C Conferentia Proceedings
USM-2016-0063 Robust, performance-based and reliability-based structural optimization under uncertainty

Robust Optimization of the Aeroelastic Behavior of Tow Steered Composite Plates

Thiago Augusto M. Guimarães1; Domingos Rade2; Aldemir A. Cavallini Jr.1

1 Federal University of Uberlândia - School of Mechanical Engineering; 2 Technological Institute of Aeronautics

doi:10.20906/CPS/USM-2016-0063

Resumo

The use of tow steered laminate composite plates, in which the fibers follow pre-specified paths has shown to be capable of improving the aeroelastic behavior of plate-like structures using only discrete choices of fiber orientation (0º/90º/45º/ − 45º). Accounting for the potential benefits of this design strategy and the inevitable presence of uncertainties in actual manufacturing process, the study reported in this paper proposes a robust optimization methodology to increase the aeroelastic stability margin, accounting for uncertainties affecting tow steering and fiber placement angles. The strategy is applied to an idealized model of a cantilever wing, consisting of a small symmetric composite plate containing six plies, which has already been used in a number of previously reported works, for various purposes. The aeroelastic model used to evaluate flutter and divergence instability results from the combination of a structural model based on the Rayleigh-Ritz approach and a quasi-steady aerodynamic model based on the strip theory with the inclusion of the term of unsteadiness in pitch velocity.Moreover, the deterministic optimization is performedby using the algorithm of differential evolution, and the robust optimization combines deterministic analysis with a Monte Carlo Simulation and Latin-Hypercube Sampling.

Palavras-chave: Tow steering; Composite materials; Robust optimization

Como citar

Thiago Augusto M. Guimarães; Domingos Rade; Aldemir A. Cavallini Jr.. “Robust Optimization of the Aeroelastic Behavior of Tow Steered Composite Plates”. 3rd International Symposium on Uncertainty Quantification and Stochastic Modeling. UNCERTAINTIES2016. 2016. DOI: 10.20906/CPS/USM-2016-0063