Fixed-wing unmanned aerial vehicles (UAVs) with the ability to hover combine the speed and endurance of traditional fixed-wing fight with the stable hovering and vertical takeoff and landing (VTOL) capabilities of helicopters and quadrotors. This combination of abilities can provide strategic advantages for UAV operators, especially when operating in urban environments where the airspace may be crowded with obstacles. Traditionally, fixed-wing UAVs with hovering capabilities had to be custom designed for specific payloads and missions, often requiring custom autopilots and unconventional airframe configurations. With recent government spending cuts, UAV operators like the military and law enforcement agencies have been urging UAV developers to make their aircraft cheaper, more versatile, and easier to repair. This thesis discusses the use of the commercially available ArduPilot open source autopilot, to autonomously transition a fixed-wing UAV to and from hover flight. Software modifications were made to the ArduPilot firmware to add hover flight modes using both Proportional, Integral, Derivative (PID) Control and Model Reference Adaptive Control (MRAC) with the goal of making the controllers robust enough so that anyone in the ArduPilot community could use their own ArduPilot board and their own fixed-wing airframe (as long as it has enough power to maintain stable hover) to achieve autonomous hover after some simple gain tuning. Three new hover flight modes were developed and tested first in simulation and then in flight using an E-Flight Carbon Z Yak 54 RC aircraft model, which was equipped with an ArduPilot 2.5 autopilot board. Results from both the simulations and flight test experiments where the airplane transitions both to and from autonomous hover flight are presented.

Most combustion machines feature internal flows with very high energy densities. If a small fraction of the total energy contained in the flow is diverted into oscillations, large mechanical or thermal loads on the structure can be the result, which are potentially devastating if not predicted correctly. This is particularly the case for lightweight high performing devices like rockets. The problem is commonly known as "Combustion Instability". Several mechanisms have been identified in the past that link the flow field to the acoustics inside a combustion chamber and thereby drive or dampen oscillations, one of them being vortex shedding. The interaction between the highly sheared flow behind an obstacle and longitudinal acoustic oscillations inside a solid rocket booster is investigated both analytically and experimentally.The analytical approach is developed based on modeling of the second order acoustic energy. The energy model is applied to the specific flow conditions just downstream of a single baffle protruding into the flow. The mean flow profile is assumed to be of the form of a hyperbolic tangent, the unsteady acoustic velocities are assumed to be sinusoidally oscillating. Solutions for the unsteady rotational velocities and the unsteady vorticity are derived. The resulting flow field is utilized in stability calculations for a simplified two-dimensional axial-symmetric geometry. This yields to linear growth rates of the (longitudinal) oscillation modes. The growth rates are functions of the chamber geometry, the mean flow properties and the properties of the shear layer created by the flow restriction.A cold flow experiment is designed, tested and performed in order to validate the analytical findings. Flow is injected radially into a tube with acoustic closed-closed end conditions. A single baffle is installed in the tube, the axial position of the baffle is varied as well as its inner diameter. Frequency spectra of pressure oscillations are recorded. The experimental data is then compared qualitatively to the analytical growth rates. Those longitudinal Normal Modes, which feature the highest theoretical growth rates, are expected to be most prominent in the experimental data. This behavior is clearly observable.

Driving aim of this study was to develop a solver which is accurate enough to be used in analysis and fast enough to be used in optimization purposes. As a first step, a three-dimensional potential flow solver is developed using Fast Multipole Boundary Element (FMBEM) for calculating the pressure distributions in non-lifting flows. It is a steady state solver which uses planar triangular unstructured mesh. After the geometry is introduced, the program creates a prescribed wake surface attached to the trailing edge(s), obtains a solution using panel elements on which the doublet and source strengths vary linearly. The reason for using FMBEM instead of classical BEM is the availability of solutions of systems having DOFs up to several millions within a few hours using a standard computer which is impossible to accomplish with classical BEM. Solutions obtained for different test cases are compared with the analytical solution (if applicable), the experimental data or the results obtained by JavaFoil.

This study presented the design and implementation of a spatial Hinf controller to suppress the free and forced vibrations of a cantilevered smart beam. The smart beam consists of a passive aluminum beam with surface bonded PZT (Lead-Zirconate-Titanate) patches. In this study, the PZT patches were used as the actuators and a laser displacement sensor was used as the sensor. In the first part of the study, the modeling of the smart beam by the assumed-modes method was conducted. The model correction technique was applied to include the effect of out-of-range modes on the dynamics of the system. Later, spatial system identification work was performed in order to clarify the spatial characteristics of the smart beam. In the second part of the study, a spatial Hinf controller was designed for suppressing the first two flexural vibrations of the smart beam. The efficiency of the controller was verified both by simulations and experimental implementation. As a final step, the comparison of the spatial and pointwise Hinf controllers was employed. A pointwise Hinf controller was designed and experimentally implemented. The efficiency of the both controllers was compared by simulations.

