The interaction of an aircraft's structure and the flight dynamics can degrade the performance of a controller designed only considering the rigid body flight dynamics. These concerns are greater for the next generation adaptive controls. These interactions lead to an increase in the tracking error, instabilities in the control parameters, and significant structural excitations. To improve the understanding of these issues the interactions have been examined using simulation as well as flight testing of a subscale aircraft. The scaling required for such a subscale aircraft has also been examined. For the simulation a coordinate system where the non-linear flight dynamics are orthogonal to the linear structural dynamics was defined. The orthogonality allows the use of separates models for the aerodynamics. For the non-linear flight dynamics, preexisting table lookups with extended vortex lattice are used to determine the aerodynamic forces. Strip theory is then used to determine the smaller, but still important, unsteady aerodynamic forces due to the flexible motion. Because the orientation of the engines is dependent on the structural deformations, the propulsive force is modeled as a non-conservative follower force. The simulation of the integrated dynamics is then used to examine the effects of the aircraft flexibility and resultant ASE interactions on the performance of adaptive controls. For the scaling, the complete similitude of a flexible aircraft was examined. However, this complete similitude is unfeasible for an actual model, so partial similitude is investigated using two approaches. First, the classical approximations of the flight dynamic modes are used to reduce the order of the coupled model, and consequently the number of scaling parameters required to maintain the physics of the system. The second approach uses sensitivity of the response to errors in the aircraft's nondimensional parameters. Both methods give a consistent set of nondimensional parameters which do not have significant influence on the aeroservoelastic interaction. These parameters do not need to be scaled, thus leading to a viable scaled model. A subscale vehicle has been designed which shows significant coupling between the flight dynamics and structural dynamics. This vehicle was used to validate the results of the scaling theory. Output error system identification was used to identify a model from the flight test data. This identified model provides the frequency of the short-period mode, and the effects of the Froude number on the flexibility. / Ph. D.

Drastic changes in aircraft operational requirements and the emergence of new enabling technologies often occur symbiotically with advances in technology inducing new requirements and vice versa. These changes sometimes lead to the design of vehicle concepts for which no prior art exists. They lead to revolutionary concepts. In such cases the basic form of the vehicle geometry can no longer be determined through an ex ante survey of prior art as depicted by aircraft concepts in the historical domain. Ideally, baseline geometries for revolutionary concepts would be the result of exhaustive configuration space exploration and optimization. Numerous component layouts and their implications for the minimum external dimensions of the resultant vehicle would be evaluated. The dimensions of the minimum enclosing envelope for the best component layout(s) (as per the design need) would then be used as a basis for the selection of a baseline geometry. Unfortunately layout design spaces are inherently large and the key contributing analysis i.e. collision detection, can be very expensive as well. Even when an appropriate baseline geometry has been identified, another hurdle i.e. vehicle scaling has to be overcome. Through the design of a notional Cessna C-172R powered by a liquid hydrogen Proton Exchange Membrane (PEM) fuel cell, it has been demonstrated that the various forms of vehicle scaling i.e. photographic and historical-data-based scaling can result in highly sub-optimal results even for very small O(10-3) scale factors. There is therefore a need for higher fidelity vehicle scaling laws especially since emergent technologies tend to be volumetrically and/or gravimetrically constrained when compared to incumbents. The Configuration-space Exploration and Scaling Methodology (CESM) is postulated herein as a solution to the above-mentioned challenges. This bottom-up methodology entails the representation of component or sub-system geometries as matrices of points in 3D space. These typically large matrices are reduced using minimal convex sets or convex hulls. This reduction leads to significant gains in collision detection speed at minimal approximation expense. (The Gilbert-Johnson-Keerthi algorithm is used for collision detection purposes in this methodology.) Once the components are laid out, their collective convex hull (from here on out referred to as the super-hull) is used to approximate the inner mold line of the minimum enclosing envelope of the vehicle concept. A sectional slicing algorithm is used to extract the sectional dimensions of this envelope. An offset is added to these dimensions in order to come up with the sectional fuselage dimensions. Once the lift and control surfaces are added, vehicle level objective functions can be evaluated and compared to other designs. For each design, changes in the super-hull dimensions in response to perturbations in requirements can be tracked and regressed to create custom geometric scaling laws. The regressions are based on dimensionally consistent parameter groups in order to come up with dimensionally consistent and thus physically meaningful laws. CESM enables the designer to maintain design freedom by portably carrying multiple designs deeper into the design process. Also since CESM is a bottom-up approach, all proposed baseline concepts are implicitly volumetrically feasible. Furthermore the scaling laws developed from custom data for each concept are subject to less design noise than say, regression based approaches. Through these laws, key physics-based characteristics of vehicle subsystems such as energy density can be mapped onto key system level metrics such as fuselage volume or take-off gross weight. These laws can then substitute some historical-data based analyses thereby improving the fidelity of the analyses and reducing design time.