The accurate prediction of unsteady aerodynamic loads is of utmost importance in an aeroelastic simulation framework. Inaccurate prediction of these loads may result in inaccurate control design and evaluation, which, in a worst-case scenario, could cause loss of control of the vehicle. In addition to accuracy, these simulations require that the aerodynamic calculations be computationally efficient, so this often eliminates the use of full-order computational fluid dynamics (CFD) simulations, which can be quite computationally-intensive. Reduced-order models (ROMs) offer a solution to these competing demands of accuracy and efficiency by extracting pertinent data from a limited number of full-order CFD simulations and using that data to construct computationally-efficient models that retain a high amount of the accuracy of the full-order solution while running orders of magnitude faster computationally. This dissertation focuses on the development of a reduced- order modeling methodology for unsteady aerodynamics based on linear convolution combined with a nonlinear correction factor. Rather than being limited to a specific Mach regime, the ROM formulation is general enough such that it can be applied over a wide range of Mach regimes, from subsonic to hypersonic flight. The correction factor term allows the ROM to be accurate over a range of vehicle elastic modal deformation amplitudes as well as flight conditions representing of-design conditions. This generality is important because it permits a single form of the equations for aerodynamic loads to be used throughout all simulations in a controls framework, further increasing the efficiency. The evaluation of the ROM is accomplished through the comparison of ROM results with full-order CFD simulations for test-case geometries in the subsonic, transonic and super/hypersonic regimes.
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