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Nanocomposites are prominent candidates to extend the capabilities in areas of established fiber reinforced composites. Carbon nanotubes (CNT) with their outstanding mechanical, electrical, and thermal properties are of particular interest. Especially polymers profit from the addition of CNTs, and can be rendered significantly stiffer, stronger, and even electrically conductive. The resulting electrical conductance is deformation-sensitive, known as piezoresistivity, and is utilized in strain sensing applications. However, the polymer matrix introduces time- and temperature-dependency into the mechanical behavior, known as viscoelasticity, and thus affects the relationship between deformation and electrical conductivity over time. Although piezoresistivity and polymer viscoelasticity have been studied separately, the interaction of both phenomena is not well understood. This thesis presents a combination of numerical, experimental, and analytical investigations of the behavior of viscoelastic, piezoresistive nanocomposites. The major goal of this research is to elucidate the underlying mechanism of viscoelasticity on strain sensing via piezoresistivity, without relying on the ill-defined viscoelastic Poisson's ratio. In the study of piezoresistive nanocomposites, a statistical, three-dimensional representative volume element is created first via the finite element method, and validated through fundamental quantities, such as total conductance and elastic piezoresistivity, against experimental data from literature. A novel electron tunneling model is proposed, incorporating the chirality of individual CNTs with regard to the local alignment between CNTs. The change of tunneling resistance via mere reorientation of the CNTs is identified as another source of bulk resistance change under deformation and lead to an increase in the previously underestimated numerical strain-sensitivity. The multiaxial viscoelasticity is characterized via uniaxial creep tests at elevated temperatures, simultaneous measurement of axial and transverse strain, and the time-temperature superposition principle. A non-constant electrical resistance is observed numerically during stress relaxation at constant axial strain. The loss of sensing repeatability is shown in a cyclic numerical simulation.

Computational optimal control relies mainly on pseudospectral methods. The use of Chebyshev and Legendre polynomials is ubiquitous in the literature. This family of methods has good accuracy characteristics but constraints the nodal distribution to a certain grid that is denser at the boundaries. In this work, a set of novel Coupled Radial Basis Functions (CRBFs) is introduced as an approximation means for the nonlinear optimal control problem. CRBFs are real-valued Radial Basis Functions (RBFs) augmented with a conical spline. They do not require a specific nodal distribution. A plethora of research articles were published on the optimization of the shape parameter of RBFs. Unlike classic RBFs, CRBFs are insensitive to the shape parameter reducing the computational time needed to find an optimal shape parameter. The method introduced in this dissertation follows an indirect approach of solving optimal control problems. Hence, the method is initiated by deriving the necessary conditions of optimality. Consequently, CRBFs are used to approximate the resulting two-point boundary value problem (TPBVP) into a set of nonlinear algebraic equations (NAEs). The system of NAEs is then solved using a standard nonlinear solver. Numerical experiments of the proposed method are carried out and compared with exact solutions and other computational methods. The method is applied to classical nonlinear optimal control problems: Zermelo's problem, a duffing oscillator with various boundary conditions, and a nonlinear inverted pendulum on a cart. CRBFs-collocation shows superiority of computational speed over other methods and is easy to implement. For future work, this method is suitable for real-time control applications.

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Selection of materials to be used for components experiencing extreme conditions is a critical process in the design phase. Nickel-base superalloys have been frequently used for hot gas path components in the turbomachinery industry. These components are required to withstand both fatigue and creep at extreme temperatures during their service time. In general, the extreme temperature materials mostly embody polycrystalline, directionally solidified, and single crystal superalloys. It is essential for design engineers to predict accurate damage behavior and lifespan for these components to prevent catastrophic failures. This dissertation presents a new framework to represent mechanical behavior of Nickel-base superalloys under variety of loading conditions. A set of constitutive and lifing models that can be applied broadly are developed based on observed trends. Despite the development of over 30 variations of single crystal and directionally solidified Nickel-base superalloys, the behavior of these alloys nominally follows similar trends with respect to temperature and orientation. Temperature-, rate-, and orientation- dependence of these materials are studied. The goal is to eliminate extensive time and cost of experiments by creating parameters to be used in strength and life calculations for generic single crystal and directionally solidified Nickel-base alloys. In order to apply generic constants to deformation modeling, a crystal-plasticity model is modified to create stress-strain hysteresis loops. Strain, stress and multi-axial life models are developed to represent the lifing behavior of the candidate alloys under uniaxial and multiaxial environments. Tensile and low-cycle fatigue experiments are conducted to measure the accuracy of these models. Parameters for the models are built on regression fits in comparison with a comprehensive material database. This database includes elastic, plastic, creep, and fatigue properties.