In this study, the non-equilibrium Johnson and King Turbulence Model (JK model) is implemented in a three-dimensional, Navier-Stokes flow solver. The main program is a structured Euler/Navier-Stokes flow solver in which spatial discretization is accomplished by a finite volume formulation and a multigrid technique is used as a convergence accelerator. The aim is the validation of this in-house developed CFD (Computational Fluid Dynamics) tool with this enhanced enlarged capability in order to obtain a reliable flow solver that can solve flows over swept wings accurately. Various test cases were evaluated against reference solutions in order to demonstrate the accuracy of the newly implemented JK turbulence model. The selected test cases are NACA 0012 airfoil, ONERA M6 wing, DLR-F4 wing and two wings taken from the 3rd Drag Prediction Workshop. The solutions were analyzed and discussed in detail. The results show appreciably good agreement with the experimental data including force coefficients and surface pressure distributions.

In this study, the structural optimization of a cruise missile wing is accomplished for the aerodynamic loads for four different flight conditions. The flight conditions correspond to the corner points of the V-n diagram. The structural analysis and optimization is performed using the ANSYS finite element program. In order to construct the flight envelope and to find the pressure distribution in each flight condition, FASTRAN Computational Fluid Dynamics program is used. The structural optimization is performed for two different wing configurations. In the first wing configuration all the structural members are made up of aluminum material. In the second wing configuration, the skin panels are all composite material and the other members are made up of aluminum material. The minimum weight design which satisfies the strength and buckling constraints are found for both wings after the optimization analyses.

In this thesis, gas-kinetic methods for inviscid and viscous flow simulations are developed. Initially, the finite volume gas-kinetic methods are investigated for 1-D flows as a preliminary study and are discussed in detail from theoretical and numerical points of view. The preliminary results show that the gas-kinetic methods do not produce any unphysical flow phenomena. Especially the Gas-Kinetic BGK method, which takes into account the particle collisions, predicts compressible flows accurately. The Gas-Kinetic BGK method is then extended for the solution of 2-D and 3-D inviscid and viscous flows on unstructured/hybrid grids. The computations are performed in parallel. Various inviscid and viscous test cases are considered and it is shown that the Gas-Kinetic BGK method predicts both inviscid and viscous flow fields accurately. The implementation of hybrid grids for viscous flows reduces the overall number of grid cells while enabling the resolution of boundary layers. The parallel computations significantly improve the computation time of the Gas-Kinetic BGK method which, in turn, enable the method for the computation of practical aerodynamic flow problems.

A dynamic flight model of a jet trainer aircraft is developed in MATLAB-SIMULINK. Using a six degree of freedom mathematical model, non-linear simulation is used to observe the longitudinal and lateral-directional motions of the aircraft following a pilot input. The mathematical model is in state-space form and uses aircraft stability and control derivatives calculated from the aircraft geometric and aerodynamic characteristics. The simulation takes the changes in speed and altitude into consideration due to pilot input and demonstrates the non-linearity of the aircraft motion. The results from the simulation are compared with the results from flight characteristics manual of the actual aircraft to validate the mathematical model used. The simulation is carried out for a number of airspeed and altitude combinations to examine the effect of changing speed and altitude on the aircraft dynamic response.

To decrease the computational cost of genetic algorithm optimizations, surrogate models are used during optimization. Online update of surrogate models and repeated exchange of surrogate models with exact model during genetic optimization converts static optimization problems to dynamic ones. However, genetic algorithms fail to converge to the global optimum in dynamic optimization problems. To address these problems, a multiploid genetic algorithm optimization method is proposed. Multi-fidelity surrogate models are assigned to corresponding levels of fitness values to sustain the static optimization problem. Low fidelity fitness values are used to decrease the computational cost. The exact/highest-fidelity model fitness value is used for converging to the global optimum. The algorithm is applied to single and multi-objective turbine blade aerodynamic optimization problems. The design objectives are selected as maximizing the adiabatic efficiency and torque so as to reduce the weight, size and the cost of the gas turbine engine. A 3-D steady Reynolds-Averaged Navier-Stokes solver is coupled with an automated unstructured grid generation tool. The solver is validated by using two well known test cases. Blade geometry is modelled by 37 design variables. Fine and coarse grid solutions are respected as high and low fidelity surrogate models, respectively. One of the test cases is selected as the baseline and is modified in the design process. The effects of input parameters on the performance of the multiploid genetic algorithm are studied. It is demonstrated that the proposed algorithm accelerates the optimization cycle while providing convergence to the global optimum for single and multi-objective problems.

Accuracy of the finite difference sensitivity calculations are improved by calculating the optimum finite difference interval sizes. In an aerodynamic inverse design algorithm, a compressor cascade geometry is perturbed by shape functions and finite differences sensitivity derivatives of the flow variables are calculated with respect to the base geometry flow variables. Sensitivity derivatives are used in an optimization code and a new airfoil is designed verifying given design characteristics. Accurate sensitivities are needed for optimization process. In order to find the optimum finite difference interval size, a method is investigated. Convergence error estimation techniques in iterative solutions and second derivative estimations are investigated to facilitate this method. For validation of the method, analytical sensitivity calculations of Euler equations are used and several applications are performed. Efficiency of the finite difference sensitivity calculations is improved by parallel computing. Finite difference sensitivity calculations are independent tasks in an inverse aerodynamic design algorithm and can be computed separately. Sensitivity calculations are performed on parallel processors and computing time is decreased.