<p> Wave propagation analysis in 1-D and 2-D composite structures is performed efficiently and accurately through the formulation of a User-Defined Element (UEL) based on the wavelet spectral finite element (WSFE) method. The WSFE method is based on the first order shear deformation theory which yields accurate results for wave motion at high frequencies. The wave equations are reduced to ordinary differential equations using Daubechies compactly supported, orthonormal, wavelet scaling functions for approximations in time and one spatial dimension. The 1-D and 2-D WSFE models are highly efficient computationally and provide a direct relationship between system input and output in the frequency domain. The UEL is formulated and implemented in Abaqus for wave propagation analysis in composite structures with complexities. Frequency domain formulation of WSFE leads to complex valued parameters, which are decoupled into real and imaginary parts and presented to Abaqus as real values. The final solution is obtained by forming a complex value using the real number solutions given by Abaqus. Several numerical examples are presented here for 1-D and 2-D composite waveguides. Wave motions predicted by the developed UEL correlate very well with Abaqus simulations using shear flexible elements. The results also show that the UEL largely retains computational efficiency of the WSFE method and extends its ability to model complex features.</p><p> An enhanced cross-correlation method (ECCM) is developed in order to accurately predict damage location in plates. Three major modifications are proposed to the widely used cross-correlation method (CCM) to improve damage localization capabilities, namely actuator-sensor configuration, signal pre-processing method, and signal post-processing method. The ECCM is investigated numerically (FEM simulation) and experimentally. Experimental investigations for damage detection employ a PZT transducer as actuator and laser Doppler vibrometer as sensor. Both numerical and experimental results show that the developed method is capable of damage localization with high precision. Further, ECCM is used to detect and localize debonding in a composite material skin-stiffener joint. The UEL is used to represent the healthy case whereas the damaged case is simulated using Abaqus. It is shown that the ECCM successfully detects the location of the debond in the skin-stiffener joint.</p>

<p> This research presents new methods to apply safety standards to Detect and Avoid (DAA) functions for Unmanned Aircraft Systems (UAS), using maneuvering target tracking and encounter models. </p><p> Previous DAA research methods focused on predefined, linear encounter generation. The new estimation and prediction methods in this research are based on the target tracking of maneuvering intruders using Multiple Model Adaptive Estimation and a realistic random encounter generation based on an established encounter model. </p><p> When tracking maneuvering intruders there is limited knowledge of changes in intruder behavior beyond the current measurement. The standard Kalman filter (KF) with a single motion model is limited in performance for such problems due to ineffective responses as the target maneuvers. In these cases, state estimation can be improved using MMAE. It is assumed that the current active dynamic model is one of a discrete set of models, each of which is the basis for a separate filter. These filters run in parallel to estimate the states of targets with changing dynamics. </p><p> In practical applications of multiple model systems, one of the most popular algorithms for the MMAE is the Interacting Multiple Model (IMM) estimator. In the IMM, the regime switching is modeled by a finite state homogeneous Markov Chain. This is represented by a transition probability matrix characterizing the mode transitions. A Markov Chain is a stochastic model describing a sequence of possible events in which the probability of each event depends only on the previous event. </p><p> This research uses the hazard states estimates (which are derived from DAA standards) to analyze the IMM performance, and then presents a new method to predict the hazard states. To reduce the prediction error, this new method accounts for maneuvering intruders. The new prediction method uses the prediction phase in the IMM algorithm to predict the future intruder aircraft states based on the current and past sensor measurements. </p><p> The estimation and prediction methods described in this thesis can help ensure safe encounters between UAS and manned aircraft in the National Airspace System through improvement of the trajectory estimation used to inform the DAA sensor certification process.</p><p>

<p> Accurate unsteady measurements are required for studying the flows in high speed turbomachines, which rely on the interaction between rotating and stationary components. Using statistics of phase locked ensembles simplifies the problem, but accurate frequency response in the 10-100 kHz range significantly limits the applicable techniques. This research advances the state of the art for phase resolved measurement techniques using for high speed turbomachinery flows focusing on the following areas: development, validation, and uncertainty quantification. Four methods were developed and implemented: an unsteady total pressure probe, the multiple overheat hot-wire method, the slanted hot-wire method, and the phase peak yaw hot-wire method. These methods allow for the entire phase locked average flow field to be measured (temperature, pressure, and velocity components, swirl angle, etc.). No trusted reference measurement or representative canonical flow exists for comparison of the phase resolved quantities, making validation challenging. Five different validation exercises were performed to increase the confidence and explore the range of applicability. These exercises relied on checking for consistency with expected flow features, comparing independent measurements, and cross validation with CFD. The combined uncertainties for the measurements were quantified using uncertainty estimates from investigations into the elemental error sources. The frequency response uncertainty of constant temperature hot-wire system was investigated using a novel method of illuminating the wire with a laser pulse. The uncertainty analysis provided estimates for the uncertainty in the measurements as well as showing the sensitivity to various sources of error.</p>