Lean blowout is experimentally investigated for premixed bluff-body flames under various inlet velocity conditions, pressure gradients, and turbulence conditions to study the influence of fluid mechanics on the lean blowout process. A premixed combustion facility paired with a bluff-body flame stabilizer is used for the study. For all experiments, lean blowout is induced by temporally decreasing the fuel flow rate into the reactant stream. A suite of high-speed optical diagnostics are simultaneously employed to capture the transient blowout process: particle image velocimetry (PIV), stereoscopic PIV, and C2*/CH* chemiluminescence imaging. These diagnostics allow for the instantaneous flame boundary, velocity fields, equivalence ratios, and local flame strain rates to be evaluated during blowout. For all testing conditions, the results show that the blowout process is highly coupled to the fluid mechanics within the reacting domain and blowout is driven from flame-flow interactions (i.e. flame-vorticity interactions or flame-turbulence interactions). The results also demonstrate that altering the vorticity dynamics or turbulence conditions within the reacting domain can profoundly augment or attenuate the blowout process.

Modern propulsion and power generation technology operates under highly turbulent conditions to promote increased efficiency. The coupled relationship between the turbulence conditions and imposed pressure gradients on reacting flow dynamics are explored by decomposing the vorticity transport terms to quantify the vorticity budgets under varying conditions. This is performed on a bluff-body reacting flow-field by utilizing the two-dimensional diagnostics of particle image velocimetry (PIV) and CH* chemiluminescence to allow for a resolved velocity field and flame front. The vorticity budget is determined by utilizing a mean conditional fluid element tracking procedure to quantify the evolution of the individual vorticity terms through the flame front. The results indicate that the flow-field is more sensitive to turbulence conditions, which when increased promote a shift towards flow-field dynamics resembling non-reacting conditions with the exothermic term contributions diminished. Additionally, since the turbulent dynamics in reacting flow-fields create strong three-dimensional behaviors tomography is implemented to capture three-dimensional flow-field and flame structure. A fiber-based endoscope method is implemented to capture multiple viewpoints simultaneously on a single camera sensor to examine the efficacy and limitations of the approach for reacting flows. Tomographic PIV and CH* chemiluminescence measurements are captured for a Bunsen flame and compared to traditional two-dimensional measurements. The PIV measurements indicate that there is agreement between the measurement techniques when considering the average velocity and vorticity fields. However, there is increased divergence when examining the instantaneous terms. The CH* chemiluminescence revealed that the measured intensity gradients are similar although there is considerable warping in the of the flame geometry near the base of the burner which diminishes near the center of the flame height. Lastly, optimal viewing angles are determined utilizing luminescent molds to help mitigate any warping errors which were encountered when conducting chemiluminescence measurements.

