The experimental data collected during Phase II of this effort will provide an invaluable resource to the aeroelastic community. The methods employed in the development of these experiments will provide an experimental dataset that provides additional confidence that published structural dynamic behavior is consistent with the experimentally derived flutter boundary. Pressure measurement will provide an additional resource for code validation and for gaining insight into discrepancies between experimental and analytical data. Data at a variety of angles of attack will generate more data in the transonic regime that will be highly value for validation of computational methods. The advances in knowledge gained through this benchmark experiment have the potential to lead to improved performance in aerospace vehicles ranging from transports, to fighters, to launch vehicles. The proposed research has the potential to dramatically improve the aeroelastic design and analysis process for aerospace vehicles. Phase II development will result in a rich dataset for aeroelastic method validation. Application of these methods during the design process will provide better insight into aeroelastic and ASE behavior resulting in reduced weight and increased structural efficiency. This will result in improvements in overall vehicle performance that will be especially critical to new configurations such as truss braces wings, high speed transports, and blended wing body configurations. Initial application of the knowledge gained through this research will likely be targeted at supersonic transport configurations operating at transonic conditions. This insight into aeroelastic behavior will also improve aeroelastic and ASE analysis methods for a variety of other applications. These methods could be applied to a variety of applications including defense and civil. Demand for the results of this research will be found in the government and at major airframe manufacturers. Satisfying the existing demand for appropriate transonic aeroelastic validation data will provide a tremendous potential for this research.