Advanced aeroelastic simulations for practical fixed-wing and rotary-wing applications

The study of aeroelasticity has many applications in the aerospace industry. There is a need in the fixed-wing and rotary-wing fields to develop computational aeroelastic tools for industrial applications that are both rapid and robust. Aeroelastic tools that would benefit the industry were developed in this work to predict the transonic fixed-wing flutter boundary and to predict rotary-wing wind turbine performance.;The flutter boundary of a wing must be determined during development and certification of an aircraft, and is critical in the transonic regime, where nonlinear effects create a dip in the flutter boundary that cannot be predicted with traditional linear tools. A frequency domain correction procedure was developed to account for nonlinear aerodynamics in the transonic regime. The flutter boundary of the experimental benchmark AGARD 445.6 wing was calculated using time domain and corrected frequency domain methods. Both approaches adequately predicted the flutter boundary, but the corrected frequency domain approach is significantly faster than the time domain simulations and represents a unique opportunity for improved flutter prediction during aircraft wing design and development.;Wind turbines represent a rapidly growing source of renewable energy but current predictive tools have been shown to lack accuracy in predicting the power output of wind turbines. Additionally, wind farm performance must be properly predicted to develop accurate annual energy estimates. An aeroelastic, aeroacoustic, discrete vortex method code called SMARTROTOR was used to predict the performance of the benchmark National Renewable Energy Laboratory (NREL) wind turbine experiment. The code properly predicted the NREL wind turbine performance in normal and yawed flow conditions and has demonstrated the capability of simulating the wake interference effects present in wind farms. The grid-free characterization of the wake behind the turbine and the rapid simulation time compared with grid-based computational fluid dynamics solvers highlights the relevance of the code for industrial applications.