
• Data de Publicação: 2019
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFU
• Texto Completo: https://repositorio.ufu.br/handle/123456789/27176; http://dx.doi.org/10.14393/ufu.te.2019.2404
• topic: Aeroelasticidade; Aeroelasticity; Modelagem estocástica; Stochastic modeling; Materiais compósitos; Composite materials; Circuitos shunt multimodais; Multimodal shunt circuits; Otimização multiobjetivo robusta; Robust multiobjective optimization; CNPQ::ENGENHARIAS::ENGENHARIA MECANICA::MECANICA DOS SOLIDOS

Reliability and safety in aeronautical structures are fundamental aspects to dealt with. Thus, it is necessary to know the responses of such systems in order to investigate their dynamic and aeroelastic stability for various loading scenarios. The use of composite materials has been increasingly in aeronautical industries for the construction of lighter structures with better mechanical properties. However, problems such as vibrations and noise are augmented significantly by the use of such materials due to the construction of lighter structures with increasing their operating speeds. Therefore, it is necessary to use efficient control strategies to deal with such problems. This work demonstrates the feasibility of using a passive composite panel flutter control tool via multimodal shunt electrical circuits. For a more realistic application of industrial interest, uncertainties present in main design parameters of the control system was considered and these uncertainties modeled as Gaussian stochastic fields and discretized by Karhunèn-Loeve expansion in the context of the Stochastic Finite Element Method. In addition, to achieve a more efficient and robust multimodal shunt circuit in aeroelastic control, a robust multi-objective optimization strategy was also implemented. In this case, additional vulnerability functions were combined with the original problem objective functions to account uncertain parameters during the optimization process. However, due to high computational cost required to obtain the optimal and robust solutions, a model reduction technique well adapted to the aeroelectromechanical systems was used.