Darwin Rajpal, Roeland De Breuker
DOI Number: N/A
Conference number: IFASD-2017-160
Including a gust analysis in an optimization framework is computationally inef-ficient as the critical load cases are not known a priori and hence a large number of points within the flight envelope have to be analyzed. Model order reduction techniques can provide significant improvement in computational efficiency of an aeroelastic analysis. In this paper a reduced order aeroelastic model is formulated by reducing the aerodynamic system with a balanced proper orthogonal decomposition and coupling it to a structural solver. It is demonstrated that the dominant modes of the aerodynamic model can be assumed to be constant for varying equivalent airspeed and Mach number, enabling the use of a single reduced model for the entire flight envelope. Comparison of the results from the full and reduced order aeroelastic model shows a high accuracy of the latter and a large saving in computational cost. A dynamic aeroelastic optimization framework is then formulated using the reduced order aeroelastic model. Results show that both dynamic and static loads play a role in optimization of the wing structure. Furthermore, the worst case gust loads change during the optimization process and hence it is important to identify the critical loads at every iteration in the optimization.