<p> A robust proportional-integral (PI) controller was synthesized for the F-16 VISTA (Variable stability In-flight Simulator Test Aircraft) using a linear matrix inequality (LMI) approach, with the goal of eventually designing and implementing a linear parameter-varying PI controller on high performance aircraft. The combination of classical and modern control theory provides theoretically guaranteed stability and performance throughout the flight envelope and ease of implementation due to the simplicity of the PI controller structure. The controller is designed by solving a set of LMIs with pole placement constraints. This closed-loop system was simulated in MATLAB/Simulink to analyze the performance of the controller. A robust <i> H</i>_&infin; controller was also developed to compare performance with PI controller. The simulation results showed stability, albeit with poor performance compared to the <i>H</i>_&infin; controlle </p>

<p> An experiment consists of a remote-controlled T-REX 600E Pro helicopter piloted above an underway 108-foot Patrol Craft&rsquo;s (YP) flight deck to analyze the effect of <i>Re_H</i> &ap; 3.4&times;10⁵ turbulent ship air wake on helicopter angular motion. The motion is measured by an inertial measurement unit (IMU) sensor mounted on the helicopter transmitting variably-spaced data in a 3-D Cartesian reference frame. Data is collected with the helicopter in locations above the flight deck which closely match actual takeoff/landing positions of US Navy H-60 helicopters above flight decks of air-capable ships (CG/DDG/FFG). This method is both an indirect way of qualifying the flow field and a practical way of measuring the actual effects of ship air wake turbulence on rotary-wing aircraft. Fourier analysis is performed on helicopter angular velocities to determine predominant frequencies of motion. Frequencies of this motion are compared with both pilot input frequencies and vortex shedding frequencies of incompressible, subsonic flow around 2-D and 3-D backward-facing step (BFS) geometries. These frequencies of motion are discussed in relation to the pilot&rsquo;s perception of motion and the phenomena of spatial disorientation. The spectra of pilot inputs in roll and pitch were found to have cutoff frequencies of 0.5 Hz and 0.7 Hz, respectively, which agree well with full-size helicopter pilot autospectra. A 3 Hz non-pilot initiated disturbance is noted; the source of this disturbance is thought to be due to interactions with airflow over the flight deck hangar or dynamic effects of the flybar on the helicopter.</p>

<p> Modern unmanned aerial vehicles (UAV) are made of lightweight structures, owing to the demand for longer ranges and heavier payloads. These lightweight aircraft are more susceptible to vibrations caused by atmospheric turbulence transmitted to the fuselage from the wings. These vibrations, which can cause damage to the payload or on board avionics present a serious problem, since air turbulence is expected to increase over the next few decades, due to climate change. </p><p> The objective of this thesis is to predict the vibration of an aircraft fuselage by establishing a relationship between wing and fuselage vibration. A combination of ANSYS^&reg; and MATLAB^&reg; modeling are used to simulate aircraft vibrations. First, the displacement of a lumped mass aircraft model to step and sinusoidal forces acting on the wings are compared to displacements calculated using modal superposition equations. Next, a state space representation of this system is found using system identification techniques, which uses wing displacement as input, and provides fuselage displacement as output. This state space model is compared to a derived state space model for validation. Finally, a three dimensional aircraft with distributed displacement sensors on its wings is modeled. A state space representation is established using the wing displacement output from the sensors as its input and the motion and rotation of the fuselage along the X, Y and Z axes as the output. </p><p> It is seen that the displacement results of the lumped mass system match with those calculated using modal superposition equations. The state space model can also accurately predict the fuselage vibration of the lumped mass system, when provided with wing displacement as input. More importantly, results have shown that the distributed vibration sensors on the three dimensional plane model are able to measure the wing displacements. Using the output from these distributed sensors, the motion and rotation of the fuselage about all three axes can be effectively predicted.</p>

Thesis (Ph.D.)--Syracuse University, 2008. / "Publication number:AAT 3345011."

Thesis (Ph.D.)--Syracuse University, 2008. / "Publication number: AAT 3323056."

Thesis (Ph.D.)--Syracuse University, 2008. / "Publication number: AAT 3334171."

Thesis (PH.D.)--Syracuse University, 2003. / "Publication number AAT 3113233."