The current research investigates next-generation alternative biofuels for internal combustion engines. This research is part of the Co-Optimization of Fuels and Engines initiative (Co-Optima) from the US Department of Energy. This initiative is focused on accelerating the introduction of scalable, affordable, and sustainable biofuels for highly efficient burning and low emissions internal combustion engines. The experiment consists of a Gasoline Direct Injector (GDI) designed for a Control Volume Combustion Chamber (CVCC) equipped with a viewing window to capture high-speed broadband chemiluminescent imaging. Time-resolved spray images were analyzed to extract the dispersion flow dynamic behavior for medium to heavy-duty engine biofuels known as Butylcyclohexane, Dodecane, Formaldehyde Dibutyl Acetyl, and Nonanol. These biofuels were compared to the conventional Diesel neat and a volumetric fraction basis of 10 and 30 percent with Diesel. Macroscopic analysis of the injector revealed that the temporal evolution of spray cone angle is a function of the Aerodynamic Weber Number for the neat fuels. The breakup length extracted from the tip penetration was inversely related to the Aerodynamic Weber Number. Blend characterization revealed a dampening effect on the spray cone angle compared to the neat fuel, and the breakup lengths were coupled to Diesel. The primary breakup mechanism of each fuel injected by a GDI injector was studied using a novel modal analysis technique called Robust Multi-Resolution Dynamic Mode Decomposition (RMrDMD), which deconstructs the nonlinear dynamical systems into multiresolution time-scaled components that capture the intermittent coherent structures. It was found that using the RMrDMD, the dominant route of breakup for these biofuels injected with a Continental GDI injector occurred at a unique Strouhal number of 0.18 related to a specific spatial breakup mechanism that portrayed globule breakup. The critical secondary atomization parameter Sauter Mean Diameter (SMD) was examined with a Particle Doppler Interferometer (PDI). The SMD extracted was utilized with an evaporation model for each neat fuel. Results show that Dodecane has the fastest evaporation rate in comparison to all the other fuels. Within the CVCC, direct fuel injection combustion characteristics, specifically emissions, heat release rate, ignition delay, and Direct Cetane number, were investigated and compared. In addition, a local fuel-air distribution map was constructed for each of the fuel and their blends using the relationship between the chemiluminescence intensity ratio of C2* and Ch* and the premixed equivalence ratio

In recent years, technological advances have shown a strive for more automated processes in agriculture, as seem with the use of unmanned aerial vehicles (UAVs) with onboard sensors in many applications, including disease detection and yield prediction. In this thesis, an octorotor UAV is presented that was designed, built, and flight tested, with features that are custom-designed for strawberry orchard disease detection. To further automate the disease scouting operation, geolocation, or the process of determining global position coordinates of identified diseased regions based on images taken, is investigated. A Kalman filter is designed, based on a linear measurement model derived from an orthographic projection method, to estimate the target position. Simulation, as well as an ad-hoc experiment using flight data, is performed to compare this filter to the extended Kalman filter (EKF), which is based on the commonly used perspective projection method. The filter is embedded onto a CPU board for real-time use aboard the octorotor UAV, and the algorithm structure for this process is presented. In the later part of the thesis, a probabilistic data association method is used, jointly with a proposed logic-based measurement-to-target correlation method, to analyze measurements of different target sources and is incorporated into the Kalman filter. A simulation and an ad-hoc experiment, using video and flight data acquired aboard the octorotor UAV with a gimballed camera in hover flight, are performed to demonstrate the effectiveness of the algorithm and UAV platform.

Emissions, flame behavior, and flow-field characteristics of a high-pressure reacting jet-in-crossflow are experimentally studied at industry-relevant conditions. An experimental facility consisting of a headend burner, optically accessible test section, and converging exit nozzle is designed, manufactured, and operated over a wide range of conditions for the study. The axial stage consists of an injector that can be modified into three configurations: fully premixed, partially premixed, and non-premixed. Particle image velocimetry (PIV) is used to obtain flow-field dynamics, high-speed CH* chemiluminescence is leveraged to analyze flame characteristics, and emission measurements are made at the exit of the facility to quantify nitrogen oxides (NOx), and carbon monoxide (CO) emissions. These measurement techniques provide insight into flame-flow field interaction, the effects of injector geometry on flame liftoff and stabilization, jet trajectories in the presence of heat release, and how flame stabilization mechanisms affect emissions. The results show for a non-premixed configuration, the flame is lifted further downstream and burns at its core compared to the fully premixed configuration. The results also demonstrate these highly lifted flames provide a significant improvement in NOx formation of the axial stage. For conditions where the flame ignites near the jet exit, the jet centerline is pushed further into the crossflow compared to jets where the flame is lifted further downstream. A jet trajectory correlation that accounts for pressure and heat release is proposed.